kin selection
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| kin selection | |
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| Name | kin selection |
| Field | Evolutionary biology, behavioral ecology, sociobiology |
| Introduced | 1964 |
| Notable people | W. D. Hamilton, R. A. Fisher, J. B. S. Haldane, E. O. Wilson, George C. Williams |
kin selection
Kin selection is an evolutionary theory explaining how alleles promoting behaviors that help relatives can spread through populations because relatives share genes. It complements concepts like natural selection and inclusive fitness by focusing on genetic relatedness among individuals in social species. Kin selection has informed research across genetics, ethology, and conservation biology and has prompted debates involving group selection, multilevel selection, and sociobiology.
Introduction
Kin selection addresses how altruistic, cooperative, and spiteful behaviors can evolve when actions affecting individual fitness also affect the reproductive success of genetically related individuals. Central figures who developed and extended the concept include W. D. Hamilton, J. B. S. Haldane, R. A. Fisher, George C. Williams, E. O. Wilson, and John Maynard Smith. The framework interacts with empirical studies from field sites like Congo Basin, Galápagos Islands, and Kruger National Park and has been applied to taxa including Apis mellifera, Homo sapiens, Pan troglodytes, Vulpes vulpes, and Peromyscus maniculatus.
Theory and Mathematical Formulation
The formalization of kin selection relies on inclusive fitness and mathematical tools developed by figures such as W. D. Hamilton and formalizers like John Maynard Smith and George R. Price. Hamilton's rule—often written rB > C—relates relatedness (r), benefit to the recipient (B), and cost to the actor (C). Theoretical extensions employ population genetics approaches used by R. A. Fisher and J. B. S. Haldane and incorporate concepts from Lewontin's quantitative genetics, models by Motoo Kimura, stochastic treatments from Sewall Wright, and evolutionary game theory popularized by Maynard Smith and G. G. Simpson. Mathematicians and biologists like George Price, John Maynard Smith, Martin A. Nowak, Carl T. Bergstrom, Simon Conway Morris, Robert Trivers, and Edmund B. Wilson contributed formulae and critiques. Modern treatments link inclusive fitness to multilevel selection frameworks developed by David Sloan Wilson, E. O. Wilson, and formal population models by Alasdair I. Houston and Moshe G. Shapiro.
Empirical Evidence and Examples
Empirical support spans eusocial insects—investigated in taxa such as Apis mellifera, Bombus terrestris, Solenopsis invicta, and Atta cephalotes—and vertebrates including Homo sapiens, Pan troglodytes, Canis lupus, and Vulpes vulpes. Classic field work by researchers at institutions such as Oxford University, Harvard University, University of Cambridge, and Smithsonian Institution produced key datasets. Studies by E. O. Wilson, Karl von Frisch, Konrad Lorenz, and Niko Tinbergen linked behavior to kin structure; investigations by Sarah Blaffer Hrdy, Robert Trivers, and Richard Dawkins explored human kin-directed altruism. Laboratory experiments using model organisms like Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Saccharomyces cerevisiae have quantified fitness effects, while long-term studies at sites such as Gombe Stream National Park and La Selva Biological Station tracked kin influences on social networks.
Criticisms and Alternative Theories
Critiques have come from proponents of group selection and multilevel selection, including E. O. Wilson (later work), David Sloan Wilson, and Elliott Sober. Debates involve works by Martin A. Nowak, Corina Tarnita, and responses by Steven A. Frank and Richard Dawkins. Critics argue that inclusive fitness calculations may fail under strong frequency dependence or structured demography; formal alternatives include multilevel selection theory articulated by David Sloan Wilson and mathematical treatments by Maynard Smith and George R. Price. Philosophers and historians such as Ernst Mayr, Stephen Jay Gould, and Daniel Dennett have weighed in on conceptual clarity and historical context. Methodological critiques reference statistical approaches developed by Ronald Fisher and population models by Motoo Kimura and Sewall Wright.
Applications and Implications
Applications extend to conservation policy at agencies like IUCN and WWF, breeding programs at institutions like Kew Gardens and San Diego Zoo, and epidemiology research at Centers for Disease Control and Prevention and World Health Organization where kin-based contact patterns affect disease spread. Agricultural implementations influence practices at Corteva Agriscience and International Rice Research Institute. Theoretical implications inform artificial life and robotics from labs at MIT and Stanford University and ethical discussions in philosophy referenced by Peter Singer and Martha Nussbaum. Kin selection principles have also influenced economics models from Nobel Prize in Economic Sciences laureates working on evolutionary game theory and social preferences.
Historical Development and Key Contributors
Origins trace through population geneticists and early theorists like R. A. Fisher, J. B. S. Haldane, and Sewall Wright. The pivotal synthesis was advanced by W. D. Hamilton in the 1960s, with mathematical formalization by George R. Price and further development by John Maynard Smith, George C. Williams, and E. O. Wilson. Subsequent contributors include Robert Trivers, Martin A. Nowak, David Sloan Wilson, Steven A. Frank, Michael J. Wade, Elliott Sober, Simon A. Levin, and experimentalists such as Konrad Lorenz, Karl von Frisch, Niko Tinbergen, Sarah Blaffer Hrdy, and Richard Dawkins. Institutions central to the discourse include Royal Society, National Academy of Sciences, Smithsonian Institution, Harvard University, University of Cambridge, and Oxford University.