4.2 Applications and skills
4.2.3 Nature of science: The missing sink
Evidence, whether gathered by direct observation or experimentation, is fundamental to a common understanding of science. When systems are small and involve only a few variables, controlled experimentation yields very reliable data. For example, one can get very significant results testing the effect of seasonal variations of carbon dioxide concentration on photosynthetic output of a specific plant at a specific altitude by mimicking those conditions in a laboratory.
When scientists make predictions about systems on a larger scale, it is much less straightforward to devise controlled experiments, so scientists rely on observational data. It is important that the data is:
- quantitative – the common language of all the sciences is mathematics; mathematical analysis should be objective and easily interpreted by other scientists
- repeated – to improve reliability and to make predictions more accurate
- available – scientists rely on cooperation and sharing of data in databases in order to improve their own models.
Calculating carbon flux
- Meteorological flux towers take readings of important greenhouse gases including carbon dioxide, water vapour and methane at various locations around the world.
- Scientists then transform those readings, using complex algorithms, to generate flux ratios at different locations.
- Although the mathematics involved is complex, the collection method is based on a simple principle, as shown in Figure 4.2.3a1. Air currents travel upwards and downwards. The flux calculation takes into consideration the concentration of gases, and wind speed in vertical air movements, to calculate carbon flux ratio.
Where did the carbon go?
In making predictions and models, scientists need to keep fundamental laws of nature in mind. A natural law describes patterns in observed phenomena, and any observation that does not obey the law must be explained.
- The law of conservation of mass states that matter is neither created nor destroyed in any transformation or process. In other words, the amount of carbon released and the amount of carbon accumulated in the various carbon sinks on Earth, must be equal.
- When all the air-monitoring data from flux towers and data collected from the sea were compiled to generate a picture of global carbon flux, scientists could only account for some of the carbon emissions. The carbon cycle does not appear to be in balance.
- This was a very unexpected result, and is demonstrated in Figure 4.2.3b. Anthropogenic carbon emissions (releases) are shown on the top half of the graph. The bottom half of the graph shows where carbon accumulated. The carbon in the orange section is unaccounted for, and presumably accumulated in, a ‘missing sink’.
Figure 4.2.3b – Annual carbon flux, 1850–2000
- The missing carbon is a concern for scientists because it is difficult to make predictions on the consequences of the carbon emissions without a clear picture of where carbon is accumulating. They do not know where the carbon is, or how long it will stay stored; if all the missing carbon suddenly reappears in the atmosphere, it could be catastrophic.
Recall from Page: 4.1.3 Carbon cycling that carbon flux is a measurement of carbon exchange between processes in the carbon cycle. Scientists have used recent data from flux towers to estimate that human activity, especially the burning of fossil fuels and redirecting land use to agriculture, is responsible for putting approximately 7–8 gigatonnes of carbon dioxide into the atmosphere annually.
- The mathematics of calculating carbon flux is quite complex, but relies on a statistical tool called eddy covariance.
- Many hypothetical missing sinks have been proposed by scientists. One such proposal is forests in northern regions, which are known to be expanding because of higher temperatures. For more information on possible missing sinks, see:
Schindler, D.W. ‘The mysterious missing sink’ in Nature 398: 105–107, 11 March 1999.
- A natural law describes phenomena without necessarily explaining them.
- Theories provide models and mechanisms explaining how natural phenomena operate
- Hypotheses provide testable and falsifiable explanations for observed phenomena.
- Image credit: Burba, G.G., 2013, Eddy Covariance Method For Scientific, Industrial, Agricultural and Regulatory Applications, LI-COR, Biosciences, USA, 12-13pp., Copyright, LI-COR, Inc.