Bibliometric research
Rarely do we encounter a scientific fact that stirs widespread debate and distrust as does the science of climate change. Despite consensus among climate specialists, and a theory that is supported by an ostensible mountain of facts from physical, natural, and cultural sciences, the climate change debate continues to be perpetrated by politicians, industrialists, academics, and arm-chair scientists. Much of the intense scepticism about climate change science began in 2009, when thousands of emails and data files were stolen from the Climate Research Unit (CRU) at the University of East Anglia, UK, and later exposed under the guise of a purported conspiracy to alter facts. The allegations claimed that scientists had only publicized results in support of their theory—that climate change is real and driven by human activities. Other facts, that may negate this claim, were said to have been hidden.
The lab uses meta-analysis methods to search for such evidence of publication bias in climate change publications. We use statistics on large set of data to identify potential biases in this field, and have in a recent paper rejected the hypothesis that non-significant effects are under-represented in the literature. We will now examine climate change literature further, expanding upon the initial analyses by including results published in low impact factor journals where most climate change science is published. By focusing on low impact journal in this field, we can bolster sample size and increase statistical power to help identify causal factors underlying putative reporting and stylistic biases.
Second, armed with the considerably larger data set (>4,200 studies) containing information about how environmental parameters affect biota, we can use meta-analysis to test the sensitivity of taxonomic groups to specific climatic drivers. For example, we can test if there exists general patterns in the literature about how ocean acidification (or temperature, or UV exposure, etc.) may affect calcifying species, and whether some taxa are more sensitive than others to acidification. Such knowledge will have profound importance for understanding global effects of climate change, and applied sciences such as conservation biology.
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