Most days, I get up, go to work, and zap corals with lasers. No, I am not building some twisted underwater version of a fly swatter, nor would I ever want to harm a coral. Rather, I am studying the chemical composition of coral skeletons to better understand how they grow, and hopefully improve our understanding of their sensitivity to ocean acidification.
I am using a technique called Raman spectroscopy. It is fundamentally different to conventional approaches for analyzing the chemistry of coral skeletons. While many studies have investigated element and isotope ratios by putting dissolved skeletons into a mass spectrometer, Raman spectroscopy is based on the scattering of light from a laser directed onto the coral skeleton. This offers several advantages: (i) it is fast, taking only 1 second per measurement, (ii) it can be applied on small spatial scales, down to about 1/100 the width of a human hair, and (iii) it is non-destructive, as the skeleton is not damaged in any way.
Based on the way the laser light is reflected from the skeleton, I can infer the chemical composition of the fluid from which it precipitated. This provides us with key insights into the mechanisms by which corals build their skeletons, and whether the skeleton-building process is sensitive to the rapid changes in seawater chemistry driven by invasion of human CO2 emissions into the ocean.
This new avenue of research into coral growth has led to several recent publications. The first paper developing the technique was published in November 2017 in Biogeosciences. Two follow-up application papers were both published this month, in Proceedings of the Royal Society B and Frontiers in Marine Science special issue on coral calcification. Within just the past year, we have already gained key insights into coral calcification with Raman spectroscopy, and this is just the beginning! Stay tuned for several new publications coming in the near future.
Have you ever tried to repeat the analysis described in a paper and found it difficult? Whether it's some missing raw data or you aren't sure which R package was used, this can be quite frustrating. Wouldn't it be nice if authors published all of the raw data and codes needed to run the analysis with a single click of a button? Now this is possible! Code Ocean is a new online tool that lets you upload data and run scripts written in a variety of languages (Matlab and R being most relevant for me). The great part is that one need not have these programs on their computer or even download the data; the scripts are run through the cloud with literally the click of a single button. (I realise this may sound like an advertisement, but I assure you that it is not. I am just genuinely excited about this.)
Thomas M. DeCarlo