4.2 Applications and skills
4.2.4 Assessing claims about climate change
As you read through this page, consider the following:
- When is skepticism appropriate?
- In what circumstances are correlative links as powerful as causal links?
- What are some ways in which bias might be introduced unintentionally into discussions about climate change?
Evidence for climate change
The National Oceanic and Atmospheric Agency (NOAA) has been collecting data on atmospheric carbon dioxide levels at Mauna Loa, in Hawaii, for over 60 years. A summary of the Agency’s data is shown in Figure 4.2.4a.
Figure 4.2.4b – Methane concentration measured through ice core samples and by air monitoring stations
Methane is another very important greenhouse gas, which is produced when coal is burned, and in agriculture. Atmospheric levels of methane have been increasing rapidly since the Industrial Revolution, as shown in Figure 4.2.4b.
All the data from Figures 4.2.2a and 4.2.2b provides strong correlative evidence that increases in carbon emissions, and subsequently climate change, are caused by human activity.
Correlation and causation
Correlative and observational studies are very important lines of evidence in the debate on climate change. It would be impossible to demonstrate experimentally that climate change is not caused, or at least amplified, by human activities. Attempting to do so would require that scientists reduce carbon dioxide emissions to pre-industrial levels.
However, correlative studies are not enough. The link between human activities and climate change is supported by a theoretical understanding of how the enhanced greenhouse effect leads to increasing global temperatures. It is further supported by localised studies and predictions from computer models.
Here is an example. Based on our understanding of the carbon cycle and global climate change, scientists have predicted the following consequences for Arctic ecosystems:
- Increased release of carbon dioxide due to decomposition in soils previously covered by permafrost.
- Increased pathogens and insect pests on newly exposed soils.
- Habitat loss for large carnivores, resulting in redistribution of prey species.
Monitoring data from different sites confirms the relationship between loss of ice in the Arctic, and carbon dioxide levels. Correlations can be as powerful as experimental evidence when there is a scientifically sound explanation linking variables.
Skepticism and public understanding of science
Scientists display skepticism when making claims. Skepticism is an important part of the scientific process, since it encourages strong evidence and research. There are many legitimate reasons why scientists are skeptical, for example:
- Environmental chemists, biologists and physicists normally have a very narrow range of expertise, so experts in one field may disagree with the methodologies and goals of another field.
- Predictions based on computer modelling programs vary depending on whether individuals choose to be conservative, or to overestimate possible long-term effects of climate change. Models and predictions vary widely for another important reason: that natural systems tend to display emergent properties. The carbon cycle involves both living and non-living systems on a global scale and their interactions. It is very difficult to understand whether correlations between parts of the system are relevant or not.
Critics of climate change often exaggerate the legitimate skepticism shown by scientists in order to heighten the public debate on climate change in the following ways:
- The straw man fallacy – while there is no consensus among scientists about the extent of damage or long-term consequences of climate change, there is consensus that climate change is occurring and that human activity is involved. Critics will premise their arguments by saying that scientists can’t agree on anything, or by misrepresenting important aspects of the debate. These ‘straw men’ scientists simply don’t exist.
- Confirmation bias – scientists collect data on a large scale, analyse anomalies and look for patterns. Critics are selective in their representation of the data. Only data that supports their theory is included in the debate.
When the public form opinions on climate change, it is difficult to distinguish between well-researched science on the one hand, and political or economic ideology on the other. It is important that we recognise logical fallacies when analysing claims about the anthropogenic causes of climate change.
Figure 4.2.4c – The reductionist approach to science
This cartoon illustrates, ironically, the reductionist approach to science. The mathematician on the right side believes every other academic discipline can be redefined simply as applied maths.
Check your understanding
Suggest reasons for the monthly variation in carbon dioxide levels illustrated in the data from Mauna Loa (Figure 4.2.4a).
Use the NOAA database to analyse concentrations of greenhouse gases from different sources NOAA database: http://www.esrl.noaa.gov/psd/data/
Figure 4.2.4e – Device wearing cow
Novel ways to collect data: this cow is wearing a device that captures methane gas released in flatulence.
Did you know?
A significant source of methane – an important greenhouse gas – comes from livestock. Scientists in Argentina are trying to capture waste gases in an attempt to understand how much is being produced, and whether it might be used as a source of fuel.
- As the outside temperature rises, ice cream sales increase.
- Brown-eyed students get better IB exam scores than blue-eyed students.
The precautionary principle guides decision-making processes in the absence of scientific consensus. If an action or decision has the potential to do harm, policy-makers have the social responsibility to err on the side of caution and make decisions that limit potential harm. There seems to be no consensus among scientists about the speed and extent of damage on ecosystems related to climate change. Why should policy-makers use conservative models to make decisions on carbon reduction strategies?
The concept of emergent properties is consistent with a holistic, or systems, approach to science.
- The guiding philosophy of the systems approach is that nothing makes sense unless it is considered in the context of the whole system.
- At the other end of the spectrum is the reductionist approach: the idea that everything in nature can be explained by simple fundamental laws that apply to everything including living and non-living systems.
Reductionism dominates most scientific endeavour, but is there a limit to what we can learn about nature using this philosophy? Where do different scientific sub-disciplines fall on the spectrum?