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Abstract Biological market theory can be used to explain intraspecific cooperation, interspecific mutualism, and sexual selection through models of game theory. These models describe the interactions between organisms as two classes of traders (buyers/sellers) exchanging commodities in the form of goods (e.g. food, shelter, matings) and services (e.g. warning calls, protection). Here, we expand biological market theory to include auction theory where bidding serves to match buyers and sellers.In a reverse auction, the seller increases the value of the item or decreases the cost until a buyer steps forward. We provide several examples of ecological systems that may have reverse auctions as underlying mechanisms to form mutualistic relationships.We focus on the yellow baboon (Papio cynocephalus) mating system as a case study to propose how the mechanisms of a reverse auction, which have the unintended but emergent consequence of producing a mutually beneficial outcome that improves collective reproductive benefits of the troop in this multi‐female multi‐male polygynandrous social system. For the yellow baboon, we posit that the “seller” is the reproductively cycling female, and the “buyer” is a male looking to mate with a cycling female. To the male, the “item for the sale” is the opportunity to sire an offspring, the price is providing safety and foraging time (via consortship) to the female. The “increasing value of the item for sale” is the chance of conception, which increases with each cycle since a female has resumed cycling post‐partum. The female's sexual swelling is an honest indicator of that cycle's probability of conception, and since resident males can track a female's cycle since resumption, there is transparency. The males presumably know the chance of conception when choosing to bid by offering consortship.Across nature, this reverse auction game likely exists in other inter‐ and intraspecific social relationships. Considering an ecological system as a reverse auction broadens our view of social evolution and adaptations through the lens of human economic structures. 

Abstract Evolvability is the capacity of a population to generate heritable variation that can be acted upon by natural selection. This ability influences the adaptations and fitness of individual organisms. By viewing this capacity as a trait, evolvability is subject to natural selection and thus plays a critical role in eco‐evolutionary dynamics. Understanding this role provides insight into how species respond to changes in their environment and how species coexistence can arise and be maintained. Here, we create a G‐function model of competing species, each with a different evolvability. We analyze population and strategy (= heritable phenotype) dynamics of the two populations under clade initiation (when species are introduced into a population), evolutionary tracking (constant, small changes in the environment), adaptive radiation (availability of multiple ecological niches), and evolutionary rescue (extreme environmental disturbances). We find that when species are far from an eco‐evolutionary equilibrium, faster‐evolving species reach higher population sizes, and when species are close to an equilibrium, slower‐evolving species are more successful. Frequent, minor environmental changes promote the extinction of species with small population sizes, regardless of their evolvability. When several niches are available for a species to occupy, coexistence is possible, though slower‐evolving species perform slightly better than faster‐evolving ones due to the well‐recognized inherent cost of evolvability. Finally, disrupting the environment at intermediate frequencies can result in coexistence with cyclical population dynamics of species with different rates of evolution. 

Abstract Recent evidence suggests that a polyaneuploid cancer cell (PACC) state may play a key role in the adaptation of cancer cells to stressful environments and in promoting therapeutic resistance. The PACC state allows cancer cells to pause cell division and to avoid DNA damage and programmed cell death. Transition to the PACC state may also lead to an increase in the cancer cell’s ability to generate heritable variation (evolvability). One way this can occur is through evolutionary triage. Under this framework, cells gradually gain resistance by scaling hills on a fitness landscape through a process of mutation and selection. Another way this can happen is through self-genetic modification whereby cells in the PACC state find a viable solution to the stressor and then undergo depolyploidization, passing it on to their heritably resistant progeny. Here, we develop a stochastic model to simulate both of these evolutionary frameworks. We examine the impact of treatment dosage and extent of self-genetic modification on eco-evolutionary dynamics of cancer cells with aneuploid and PACC states. We find that under low doses of therapy, evolutionary triage performs better whereas under high doses of therapy, self-genetic modification is favored. This study generates predictions for teasing apart these biological hypotheses, examines the implications of each in the context of cancer, and provides a modeling framework to compare Mendelian and non-traditional forms of inheritance.