As is seeming to be my norm of late (in fact, probably as much as the last six months or more), rather than regular posts, here’s another sporadic update. My apologies, but work and personal commitments have squeezed much of my former free time.

Here’s a comparison of the carbon dioxide levels from my research site compared to the global averages (sourced from here – don’t you love free and easy access to such data? I know I do. But then again, I’m a fan of making graphs, clearly).

Click the image to enlarge it. I’m always keeping an eye out for NOAA updates. Our data heads back up in March, as it did the year prior, but I need to wait for more NOAA data to include that.

Recently, I have also been re-running our raw data through the EddyProTM software produced by Li-Cor to compare outputs against our in-house processes. So far, the results are promising, with less than ±5% difference between the output of both. Of course, as both start with the same raw data, this still needs explaining – an interesting project awaits.

What I really like about the EddyProTM software is that it includes some really interesting / useful outputs that are not included in our standard in-house analysis. The two that stand out are 1) quality flagging that indicates suitability of data for journal grade studies and 2) analysis of the fetch, that is, how far away from the tower the actual flux most likely occurred. The latter, combined with wind direction would be incredibly valuable, especially as the heterogeneity of the test area increases (we’re fairly lucky – looking at images from the top of the tower, it’s easy to see just how uniformed our test area is for many kilometres in any direction).

The following is some of the resulting analysis of my first run of the data through the EddyProTM software.

I mention the morning bias on CO2 uptake in the average 24hrs over the entire research period to date (the data covers from the beginning of Aug 2010 until the end of March 2012), however, if you look a the monthly graphs, you will also notice the same bias appearing in many of the warmer months (Spring through to Autumn). The entire research period so far has been over a wetter-than-average section of time (at least when compared to the preceding decade).

Does it mean that the vegetation is so evolved that it doesn’t rely on rainfall as an environmental cue; that it “knows” better than to trust rainfall as an indicator of a boom year? Does it rely on ground water deep in the soil rather than rainfall? Is it instead the timing of rainfall rather than the amount?

There are a whole host of questions worth answering and it just goes to show how amazing any ecosystem is; our humble woodland doesn’t have towering mountain ash or a mind boggling assemblage of invertebrates per square metre, but it does have it’s secrets and those secrets are of value and interest to know about.