Despite an explosion of Darwinian evolution-based models for explaining patterns of cultural phenomena, evolutionary thinking has made only limited contributions to applied studies of human communities such as those focused on promoting sustainable practices and public policy. A number of hurdles contribute to the relatively nascent status of evolutionary models applied to community action and planning. First, the rejection of nineteenth-century notions of Social Darwinism continues to taint the idea that evolutionary models might be productively used to explain the differential persistence of human behavior and social structures. Second, community planning has traditionally been founded upon common sense notions of causation. Many planning efforts assume that individuals follow a rational decision process and that change comes from the production of compelling information. In this sense, our common sense is consistent with Lamarckian mechanisms of change, and we hold that Darwinian processes are limited to the “natural world.” This isolation of humans from nature combined with a commitment to rationality obscures the potential that evolutionary models have for constructing explanations and shaping social outcomes. Third, and importantly, we have relatively few examples that can serve as exemplars for how evolutionary thinking can be employed in public planning, policy, and action.
Despite these challenges, Waring and Tremblay are among a growing group of scholars (e.g., Wilson 2011, Wilson et al. 2014) who argue that evolutionary thinking may hold the key to our ability to not only explain the past but also shape our future. The need for effective tools that can conceptualize and systematically effect social change could not be more immediate, especially in the domain of sustainability. Among the many long-term societal issues that plague our contemporary world, few are as pressing as the need for establishing sustainable practices in the production and consumption of vital resources such as energy and food. Over the past 150 years, we have witnessed the profound impact of economic growth that has been entirely based on the mining of the natural environment. Over the past 30 years, concern over sustainability has grown tremendously; interest in sustainable practices parallels but also out-paces societal interest in climate change and global warming (Figure 1). As a society, we worry about our future, and most people generally acknowledge that contemporary practices favoring short-term gains over long-term stability cannot persist over the long run. Consequently, a clear challenge exists for establishing a means by which we can shape the behavior of individuals, communities, companies, and governments so that they make choices considering the future health of the environment and the long-term well-being of all stakeholders rather than maximizing immediate pay-offs.
Yet, for the most part, efforts at promoting sustainable practices have not yielded substantial change in the way individuals behave or how communities are structured. Changing behavior at the scale of communities or organizations that have traditionally relied on non-sustainable practices is obviously a grand challenge. Those seeking to promote change must overcome the fact that in many contemporary economic and social contexts, it pays for individuals to act in their own selfish, short-term interests. Thus, many traditional strategies for changing populations, such as advertising, are ineffective. Although advertisers devise effective strategies leading to increases in individual-scale consumption of products in a population, marketing messages that promote anti-consumption have led to only marginal changes in daily practices. Mass marketing of sustainability has led many to accuse current attempts at promoting sustainable systems as simple “greenwashing” activities that have little to do with altering the behaviors of individuals at the scale of a community or organization (e.g., Laufer 2003). Significantly, we have yet to seriously address the factors that shape patterns of individual behavior, and we have failed to consider how social structures might be employed to encourage behavior favoring sustainable practices over non-sustainable ones, particularly over the long run. Instead, we rely on the assumption that arguments based on logic, data, or moral stances will spur populations to do the “right thing.” At the same time, we hope that technological changes such as improvements in the efficiency of alternative energy sources will make the problem of non-sustainability simply go away. Wishful thinking, indeed.
<iframe name=”ngram_chart” src=”https://books.google.com/ngrams/interactive_chart?content=sustainability%2Cclimate+change%2Cglobal+warming&case_insensitive=on&year_start=1960&year_end=2000&corpus=15&smoothing=3&share=&direct_url=t4%3B%2Csustainability%3B%2Cc0%3B%2Cs0%3B%3Bsustainability%3B%2Cc0%3B%3BSustainability%3B%2Cc0%3B%3BSUSTAINABILITY%3B%2Cc0%3B.t4%3B%2Cclimate%20change%3B%2Cc0%3B%2Cs0%3B%3Bclimate%20change%3B%2Cc0%3B%3BClimate%20Change%3B%2Cc0%3B%3BClimate%20change%3B%2Cc0%3B%3BCLIMATE%20CHANGE%3B%2Cc0%3B.t4%3B%2Cglobal%20warming%3B%2Cc0%3B%2Cs0%3B%3Bglobal%20warming%3B%2Cc0%3B%3BGlobal%20Warming%3B%2Cc0%3B%3BGlobal%20warming%3B%2Cc0%3B%3BGLOBAL%20WARMING%3B%2Cc0″ width=900 height=500 marginwidth=0 marginheight=0 hspace=0 vspace=0 frameborder=0 scrolling=no></iframe>
Figure 1: Comparative popularity in the terms “Sustainability, “Climate Change” and “Global Warming” in books published from 1960 to the 2015 from the Google Books N-Gram database (Michel et al. 2010).
It is in this context that Waring and Tremblay’s article An Evolutionary Approach to Sustainability Science brings timely attention to the idea that evolutionary thinking is directly applicable for studying contemporary communities and can make major contributions to an understanding of the conditions needed to form and sustain communities over the long run. Waring and Tremblay lay out a simple argument about the applicability of evolutionary principles for explaining cultural phenomena and then suggest that sustainability is fundamentally an evolutionary issue. In their model, sustainability is linked intrinsically to group-beneficial behaviors of individuals because these favor the persistence of cooperating communities. Central to their evolutionary model is the notion of scale; they recognize that sustainability comes from the aggregate and integrative patterns at the scale of groups that, in turn, contribute to the success of individuals at a lower scale. Individuals trade off gains that could be made for themselves for the benefits that come with group membership. Thus, they argue that the keys to sustainability are mechanisms that favor (or deter) cooperation among individuals within nested groups at greater scales. Sustainable communities, presumably, are those in which individuals behave to conserve resources, an altruistic action that requires one to trust that no one else will selfishly use the resources. Thus, group cooperation is central to sustainability and works when everyone benefits indirectly from their participation in aggregates at greater scales.
Waring and Tremblay’s approach makes explicit use of multi-level selection, though they phrase this discussion as “group selection.” Individuals cooperate in such a way to benefit group members, and membership in the group confers benefits to all individuals. In a number of ways, their use of “group” language weakens their argument, and they might be better off using the more abstract “multi-level selection.” Here is why: any particular group of individuals may or may not be an inherently meaningful unit of analysis. From an intuitive perspective, we certainly perceive that we live in “groups” and act as if groups are clear, measureable phenomena. As examples of group-scale phenomena, Waring and Tremblay mention units such as “society,” “organization,” “governments,” “parties,” “chiefdoms,” and “corporations.” As anthropologists have long noted, however, the boundaries of any group depend on the question asked rather and are not intrinsic properties. Thus, we cannot simply treat groups as a given in the analysis. They must be groups for the purposes of the analysis.
In part, I think confusion over “empirically-assumed groups” versus “analytically-produced groups” has led to some of the criticism of group selection as a mechanism of change (e.g., West et al. 2007). Waring and Tremblay take an approach that furthers some of this confusion by arguing that group-selection is simply differential success of groups because “when groups compete, cooperative and coordinated groups win.” This statement treats group selection as a simple analogy to the natural selection of biological entities. But although we can easily conceive of differential persistence of skin-bounded, organism-scale entities via birth and deaths, it is difficult to envision groups having such clear beginnings and endings. As aggregates, human groups shift, merge, reform, grow, and contract in a continuous fashion subject to ever-changing aggregate membership that is not at all analogous to the binary forms that living/dead organisms take.
The amorphous nature of groups does not imply that natural selection is inappropriate for explaining changes at scales beyond the organism. Cultural units are not empirically-bounded physical units at the levels of inheritance traits, individuals and aggregate phenomena. In the case of cultural variability, the units we use for describing and measuring change matter. In evolutionary analyses, groups must be defined in terms of aggregates that meaningfully interact and replicate at lower scales. Groups, then, are empirical entities identified though units representing a shift in classification level. Here, it is useful to distinguish scale from level. Scale represents the set of things that share physical inclusiveness. Level, on the other hand, is a conceptual property that consists of the set of units at the same definitional inclusiveness (Dunnell 1971). Level is a property of analysis. Although a group will always be an aggregate of things, a group of things may not meet the definition of the unit at any particular level of analysis.
This distinction suggests that the use of “multilevel selection” is preferable over “group selection” because it reinforces the idea that levels must be defined in the context of analysis, not assumed. The issue is more than just semantics. Perhaps the greatest challenge to those committed to an evolutionary approach to cultural phenomena and human behavior is to establish the units of measurement. As Lewontin (1974:9) pointed out: “we cannot go out and describe the world in any old way we please and then sit back and demand that an explanatory and predictive theory be built on that description.” In the case of cultural phenomena, we cannot simply assume the units of biology are the same for cultural and social entities at the individual and aggregate scale. Significantly, the problem gets more complicated the more inclusive the unit of analysis.
Waring and Tremblay (also Waring et al. 2015), illustrate their overall argument using fairly commonsense-framed examples of groups: Fijian fish harvesters, the Bhutanese government, United States municipalities and agencies. In general, these examples illustrate the potential that multi-level selection models might play in explaining why group-beneficial properties can persist despite conditions that tend to oppose these actions. What is not clear, at this point, is whether any of the groups identified in the examples are sufficient and necessary to the analysis. The next step must be to analytically determine the levels at which natural selection can be said to act based on the measurable heritable variation with performance differences—the essentials for any evolutionary unit to have meaning.
In their short article, of course, the examples are simply pointers to more comprehensive analyses that remain to be accomplished. Lacking a clear linkage between theory and the measurement units, however, their examples make the approach appear to be more of a heuristic than an evolutionary analysis. This is unfortunate: cultural evolution is more than a simple analogy to biological evolution, and although both share a theoretical framework, the tools and units involved in each have to be formulated independently. Lacking these components, it is difficult to say whether the multi-level approach, despite its satisfying embeddedness in evolutionary theory, is inherently better than alternative or traditional models, such as multi-scale systems or political economy theory. For some, the relatively limited depth to the analysis will make it difficult to imagine we are doing more than preaching to the converted. If the approach is going to go beyond the notion that politics operate at different scales, we must begin to build units and models for exploring and measuring the empirical expectations of changes in the structure of interaction at different scales.
Waring and Tremblay emphasize that group-beneficial behavior is generally linked to sustainability, though this need not be the case. For natural selection to operate, there must be a performance consequence to overconsumption of resources for entities at any scale. Traditionally, land-based entities, such as communities, states, and nations, have been tied to the resources in the space they inhabit. Thus, environmental impacts affect their performance relative to other competing entities. Multi-national corporate-scale entities, however, are notoriously ignorant of sustainable practices specifically because their overall success relative to competitors is not tied to any particular environment. As we have seen in recent history, the ability to abandon any source of resources (labor, minerals, fish, oil) for another location anywhere in the world results in the selection for entities that can most efficiently extract resources, regardless of long-term consequences. Sustainability for entities of this scale is tied to group-beneficial traits that make extraction more efficient and/or thorough: obviously not the kind of “sustainability” meant by most. A big challenge facing the contemporary world is establishing an environment that selects for corporate entities that exhibit socially and environmentally-beneficial behavior at the scale of the planet. Solving this problem will go a long way towards achieving a sustainable future.
Another point that warrants some consideration is the relationship between contemporary populations and their degree of “adaptedness” to their current environment. Waring and Tremblay propose that humans are “well-adapted” to their environments due to the effects of natural selection and the cumulative nature of cultural inheritance. Natural selection, of course, simply favors variants that are sufficiently better (i.e., “good enough”) in performance relative to the alternatives present at any point in time (Jacob 1977). The challenge for evolutionary researchers is to learn the detailed history of the local environment and to identify the competing variants that led to any particular outcome. We should not assume that any particular outcome provides an ideal model about best practices that can be successfully emulated elsewhere. In the case of shaping populations to favor group-scale attributes, we must seek to identify the conditions in any particular environment in which group-beneficial interaction confers sufficient advantages to individuals relative to those not participating. Given the nature of technological and environmental change, these advantages must constantly be adjusted to compensate for continually-innovating variants.
These comments are not intended to unduly criticize the work represented here: although there are certainly challenges in the way we measure and analyze cultural phenomena, the potential of an evolutionary approach to tackling the issue of sustainability is undeniably exciting. Waring and Tremblay have identified an area of investigation that presents not only a good case for multi-level selection applied to culture but also highlights some of the efforts needed to build a fully-formulated sustainability science. Despite the challenges, I have no doubt that the evolution-based studies represented here will result in significant contributions that may be vital to our future.
Dunnell, R.C. (1971). Systematics in Prehistory. Free Press, New York.
Jacob, F., Evolution and Tinkering. Science 196 (1977): 1161–1166.
Laufer, W. S. (2003). Social Accountability and Corporate Greenwashing. Journal of Business Ethics, 43(3), 253–261. http://doi.org/10.1023/A:1022962719299
Lewontin, R, C. (1974) The Genetic Basis of Evolutionary Change. Columbia University Press, New York.
Michel, J.-B., Shen, Y.K., Aiden, A.P., Veres, A., Gray, M.K., Brockman, M.K., The Google Books Team, Pickett, J.P., Hoiberg, D., Clancy, D., Norvig, P., Orwant, J., Pinker, S., Nowak, M.N., Aiden, E.A. Quantitative Analysis of Culture Using Millions of Digitized Books. Science. 331 (6014), 176-182. doi: 10.1126/science.1199644
Waring, T.M., Kline, M.A., Brooks, J.S., Goff, S.H., Gowdy, J., Janssen, M.A., Smaldino, P.E., Jacquet, J., (2015) A multilevel evolutionary framework for sustainability analysis. Ecol. Soc. 20. doi:10.5751/ES-07634-200234
West, S.A., Griffin, A.S., Gardner, A., (2008). Social semantics: how useful has group selection been? Journal of Evolutionary Biology 21:374-385.
Wilson, D.S. (2011) The Neighborhood Project: Using Evolution to Improve My City, One Block at a Time. Little, Brown and Company. New York.
Wilson, D. S., Hayes, S. C., Biglan, A., & Embry, D. (2014). Evolving the Future: Toward a Science of Intentional Change. Behavioral and Brain Sciences, 37, 395–460.
Why We Experiment
July 7, 2022