The Role of Historical Context in Understanding Past Climate, Pollution and Health Data in Trans-disciplinary Studies: Reply to Comments on More et al., 2017

Abstract

Understanding the context from which evidence emerges is of paramount importance in reaching robust conclusions in scientific inquiries. This is as true of the present as it is of the past. In a trans-disciplinary study such as More et al. (2017, https://doi.org/10.1002/2017GH000064) and many others appearing in this and similar journals, a proper analysis of context demands the use of historical evidence. This includes demographic, epidemiological, and socio-economic data—common in many studies of the impact of anthropogenic pollution on human health—and, as in this specific case, also geoarchaeological evidence. These records anchor climate and pollution data in the geographic and human circumstances of history, without which we lose a fundamental understanding of the data itself. This article addresses Hinkley (2018, https://doi.org/10.1002/2018GH000105) by highlighting the importance of context, focusing on the historical and archaeological evidence, and then discussing atmospheric deposition and circulation in the specific region of our study. Since many of the assertions in Bindler (2018, https://doi.org/10.1002/2018GH000135) are congruent with our findings and directly contradict Hinkley (2018), this reply refers to Bindler (2018), whenever appropriate, and indicates where our evidence diverges. Plain Language Summary This article highlights the crucial importance of historical and archaeoscientific data in trans-disciplinary studies of planetary health, in the form of a reply to two comments to a previous article (More et al., 2017, https://doi.org/10.1002/2017GH000064). This reply emphasizes the crucial importance of geographic and historical context in assessing the significance and reach of scientific findings. The article also showcases the growing role of “Big-Data” scale data sets of demographic, epidemiological, and historical records for understanding how past pollution and climate data affected populations, especially when cutting-edge methods (e.g., laser ablation inductively coupled plasma mass spectrometry) in climate science provide an ever more detailed chronology of past crises and long-term pollution trends.