Humans possess great capacity for behavioral and cultural change, but our ability to manage change is still limited. This article has two major objectives: first, to sketch a basic science of intentional change centered on evolution; second, to provide examples of intentional behavioral and cultural change from the applied behavioral sciences, which are largely unknown to the basic sciences community. All species have evolved mechanisms of phenotypic plasticity that enable them to respond adaptively to their environments. Some mechanisms of phenotypic plasticity count as evolutionary processes in their own right. The human capacity for symbolic thought provides an inheritance system having the same kind of combinatorial diversity as does genetic recombination and antibody formation. Taking these propositions seriously allows an integration of major traditions within the basic behavioral sciences, such as behaviorism, social constructivism, social psychology, cognitive psychology, and evolutionary psychology, which are often isolated and even conceptualized as opposed to one another. The applied behavioral sciences include well-validated examples of successfully managing behavioral and cultural change at scales ranging from individuals to small groups to large populations. However, these examples are largely unknown beyond their disciplinary boundaries, for lack of a unifying theoretical framework. Viewed from an evolutionary perspective, they are examples of managing evolved mechanisms of phenotypic plasticity, including open-ended processes of variation and selection. Once the many branches of the basic and applied behavioral sciences become conceptually unified, we are closer to a science of intentional change than one might think.

https://www.ode.state.or.us/wma/teachlearn/conferencematerials/sped/2014/evolvingthefuture.pdf

Evolving the future: Toward a science of intentional change

We report a study of central Maya lowland dynastic information networks, i.e., six cities’ external elite ceramic influences, and how they reflect the decision-making practices of Maya elites over 3000 years. Forest cover, i.e., Moraceae family pollen, was added to the network analysis to provide ecological boundary conditions, thus ecologically moderated information networks. Principal components analysis revealed three dominant patterns. First, the networking of interior cities into powerful polities in the Late Preclassic and Classic periods (400 BCE-800 CE). In a second pattern, coastal cities emerged as key entrepôts based on marine navigation (Terminal and Postclassic periods, 800-1500 CE). Climate dynamics and sustainability considerations facilitated the transition. Forest cover, a measure of ecosystem health, shows interior forests diminished as interior cities networked but rebounded as their networks declined. By contrast, coastal forests flourished with networks implying that the marine-based economy was sustainable. Third, in the Classic, the network-dominant coast, west or east, changed with interior polities’ political struggles, the critical transition occurring after 695 CE as Tikal gained dominance over the Calakmul-Caracol alliance. Beginning with the Late Preclassic about 2000 years ago, it is possible to assign names to the decision makers by referencing the growing literature on written Maya records. Although the detectable decision sequence evident in this analysis is very basic, we believe it does open possible avenues to much deeper understanding as the study proceeds into the future. The Integrated History and Future of People on Earth–Maya working group that sponsored the analysis anticipates that it will provide actionable social science intelligence for future decision making at the global scale.

/pdf/a-distribution-analysis-of-the-central-maya-lowlands-jad4vhvs7i.pdf

A distribution analysis of the central Maya lowlands ecoinformation network: its rises, falls, and changes

To what degree is cultural multi-level selection responsible for the rise of environmentally transformative human behaviors? And vice versa? From the clearing of vegetation using fire to the emergence of agriculture and beyond, human societies have increasingly sustained themselves through practices that enhance environmental productivity through ecosystem engineering. At the same time, human societies have increased in scale and complexity from mobile bands of hunter-gatherers to telecoupled world systems. We propose that these long-term changes are coupled through positive feedbacks among social and environmental changes, coevolved primarily through selection acting at the group level and above, and that this can be tested by combining archeological evidence with mechanistic experiments using an agent-based virtual laboratory (ABVL) approach. A more robust understanding of whether and how cultural multi-level selection couples human social change with environmental transformation may help in addressing the long-term sustainability challenges of the Anthropocene.

/pdf/evolving-the-anthropocene-linking-multi-level-selection-with-4a8l5p2onc.pdf

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

Private foundations and other organizations concerned with improving society these days frequently ask grantees to articulate their “theory of change.” By this they usually mean their strategy for accomplishing the stated goals of the project, rather than a real, general theory of how social change happens (Anderson 2005). For example, the Center for Theory of Change defines it this way: “A Theory of Change provides a roadmap to get you from here to there.” (http://www.theoryofchange.org/ what-is-theory-of-change/#4). While it is certainly good to have a well thought out strategy for accomplishing complex social goals, a true theory of social change is a very different thing. Such a theory is what Elinor Ostrom was reaching for in her target article (Ostrom 2013). Such a theory must, Lin believed, be grounded in an expanded evolutionary paradigm that is capable of explaining not only how organisms evolve and change, but also how rules, norms, institutions, and cultures evolve and change. This commentary builds on some of the ideas in Lin’s article to develop a broader theory of how complex systems from organisms to ecosystems, communities, states, nations, and the planet as a whole evolve and change, and how we can use this theory to design strategies to get from here to a desired there. In biology, evolution is the theory of change. It applies across the board. But in the recent past, evolutionary theory has gone down what David Sloan Wilson has identified as some wrong paths. The emphasis on selection at the genetic level, to the exclusion of selection at other levels of organization, has hindered the development of the field and slowed integration with the social sciences. When one considers the evidence more comprehensively, it is clear that selection occurs at multiple levels, and between group selection may in some circumstances be more important than within

A theory of socio-ecological system change

The MayaSim model is an integrated agent-based, cellular automata, and network model representing the ancient Maya social-ecological system. The model represents the relationship between population growth, agricultural production, soil degradation, climate variability, primary productivity, hydrology, ecosystem services, forest succession, and the stability of trade networks. Agents representing settlements develop and expand within a spatial landscape that changes under climate variation and responds to anthropogenic impacts. The model is able to reproduce spatial patterns and timelines somewhat analogous to that of the ancient Maya, although this proof-of-concept model requires refinement and further archaeological data for calibration. This paper aims to identify candidate features of a resilient versus vulnerable social-ecological system, and employs computer simulation to explore this topic, using the ancient Maya as an example. Complex systems modelling identifies how interconnected variables behave, considering fast-moving variables such as land cover change and trade connections, meso-speed variables such as demographics and climate variability, as well as slow-moving variables such as soil degradation.

MayaSim: An agent-based model of the ancient Maya social-ecological system (Version 3)

Growing the Ancient Maya Social-Ecological System from the Bottom

The Rupture of Classic Maya Divine Kingship from the Perspective of Postclassic Archaeology, Iconography, and Ethnohistory

Interpreting Ancient Maya Society Through Residential Groups: Investigating Early Long-Distance Interaction in Caracol's Epicenter: Caracol Archaeological Project Investigations for 2017

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Growing the Ancient Maya Social-Ecological System from the Bottom

The Rupture of Classic Maya Divine Kingship from the Perspective of Postclassic Archaeology, Iconography, and Ethnohistory

Interpreting Ancient Maya Society Through Residential Groups: Investigating Early Long-Distance Interaction in Caracol's Epicenter: Caracol Archaeological Project Investigations for 2017