Week 3: Learning about Macroscopic Charcoal Analysis

After three weeks of lab work, I am facing some stark realities about scientific work. Research in particular is a source of incredible anxiety. It’s tedious work, tends to be awfully unpredictable and it’s clear to see how easy it is for the process to get frustrating, but every time I sit down to write for this blog particularly know what the bigger picture is but I think I will eventually figure it out.

What are paleoclimate proxies?

All my dread aside, in the past week and a half I have learnt a lot about lake Ayauchi as well as about paleoclimate proxies. Proxies, a word which seems to be thrown around a lot in the paleoclimate and paleoecology research fields, simply means environmental indicators or markers. Climate scientists look for them in sediment, trees, corals and even caves. Proxies are signals of environmental change and scientists collects lots of data recording variation of a specific proxy level over time. Subsequently this data becomes input for highly encoded computer models that process it to reveal past climate patterns, forecast expected environmental changes and hopefully provide insights that can inform decision making and climate policy innovation. In our lab, our prime paleoclimate proxy is charcoal/organic content as well as other signals of aridity.

Charcoal as a Proxy

I have been working with charcoal, a common proxy for drought. High levels of charcoal in paleo-sediments (like the core we are working on, Ayauchi aka AYC3) is often a signal of paleo-wildfires. Fires are likely to occur during dry periods and thus can be an ideal indicator of aridity. Of course, there might be other reasons why sediment records might show high levels of charcoal, human beings have been starting fires for a long time. Often using them (fires) for warmth, to facilitate daily chores and housekeeping as well as to clear land for cultivation. Some fires can be started by lightning, meteorites or volcanic activity. Nonetheless, even with all these other sources of paleo-wildfires in mind, charcoal remains an excellent indicator for periods of low precipitation and can thus serve as good evidence of paleo-droughts.

This is the reason why I have spent the last few weeks, looking for tiny specks of charcoal, one petri dish after another. Charcoal particles will disintegrate upon being probed as shown in the series of photos below.

Macroscopic Analysis of Charcoal from Paleo-sediments

The charcoal analysis process starts off with a sediment subsample taken from a larger core, in our case we have been using AYC3.

1. Weighing out.

We scoop out a known volume of sediment, (in this case 0.5 cubic cm) into a small beaker.

2. Sediment treatment

Next we add known volumes of a dispersant- Sodium hexametaphosphate (NaPO3)6 as well as Bleach (NaClO, plain old Clorox solution) as a bleaching agent. The dispersant helps to break apart sediment particles and Clorox discolours all dark organic matter, except charcoal which is resistant to bleach.

Reagent 1: Pour out 50 ml of Clorox solution

Reagent 2: Use 50 ml of Sodium Hexametaphosphate

3. Overnight Soak

We  then leave the samples soaking overnight, so that the sediment is completely bleached out and separated. We make sure to cover the samples to avoid dust and other contaminants from entering the sample solutions.

           

Sediment is left soaking in the solution overnight.

Jared uses a sediment sieve and squirt bottle to filter and rinse sediment

4. Wet Sieving After being left soaking, organic matter, charcoal and other material will be left suspended in the solution. Sieve out all suspended material into a petri dish.

5. Counting Charcoal

Place these samples under a simple Olympus SZX9 stereomicroscope and look out for black specks of charcoal. Once probed, charcoal particles disintegrate along a plane.

              

A stereomicroscope setup to observe charcoal particles from filtered samples. On the left a petri dish sample shows long flakes of old charcoal.

6. Data Analysis and Interpretations
Finally, we make sure to record the depth interval of sub-sampled sediment, as well as volume of sample, and number of charcoal particles counted. This is the raw data that will later be entered into our charcoal Matlab model (CharAnalysis Software), to compute for charcoal accumulation rates and detect peak points. Ultimately this data can be used to infer paleo-wildfire incidences and hopefully ultimately help us reconstruct the past climate environments of the Amazon region, particularly close to Lake Ayauchi.

Charcoal analysis is one of numerous paleoenvironmental research techniques and later on this summer, Jared, Colton and I will continue to learn many other methods of reconstructing paleoenvironmental conditions of the Amazon and Nepal regions.

Kopo :)