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Evolving the Anthropocene: linking multi-level selection with long-term social-ecological change.

Erle C Ellis1, Nicholas R Magliocca2, Chris J Stevens3

  • 11Department of Geography and Environmental Systems, University of Maryland, Baltimore County, Baltimore, MD 21250 USA.

Sustainability Science
|August 28, 2018
PubMed
Summary

Cultural multi-level selection drives human environmental transformation and societal complexity through coevolutionary feedbacks. This research explores how group-level selection shapes human behaviors and ecosystem engineering for long-term sustainability.

Keywords:
Agent-based modeling (ABM)AnthroecologyArchaeologySocial–ecological systems (SES)Sociocultural niche construction (SNC)The extended evolutionary synthesis (EES)

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Area of Science:

  • Evolutionary anthropology
  • Environmental science
  • Computational social science

Background:

  • Human societies have increasingly engineered environments, from early fire use to agriculture.
  • Societal complexity has grown from small bands to global systems.
  • These changes are linked through social and environmental coevolution.

Purpose of the Study:

  • To investigate the role of cultural multi-level selection in human environmental transformation.
  • To understand the reciprocal relationship between societal change and environmental impact.
  • To address sustainability challenges in the Anthropocene.

Main Methods:

  • Combining archaeological evidence with agent-based virtual laboratory (ABVL) modeling.
  • Analyzing long-term coupled social and environmental changes.
  • Testing hypotheses on group-level selection dynamics.

Main Results:

  • Positive feedbacks identified between social complexity and environmental productivity enhancement.
  • Evidence suggests coevolutionary processes driven by selection above the individual level.
  • The agent-based virtual laboratory approach provides a framework for mechanistic testing.

Conclusions:

  • Cultural multi-level selection is a key driver of human-induced environmental transformation.
  • Understanding these coevolutionary dynamics is crucial for addressing Anthropocene sustainability.
  • The study offers a novel approach to integrate empirical data and computational modeling.