Assortative mating without assortative preference

Xie, Yu; Cheng, Siwei; Zhou, Xiang

doi:10.1073/pnas.1504811112

Cited by 43 publications

(48 citation statements)

References 23 publications

(20 reference statements)

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“…I demonstrate the software by replicating a recent study that utilized a continuous encounter mating (EM) model to show how patterns of positive assortative mating may arise from non-assortative individual preferences (Xie et al, 2015).…”

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 91%

“…Simulation is a key tool for exploring mate choice evolution scenarios (CarvajalRodriguez and Rolán-Alvarez, 2014;Fernández-Meirama et al, 2017;Rolan-Alvarez et al, 2015;Xie et al, 2015). In the present work, I propose a mating simulation software that allows the generation of mating tables under different kinds of traits, encounters and preferences.…”

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 99%

“…Logistic preference models (Xie et al, 2015) may be obtained from (2) by considering the probability for any female F to mate with male j (i.e. the probability of male j to be accepted)…”

Section: Logistic Modelsmentioning

confidence: 99%

“…http://dx.doi.org/10.1101/239178 doi: bioRxiv preprint first posted online Dec. 24, 2017; 14 marriages are performed, especially if neither polygamy nor divorce is allowed (Xie et al, 2015). Therefore, as time progressed the individuals become less choosy proportional to the number of marriages already performed (see details of the implementation in the appendix A).…”

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 99%

“…In the former, the population pattern would resemble the individual preferences more precisely while in the latter, the encounter process will introduce some noise that disconnect the expected individual mating preferences from the obtained mating pattern (Gimelfarb, 1988a, b). Moreover, the difference between the mating pattern observed in a population and the mating preferences of the individuals, have been evidenced by modeling scenarios that produce positive assortative mating without assortative individual preferences (Burley, 1983;Xie et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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MateSim: Monte Carlo simulation for the generation of mating tables

Carvajal-Rodríguez

2017

Preprint

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In species with sexual reproduction, the mating pattern is a meaningful element for understanding evolutionary and speciation processes. Given a mating pool where individuals can encounter each other randomly, the individual mating preferences would define the matings frequencies in the population.However, in every mating process, we can distinguish two different steps. First, the process of pair formation which implies that an encounter between partners must occur.Second, the actual mating once the encounter has occurred.Yet, we cannot always assume that the observed population patterns accurately reflect the individual's preferences. In some scenarios the individuals may have difficulties to achieve their mating preferences, such as in monogamous species with low population size, where the mating process is similar to a sampling without replacement. In the latter, the encounter process will introduce some noise that may disconnect the expected individual preferences from the obtained mating pattern.Actually, the difference between the mating pattern observed in a population and the mating preferences of the individuals have been shown by different modeling scenarios.Here I present a program that simulates the mating process for both discrete and continuous traits, under different encounter models and individual preferences, including effects as drift, time dependence and aging. The utility of the software is demonstrated by replicating and extending, a recent study that showed how patterns of positive assortative mating, or marriage in human societies, may arise from nonassortative individual preferences. The previous result is confirmed and it is caused by the marriage among the "ugliest" and oldest individuals, who after many attempts were . CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/239178 doi: bioRxiv preprint first posted online Dec. 24, 2017; 3 finally able to mate among themselves. In fact, by introducing an aging process, I show how the assortative pattern vanishes provided that there is not assortative individual preference.The software MateSim is available jointly with the user's manual, at

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Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 91%

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 99%

“…Logistic preference models (Xie et al, 2015) may be obtained from (2) by considering the probability for any female F to mate with male j (i.e. the probability of male j to be accepted)…”

Section: Logistic Modelsmentioning

confidence: 99%

Section: Cc-by-nc-nd 40 International License Not Peer-reviewed) Is mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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MateSim: Monte Carlo simulation for the generation of mating tables

Carvajal-Rodríguez

2017

Preprint

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Sound Localization and Separation in 3D Space Using a Single Microphone with a Metamaterial Enclosure

et al. 2019

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Conventional approaches to sound localization and separation are based on microphone arrays in artificial systems. Inspired by the selective perception of the human auditory system, a multisource listening system which can separate simultaneous overlapping sounds and localize the sound sources in 3D space, using only a single microphone with a metamaterial enclosure is designed. The enclosure modifies the frequency response of the microphone in a direction‐dependent manner by giving each direction a characteristic signature. Thus, the information about the location and the audio content of sound sources can be experimentally reconstructed from the modulated mixed signals using a compressive sensing algorithm. Due to the low computational complexity of the proposed reconstruction algorithm, the designed system can also be applied in source identification and tracking. The effectiveness of the system in multiple real‐life scenarios is evaluated through multiple random listening tests. The proposed metamaterial‐based single‐sensor listening system opens a new way of sound localization and separation, which can be applied to intelligent scene monitoring and robot audition.

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Conceptual Issues

Uchikoshi,

Raymo

2021

SpringerBriefs in Population Studies

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Assortative mating without assortative preference

Cited by 43 publications

References 23 publications

MateSim: Monte Carlo simulation for the generation of mating tables

MateSim: Monte Carlo simulation for the generation of mating tables

Sound Localization and Separation in 3D Space Using a Single Microphone with a Metamaterial Enclosure

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