Nice new paper showing how in situ cameras can be used to measure feeding rates!
New technology reveals the role of giant larvaceans in oceanic carbon cycling
(by Katija, Sherlock, Sherman & Robison)
Our meeting report is now online. Many thanks to Klas for the fantastic photos!
There is an exciting job offer for a 4-year postdoc position at the National Oceanography Centre, Southampton, looking at converting glider data into fluxes. Closing date: 4 May 2017.
Post Doctorate in Ocean Biogeochemistry and Autonomous Vehicles (Fixed Term, Full Time)
We feature on the NOC website and Twitter.
It was great to meet everyone this week and I’m really excited about the work we will produce. Thanks again to Sari for organising such a fab meeting. Our offices are still full of cake!
One thing that came up many times in the meeting was TEP, and how it often goes undetected using optical instruments. Or they might assume a TEP particle is many smaller ones rather than one larger aggregated particle. I realised after we left the meeting that this is probably an important point to highlight in the review paper. Detecting smaller particles and excluding TEP reduces estimated sinking rates and estimated organic carbon content. I thought we could have a small section in the discussion somewhere under fluxes/processes to highlight the complications of TEP. Really we should probably start to use a generic term e.g. ‘gelatinous material’ as TEP is just one of many kinds of sticky, transparent matter.
d and e are examples of manually classified ‘gelatinous’ particles. 10 % is an underestimation and I’m sure many of the smaller particles would have been formed in a similar manner but its harder to see, so the results are biased to larger particles.
Looking back at my FlowCAM data ‘gelatinous’ particles (classified manually myself) comprised 10 % of particles (n=810, likely an underestimation), sank faster than the other particles (gel=124 m/d, others=99 m/d, p=0.08) and were significantly larger (ESD gel=848 um, others=463um, p<0.001).
Food for thought!
I was on a course about metabolomics this week and they had a very interesting session on data processing. We were discussing how data processing can alter the interpretation, and that often people do not fully report how they have handled the data (quality control, baseline shift correction, outlier treatment, etc.) The metabolomics group at Birmingham are now trying to get everyone to record their workflow in detail and attach it as supplementary material to their work, so that anyone can easily reproduce their results.
Maybe we should aim to encourage people to do a similar thing for optical data. (Obviously building a tool like Birmingham did is completely out of the scope of this group!).
#dataprocessing #data #workflow