Extending r/K selection with a maternal risk-management model that classifies animal species into divergent natural selection categories
Reproduction is a defining process of biological systems. Every generation, across all species, breeding females repopulate ecosystems with offspring. r/K selection was the first theory to classify animal species by linking the rates with which breeding females repopulated ecosystems, to the stability of ecosystems. Here, I introduce a species classification scheme that extends the reach of r-K selection and CSR selection by linking breeder investments in offspring quantity, quality, and diversity to specific natural selection pressures. The species classification scheme is predicated on the assumption that high rates of predation favor breeders that invest more in offspring quantity than quality; and that spatiotemporal scarcity favors breeders that investment more in offspring quality than quantity. I present equations that convert the species classification scheme into a maternal risk-management model. Thereafter, using the equations, I classify eighty-seven animal species into the model’s natural selection categories. Species of reptiles, fish, and marine invertebrates clustered in the predation selection category. Species of birds and mammals clustered in the scarcity selection category. Several species of apex predators clustered in the weak selection category. Several species of social insects and social mammals clustered in the convergent selectioncategory. In summary, by acknowledging breeding females as the individuals upon which natural selection acts to repopulate ecosystems with offspring, the proposed maternal risk-management model offers a testable, theoretical framework for the field of ecology.
Nature Publishing Group
Cassill, D. L. (2019). Extending r/K selection with a maternal risk-management model that classifies animal species into divergent natural selection categories. Scientific Reports, 9(1), 6111. https://doi.org/10.1038/s41598-019-42562-7
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