Exploring Jacob Stegenga's philosophical challenge to biological population concepts and the implications for ecological research.
What is a biological population? It sounds like a simple question with a straightforward answer—a group of individuals of the same species living in a particular area. This concept serves as a fundamental building block throughout biology, from tracking disease transmission to understanding evolutionary pressures. But beneath this apparent simplicity lies a profound philosophical debate that strikes at the very heart of how biologists define their basic objects of study.
In 2010, philosopher of science Jacob Stegenga ignited a scholarly controversy with his provocative paper "'Population' Is Not a Natural Kind of Kinds." In it, he challenged the influential work of fellow philosopher Roberta Millstein, who had argued for a single, universal definition of populations based on causal interactions between individuals. Stegenga mounted a twin attack: he rejected Millstein's case against conceptual pluralism while simultaneously arguing that her proposed unified definition failed. His radical conclusion? The concept of 'population' doesn't refer to a natural kind at all—instead, populations are constructs of biologists that are variably defined by their specific contexts of inquiry 2 7 .
This debate matters far beyond philosophical circles. How we define populations shapes how we study endangered species, track disease spread, understand evolutionary processes, and conserve ecosystems. Stegenga's position of population pluralism suggests that biologists aren't discovering pre-existing population "truths" but rather creating useful constructs for specific research contexts.
In both ecology and evolutionary biology, populations serve as fundamental units of analysis. Ecologists might study population dynamics of wolves in Yellowstone, while evolutionary biologists examine how trait frequencies change in populations over generations. The conventional understanding assumes populations are natural units that exist in the world, waiting to be discovered and studied by scientists.
This perspective was defended by Millstein, who proposed defining populations based on causal interaction—specifically, mating, competition, predation, and other biological interactions that bind individuals together. She argued against conceptual pluralism, maintaining that a single, unified concept of population was both possible and necessary for biological research 4 .
Stegenga turned this traditional view on its head. He argued that the concept of 'population' does not refer to what philosophers call a "natural kind"—a fundamental category that exists in nature independently of human observers. Instead, he proposed that populations are human constructs that biologists define differently depending on their particular research questions and contexts 2 7 .
This view, which Stegenga calls "population pluralism," holds that there are many legitimate ways to define populations, rather than one single "correct" approach. The boundaries of a population aren't discovered in nature but drawn by scientists for specific purposes.
The importance of how we define populations becomes strikingly clear in what historians of biology call "the great snail debate" of the 1950s, which Stegenga references in his work 1 . This controversy centered on whether observed variations in shell banding patterns of the land snail Cepaea nemoralis resulted from natural selection or random genetic drift.
Different research teams studying similar snail groups reached dramatically different conclusions because they had effectively defined their study populations differently:
Defined populations broadly across environmental gradients, finding correlations between shell patterns and environmental factors that suggested adaptive significance.
Defined populations more locally, emphasizing random variation in small, relatively isolated groups that appeared to support neutral evolution through genetic drift.
The debate wasn't ultimately resolved by determining who had the "correct" population definition. Rather, biologists came to recognize that both processes were operating, and that the relative importance of selection versus drift depended significantly on how population boundaries were drawn—which in turn depended on the specific biological questions being asked.
This historical case demonstrates Stegenga's core argument: how we define populations directly shapes our scientific conclusions. Rather than there being one "true" population structure waiting to be discovered, different ways of bounding populations reveal different biological processes 1 3 .
| Research Approach | Population Definition | Primary Conclusion | What Each Approach Revealed |
|---|---|---|---|
| Selection-Focused | Broad, environmentally-defined groups | Shell patterns resulted from natural selection | Large-scale adaptive patterns across habitats |
| Drift-Focused | Local, isolated groups | Shell patterns resulted from random genetic drift | Effects of small group size and isolation |
The practical methods that biologists use to study populations effectively constitute different ways of defining what counts as a population. Stegenga's pluralism acknowledges that these varied approaches don't merely measure pre-existing populations but actively construct them through methodological choices 3 .
| Research Method | How It Defines Populations | Best Suited For | Key Limitations |
|---|---|---|---|
| Quadrat Sampling | Spatially-bounded areas (e.g., 1m² for plants) | Immobile organisms (plants, fungi) | May miss rare species or irregular distributions |
| Distance Sampling | Detection probabilities from lines/points | Mobile animals, rare trees | Assumptions about detection patterns |
| Mark-Recapture | Groups with mixing between sampling periods | Mobile animals (mammals, birds, fish) | Requires sufficient mixing between samples |
Field biologists employ diverse methods that implicitly define populations differently, each with particular strengths and limitations:
Involve marking off square areas within a habitat and counting individuals within those boundaries. The size and number of quadrats depend on the organism—for instance, a 1 m² quadrat might be used for daffodils, while a 100 m² quadrat might be employed for widely-spaced trees like giant redwoods 5 .
Estimate population density based on detection distances. Researchers travel along line transects, recording distances and angles to observed organisms, then use mathematical models to estimate densities based on detection probability patterns 5 .
Involve capturing, marking, and releasing animals, then later recapturing individuals to estimate total population size based on the ratio of marked to unmarked individuals. This approach defines populations operationally through mixing and capture probabilities 5 .
Stegenga's central argument is that 'population' is not a natural kind—a fundamental category that exists independently of human observers, like chemical elements. Instead, he proposes that populations are constructs that biologists create through their research methods and questions 2 .
This "population pluralism" holds that there are numerous legitimate ways to define populations, rather than one single correct approach. The fine-grained causal relations that could constitute membership in a biological population are huge in number, and many are manifested by degree. Thus, we can view population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary 3 .
Stegenga suggests that the most intuitive criterion for population membership—causal connectivity, or individuals interacting and influencing each other's life trajectories—is best understood using what he calls "thick causal concepts." These acknowledge that causal relations in biology are complex, context-dependent, and degree-based rather than simple yes-or-no relationships 3 .
This perspective allows for more nuanced understanding of population boundaries, recognizing that connectivity between organisms exists on a continuum rather than as a binary distinction.
Based on geographic boundaries
Based on gene flow and relatedness
Based on social interactions
Based on resource use and competition
Stegenga's population pluralism has significant implications for how biological research is conducted and interpreted:
This debate represents a microcosm of larger questions in philosophy of science concerning whether scientific categories reflect pre-existing natural divisions or represent useful human impositions on a continuous and complicated natural world.
Stegenga's position aligns with what philosophers call anti-realism about biological populations—the view that populations don't exist independently of scientific practice. This doesn't make populations "unreal" but acknowledges that how we divide the biological world into populations depends on our interests, methods, and questions 2 3 .
"The population concept is not a reflection of how nature is carved at its joints, but a versatile tool that biologists can adapt to better understand the complex, interconnected web of life."
Jacob Stegenga's challenge to conventional thinking about populations represents more than just an academic debate—it forces us to reconsider how we categorize and study the living world. By arguing that 'population' is not a natural kind, Stegenga doesn't diminish the concept's usefulness but rather liberates biologists to employ multiple, context-sensitive definitions.
The next time you read about "wolf populations" in Yellowstone, "bacterial populations" in your gut, or "population genetics" of rare species, remember that these categories are not simple discoveries of pre-existing natural divisions. They are useful constructs that help scientists answer specific questions based on their research methods and theoretical frameworks.
This pluralistic perspective ultimately makes biology more flexible and potentially more powerful, allowing researchers to draw population boundaries in ways that serve their specific inquiries rather than searching for a single "true" definition that works for all contexts. In Stegenga's view, the population concept is not a reflection of how nature is carved at its joints, but a versatile tool that biologists can adapt to better understand the complex, interconnected web of life.
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