UMD: A Globally Connected University

Prehistoric Europe Holds Sobering Lessons for Today’s Environmental Scientists

The effects of human society on the environment, including the degradation of ecosystems and habitats, are the subject of considerable, focused research in universities around the world. In recent decades, environmental science, ecology, and biology have become crucial in efforts to understand climate change and to modifying development theories to accommodate sustainable outcomes. But it is only relatively recently that archaeology has started to contribute to our understanding of the environment and sustainable development, creating related fields such as paleoclimatology. 

This was the focus of a talk by UMD Anthropology Assistant Professor Sean Downey, on Oct. 25 as part of UMD’s Bioscience Day celebration. The lecture, entitled "Early Warning Signals of Population Collapse among European Neolithic Societies (8000-4000 BP)," examined the unintended consequences of the Neolithic agricultural revolution and resulting changes in technology. It also considered lessons that might be applied to modern sustainable development initiatives, particularly in agriculture and food production. 

By collecting data from 63 sites around Europe, and extrapolating data from several thousand more sites around the world, Downey and his team of researchers have developed a statistical model around the idea of endemic collapse being a systemic part of demographic changes, with population growth occurring in cyclical boom-and-bust patterns. His research focuses on the centuries in Europe after the introduction of widespread agriculture, following the agricultural revolution in the Fertile Crescent some 10,000 years ago. Contrary to historically accepted models of smooth transitions and steady population growth because of agricultural production, Downey's research indicates that soon after the introduction of agriculture, populations declined sharply, triggering societal collapse before recovering to growth patterns, often generations later, and very possibly within a new societal order. 

Utilizing 23,000 datasets in a statistical model that was run over 10,000 times, Downey and his fellow researchers adapted the mechanism used to describe an ecosystem’s resilience to changing climatic patterns and applied it to human societal growth. In effect, Downey described human society in ecological terms, arguing that human social organizations react in the same way that ecological systems build resistance to collapse, regenerating until conditions become hostile enough that a point of no return is reached, a process he termed “regime change.”

The idea of collapsing societies is not new but it is hotly debated. Biochemist Jared Diamond argued for societal collapse predicated on ecological change in his 2006 book Collapse, and he utilized similar evidence from core drillings, deforestation patterns, pollen and river sediment analysis, and examination of ancient burial sites to argue his point. In this case, Downey argues that the triggers of collapse can be identified earlier, perhaps in time to prevent collapse.

“This is a very controversial. It was a fascinating approach to dealing with some difficult questions,” said David Thulman, a lecturer at George Washington University who attended the talk. “For me the controversy is in the methodology here. I think everybody agrees on how the collapse occurred.”

But Downey was more somber, his final words delivering something of a warning to the audience, one he said he hopes the public will heed as well: "It remains unclear whether modern technological innovation can continue to outpace demand, but it is important for sustainability scientists to consider the possibility that generic mechanisms can contribute to demographic collapse in human societies. Today, I presented the first discovery of early warning signals known to precede large-scale human population collapse in the European Neolithic period. I suggest that further study of human ecodynamics should include applying these methods to other historical datasets at different scales of analysis, in order to learn how to detect declining societal resilience, social and ecological regime shifts, and social processes such as growth and collapse, resource degradation, disease, and warfare before they occur."