GREENFIELD Michael D's profile
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GREENFIELD Michael D

  • Equipe Neuro-Ethologie Sensorielle, ENES/Neuro-PSI, CNRS UMR 9197, , Université de Lyon/Saint-Etienne,, 42023 Saint Etienne, France
  • Behavior & Social Evolution, Evolutionary Ecology, Phenotypic Plasticity, Phylogeography & Biogeography, Quantitative Genetics, Sexual Selection
  • recommender

Recommendations:  3

Reviews:  3

Areas of expertise
B.A. New York University (1973 ; biology, engineering) Ph.D. University of Wisconsin, Madison (1978 ; entomology) assistant - associate professor ; University of California, Los Angeles (1981-1993) professor ; University of Kansas (1991 - 2007) adjunct professor ; University of Kansas (2007 - present) professeur / chercheur ; CNRS (IRBI, UMR 7261) , Tours, France (2006 - 2018) Chercheur Associé / Professeur Invité (2019 - present) Equipe Neuro-Ethologie Sensorielle, ENES/Neuro-PSI, CNRS UMR 9197, Université de Lyon/Saint-Etienne, 42023 Saint Etienne, France

Recommendations:  3

29 Nov 2023
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Does sociality affect evolutionary speed?

On the evolutionary implications of being a social animal

Recommended by based on reviews by Rafael Lucas Rodriguez and 1 anonymous reviewer

What does it mean to be highly social?  Considering the so-called four ‘pinnacles’ of animal society (Wilson, 1975) – humans, cooperative breeding as found in some non-human mammals and birds, the social insects, and colonial marine invertebrates – having inter-individual relations extending beyond the sexual pair and the parent-offspring interaction is foremost.  In many cases being social implies a high local population density, interaction with the same group of individuals over an extended time period, and an overlapping of generations.  Additional features of social species may be a wide geographical range, perhaps associated with ecological and behavioral plasticity, the latter often facilitated by cultural transmission of traditions.  

Narrowing our perspective to the domain of PCI Evolutionary Biology, we might continue our question by asking whether being social predisposes one to a special evolutionary path toward the future.  Do social species evolve faster (or slower) than their more solitary relatives such that over time they are more unlike (or similar to) those relatives (anagenesis)?  And are evolutionary changes in social species more or less likely to be accompanied by lineage splitting (cladogenesis) and ultimately speciation?  The latter question is parallel to one first posed over 40 years ago (West-Eberhard, 1979; Lande, 1981) for sexually selected traits:  Do strong mating preferences and conspicuous courtship signals generate speciation via the Fisherian process or ecological divergence?  An extensive survey of birds had found little supporting evidence (Price, 1998), but a recent one that focused on plumage complexity in tanagers did reveal a relationship, albeit a weak one (Price-Waldman et al., 2020).  Because sexual selection has been viewed as a part of the broader process of social selection (West-Eberhard, 1979), it is thus fitting to extend our surveys to the evolutionary implications of being social.

Unlike the inquiry for a sexual selection - evolutionary change connection, a social behavior counterpart has remained relatively untreated.  Diverse logistical problems might account for this oversight.  What objective proxies can be used for social behavior, and for the rate of evolutionary change within a lineage?  How many empirical studies have generated data from which appropriate proxies could be extracted?  More intractable is the conundrum arising from the connectedness between socially- and sexually-selected traits.  For example, the elevated population density found in highly social species can greatly increase the mating advantage enjoyed by an attractive male.  If anagenesis is detected, did it result from social behavior or sexual selection?  And if social behavior leads to a group structure in which male-male competition is reduced, would a modest rate of evolutionary change be support for the sexual selection - evolutionary speed connection or evidence opposing the sociality - evolution one?

Against the above odds, several biologists have begun to explore the notion that social behavior just might favor evolutionary speed in either anagenesis or cladogenesis.  In a recent analysis relying on the comparative method, Lluís Socias-Martínez and Louise Rachel Peckre (2023) combed the scientific literature archives and identified those studies with specific data on the relationships between sexual selection or social behavior and evolutionary change, either anagenesis or cladogenesis.  The authors were careful to employ fairly conservative criteria for including studies, and the number eventually retained was small.  Nonetheless, some patterns emerge:  Many more studies report anagenesis than cladogenesis, and many more report correlations with sexually-selected traits than with non-sexual social behavior ones.  And, no study indicates a potential effect of social behavior on cladogenesis.  Is this latter observation authentic or an artifact of a paucity of data?  There are some a priori reasons why cladogenesis may seldom arise.  Whereas highly social behavior could lead to fission encompassing mutually isolated population clusters within a species, social behavior may also engender counterbalancing plasticity that allows and even promotes inter-cluster migration and fusion.  And briefly – and non-systematically, as the rate of lineage splitting would need to be measured – looking at one of the pinnacles of animal social behavior, the social insects, there is little indication that diversification has been accelerated.  There are fewer than 3000 described species of termites, only ca. 16,000 ants, and the vast majority of bees and wasps are solitary.                            

Lluís Socias-Martínez and Louise Rachel Peckre provide us with a very detailed discussion of these and a myriad of other complications.  I end with a common refrain, we need more consideration of the authors’ interesting question, and much more data and analysis.  One can thank Socias-Martínez and Peckre for pointing us in that direction.

References

Lande, R. (1981). Models of speciation by sexual selection on polygenic traits. Proc. Natn. Acad. Sci. USA 78, 3721-3725. https://doi.org/10.1073/pnas.78.6.3721

Price, T. (1998). Sexual selection and natural selection in bird speciation. Phil. Trans. Roy. Soc. B, 353, 251-260.  https://doi.org/10.1098/rstb.1998.0207  

Price‐Waldman, R. M., Shultz, A. J., & Burns, K. J. (2020). Speciation rates are correlated with changes in plumage color complexity in the largest family of songbirds. Evolution, 74(6), 1155–1169. https://doi.org/10.1111/evo.13982

Socias-Martínez and Peckre. (2023). Does sociality affect evolutionary speed? Zenodo, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.5281/zenodo.10086186

West-Eberhard, M. J. (1979). Sexual selection, social competition, and evolution. Proceedings of the American Philosophical Society, 123(4), 222–234. http://www.jstor.org/stable/2828804

Wilson, E. O. (1975). Sociobiology. The New Synthesis. Cambridge, Mass., The Belknap Press of Harvard University

18 Nov 2020
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A demogenetic agent based model for the evolution of traits and genome architecture under sexual selection

Sexual selection goes dynamic

Recommended by based on reviews by Frédéric Guillaume and 1 anonymous reviewer

150 years after Darwin published ‘Descent of man and selection in relation to sex’ (Darwin, 1871), the evolutionary mechanism that he laid out in his treatise continues to fascinate us. Sexual selection is responsible for some of the most spectacular traits among animals, and plants, and it appeals to our interest in all things reproductive and sexual (Bell, 1982). In addition, sexual selection poses some of the more intractable problems in evolutionary biology: Its realm encompasses traits that are subject to markedly different selection pressures, particularly when distinct, yet associated, traits tend to be associated with males, e.g. courtship signals, and with females, e.g. preferences (cf. Ah-King & Ahnesjo, 2013). While separate, such traits cannot evolve independently of each other (Arnqvist & Rowe, 2005), and complex feedback loops and correlations between them are predicted (Greenfield et al., 2014). Traditionally, sexual selection has been modelled under simplifying assumptions, and quantitative genetic approaches that avoided evolutionary dynamics have prevailed. New computing methods may be able to free the field from these constraints, and a trio of theoreticians (Chevalier, De Coligny & Labonne 2020) describe here a novel application of a ‘demo-genetic agent (or individual) based model’, a mouthful hereafter termed DG-ABM, for arriving at a holistic picture of the sexual selection trajectory. The application is built on the premise that traits, e.g. courtship, preference, gamete investment, competitiveness for mates, can influence the genetic architecture, e.g. correlations, of those traits. In turn, the genetic architecture can influence the expression and evolvability of the traits. Much of this influence occurs via demographic features, i.e. social environment, generated by behavioral interactions during sexual advertisement, courtship, mate guarding, parental care, post-mating dispersal, etc.
The authors provide a lengthy verbal description of their model, specifying the genomic and behavioral parameters that can be set and how a ‘run’ may be initialized. There is a link to an internet site where users can then enter their own parameter values and begin exploring hypotheses. Back in the article several simulations illustrate simple tests; e.g. how gamete investment and preference jointly evolve given certain survival costs. One obvious test would have been the preference – courtship genetic correlation that represents the core of Fisherian runaway selection, and it is regrettable that it was not examined under a range of demographic parameters. As presented the author’s DG-ABM appears particularly geared toward mating systems in ‘higher’ vertebrates, where couples form during a discrete mating season and are responsible for most reproduction. It is not clear how applicable the model could be to a full range of mating systems and nuances, including those in arthropods and other invertebrates as well as plants.
What is the likely value of the DG-ABM for sexual selection researchers? We will not be able to evaluate its potential impact until readers with specialized understanding of a question and taxon begin exploring and comparing their results with prior expectations. Of course, lack of congruence with earlier predictions would not invalidate the model. Hopefully, some of these specialists will have opportunities for comparing results with pertinent empirical data.

References

Ah-King, M. and Ahnesjo, I. 2013. The ‘sex role’ concept: An overview and evaluation Evolutionary Biology, 40, 461-470. doi: https://doi.org/10.1007/s11692-013-9226-7
Arnqvist, G. and Rowe, L. 2005. Sexual Conflict. Princeton University Press, Princeton. doi: https://doi.org/10.1515/9781400850600
Bell, G. 1982. The Masterpiece of Nature: The Evolution and Genetics of Sexuality. University of California Press, Berkeley.
Chevalier, L., De Coligny, F. and Labonne, J. (2020) A demogenetic individual based model for the evolution of traits and genome architecture under sexual selection. bioRxiv, 2020.04.01.014514, ver. 4 peer-reviewed and recommended by PCI Evol Biol. doi: https://doi.org/10.1101/2020.04.01.014514
Darwin, C. 1871. The Descent of Man and Selection in Relation to Sex. J. Murray, London.
Greenfield, M.D., Alem, S., Limousin, D. and Bailey, N.W. 2014. The dilemma of Fisherian sexual selection: Mate choice for indirect benefits despite rarity and overall weakness of trait-preference genetic correlation. Evolution, 68, 3524-3536. doi: https://doi.org/10.1111/evo.12542

16 Dec 2016
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POSTPRINT

Evolutionary robotics simulations help explain why reciprocity is rare in nature.

Simulated robots and the evolution of reciprocity

Recommended by and

Of the various forms of cooperative and altruistic behavior, reciprocity remains the most contentious. Humans certainly exhibit reciprocity – under certain circumstances – and various non-human animals behave in ways suggesting that they do as well. Thus, evolutionary biologists have sought to explain why non-relatives might engage in altruistic transactions when a substantial delay occurs between helping and compensation; i.e. an individual may be a donor today and a beneficiary tomorrow, or vice-versa. This quest, aided by game theory and computer modeling late in the past century, identified some strategies for reciprocal behavior that could work – in theory. But when biologists looked for confirmation of these strategies in animals they found little evidence that stood up to rigorous testing. In a recent paper André and Nolfi [1] offer a compelling reason for this observed rarity of reciprocity: Reciprocal behavior that animals might exhibit is a bit more complex than any of the game theoretic strategies, and even the simplest forms of realistic behavior would entail several nearly simultaneous mutations, an unlikely occurrence. André and Nolfi [1] relied on neural networks to test actors, robots that could evolve helping and reciprocal behavior from a basal level of selfishness. In an extensive series of simulations, they found that reciprocal behavior did not take hold in a population, largely because the various intermediates to full reciprocity were eliminated before the subsequent mutations occurred. The findings are satisfying given our current knowledge of animal behavior, but questions remain. Notably, how does one account for those rare cases in which reciprocity does meet all the criteria? The authors suggest some possibilities, but an analysis will await their next study.

Reference

[1] André J-B, Nolfi S. 2016. Evolutionary robotics simulations help explain why reciprocity is rare in nature. Scientific Reports 6:32785. doi: 10.1038/srep32785

Reviews:  3

16 Jun 2022
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Sensory plasticity in a socially plastic bee

Taking advantage of facultative sociality in sweat bees to study the developmental plasticity of antennal sense organs and its association with social phenotype

Recommended by based on reviews by Michael D Greenfield, Sylvia Anton and Lluís Socias-Martínez

The study of the evolution of sociality is closely associated with the study of the evolution of sensory systems. Indeed, group life and sociality necessitate that individuals recognize each other and detect outsiders, as seen in eusocial insects such as Hymenoptera. While we know that antennal sense organs that are involved in olfactory perception are found in greater densities in social species of that group compared to solitary hymenopterans, whether this among-species correlation represents the consequence of social evolution leading to sensory evolution, or the opposite, is still questioned. Knowing more about how sociality and sensory abilities covary within a species would help us understand the evolutionary sequence. Studying a species that shows social plasticity, that is facultatively social, would further allow disentangling the cause and consequence of social evolution and sensory systems and the implication of plasticity in the process.

Boulton and Field (2022) studied a species of sweat bee that shows social plasticity, Halictus rubicundus. They studied populations at different latitudes in Great Britain: populations in the North are solitary, while populations in the south often show sociality, as they face a longer and warmer growing season, leading to the opportunity for two generations in a single year, a pre-condition for the presence of workers provisioning for the (second) brood. Using scanning electron microscope imaging, the authors compared the density of antennal sensilla types in these different populations (north, mid-latitude, south) to test for an association between sociality and olfactory perception capacities. They counted three distinct types of antennal sensilla: olfactory plates, olfactory hairs, and thermos/hygro-receptive pores, used to detect humidity, temperature and CO2. In addition, they took advantage of facultative sociality in this species by transplanting individuals from a northern population (solitary) to a southern location (where conditions favour sociality), to study how social plasticity is reflected (or not) in the density of antennal sensilla types. They tested the prediction that olfactory sensilla density is also developmentally plastic in this species.

Their results show that antennal sensilla counts differ between the 3 studied regions (north, mid-latitude, south), but not as predicted. Individuals in the southern population were not significantly different from the mid-latitude and northern ones in their count of olfactory plates and they had less, not more, thermos/hygro receptors than mid-latitude and northern individuals. Furthermore, mid-latitude individuals had more olfactory hairs than the ones from the northern population and did not differ from southern ones. The prediction was that the individuals expressing sociality would have the highest count of these olfactory hairs. This unpredicted pattern based on the latitude of sampling sites may be due to the effect of temperature during development, which was higher in the mid-latitude site than in the southern one. It could also be the result of a genotype-by-environment interaction, where the mid-latitude population has a different developmental response to temperature compared to the other populations, a difference that is genetically determined (a different “reaction norm”). Reciprocal transplant experiments coupled with temperature measurements directly on site would provide interesting information to help further dissect this intriguing pattern. 

Interestingly, where a sweat bee developed had a significant effect on their antennal sensilla counts: individuals originating from the North that developed in the south after transplantation had significantly more olfactory hairs on their antenna than individuals from the same Northern population that developed in the North. This is in accordance with the prediction that the characteristics of sensory organs can also be plastic. However, there was no difference in antennal characteristics depending on whether these transplanted bees became solitary or expressed the social phenotype (foundress or worker). This result further supports the hypothesis that temperature affects development in this species and that these sensory characteristics are also plastic, although independently of sociality. Overall, the work of Boulton and Field underscores the importance of including phenotypic plasticity in the study of the evolution of social behaviour and provides a robust and fruitful model system to explore this further.

References

Boulton RA, Field J (2022) Sensory plasticity in a socially plastic bee. bioRxiv, 2022.01.29.478030, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.01.29.478030

20 Jan 2020
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A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest

Estimating recent divergence history: making the most of microsatellite data and Approximate Bayesian Computation approaches

Recommended by and based on reviews by Michael D Greenfield and 2 anonymous reviewers

The present-day distribution of extant species is the result of the interplay between their past population demography (e.g., expansion, contraction, isolation, and migration) and adaptation to the environment. Shedding light on the timing and magnitude of key demographic events helps identify potential drivers of such events and interaction of those drivers, such as life history traits and past episodes of environmental shifts.

The understanding of the key factors driving species evolution gives important insights into how the species may respond to changing conditions, which can be particularly relevant for the management of harmful species, such as agricultural pests (e.g. [1]). Meaningful demographic inferences present major challenges. These include formulating evolutionary scenarios fitting species biology and the eco-geographical context and choosing informative molecular markers and accurate quantitative approaches to statistically compare multiple demographic scenarios and estimate the parameters of interest. A further issue comes with result interpretation. Accurately dating the inferred events is far from straightforward since reliable calibration points are necessary to translate the molecular estimates of the evolutionary time into absolute time units (i.e. years). This can be attempted in different ways, such as by using fossil and archaeological records, heterochronous samples (e.g. ancient DNA), and/or mutation rate estimated from independent data (e.g. [2], [3] for review). Nonetheless, most experimental systems rarely meet these conditions, hindering the comprehensive interpretation of results.

The contribution of Chapuis et al. [4] addresses these issues to investigate the recent history of the African insect pest Schistocerca gregaria (desert locust). They apply Approximate Bayesian Computation-Random Forest (ABC-RF) approaches to microsatellite markers. Owing to their fast mutation rate microsatellite markers offer at least two advantages: i) suitability for analyzing recently diverged populations, and ii) direct estimate of the germline mutation rate in pedigree samples. The work of Chapuis et al. [4] benefits of both these advantages, since they have estimates of mutation rate and allele size constraints derived from germline mutations in the species [5].

The main aim of the study is to infer the history of divergence of the two subspecies of the desert locust, which have spatially disjoint distribution corresponding to the dry regions of North and West-South Africa. They first use paleo-vegetation maps to formulate hypotheses about changes in species range since the last glacial maximum. Based on them, they generate 12 divergence models. For the selection of the demographic model and parameter estimation, they apply the recently developed ABC-RF approach, a powerful inferential tool that allows optimizing the use of summary statistics information content, among other advantages [6]. Some methodological novelties are also introduced in this work, such as the computation of the error associated with the posterior parameter estimates under the best scenario. The accuracy of timing estimate is assured in two ways: i) by the use of microsatellite markers with known evolutionary dynamics, as underlined above, and ii) by assessing the divergence time threshold above which posterior estimates are likely to be biased by size homoplasy and limits in allele size range [7]. The best-supported model suggests a recent divergence event of the subspecies of S. gregaria (around 2.6 kya) and a reduction of populations size in one of the subspecies (S. g. flaviventris) that colonized the southern distribution area. As such, results did not support the hypothesis that the southward colonization was driven by the expansion of African dry environments associated with the last glacial maximum, as it has been postulated for other arid-adapted species with similar African disjoint distributions [8]. The estimated time of divergence points at a much more recent origin for the two subspecies, during the late Holocene, in a period corresponding to fairly stable arid conditions similar to current ones [9,10].

Although the authors cannot exclude that their microsatellite data bear limited information on older colonization events than the last one, they bring arguments in favour of alternative explanations. The hypothesis privileged does not involve climatic drivers, but the particularly efficient dispersal behaviour of the species, whose individuals are able to fly over long distances (up to thousands of kilometers) under favourable windy conditions. A single long-distance dispersal event by a few individuals would explain the genetic signature of the bottleneck. There is a growing number of studies in phylogeography in arid regions in the Southern hemisphere, but the impact of past climate changes on the species distribution in this region remains understudied relative to the Northern hemisphere [11,12].

The study presented by Chapuis et al. [4] offers several important insights into demographic changes and the evolutionary history of an agriculturally important pest species in Africa, which could also mirror the history of other organisms in the continent. As the authors point out, there are necessarily some uncertainties associated with the models of past ecosystems and climate, especially for Africa. Interestingly, the authors argue that the information on paleo-vegetation turnover was more informative than climatic niche modeling for the purpose of their study since it made them consider a wider range of bio-geographical changes and in turn a wider range of evolutionary scenarios (see discussion in Supplementary Material). Microsatellite markers have been offering a useful tool in population genetics and phylogeography for decades, but their popularity is perhaps being taken over by single nucleotide polymorphism (SNP) genotyping and whole-genome sequencing (WGS) (the peak year of the number of the publication with “microsatellite” is in 2012 according to PubMed).

This study reaffirms the usefulness of these classic molecular markers to estimate past demographic events, especially when species- and locus-specific microsatellite mutation features are available and a powerful inferential approach is adopted. Nonetheless, there are still hurdles to overcome, such as the limitations in scenario choice associated with the simulation software used (e.g. not allowing for continuous gene flow in this particular case), which calls for further improvement of simulation tools allowing for more flexible modeling of demographic events and mutation patterns. In sum, this work not only contributes to our understanding of the makeup of the African biodiversity but also offers a useful statistical framework, which can be applied to a wide array of species and molecular markers (microsatellites, SNPs, and WGS).

References

[1] Lehmann, P. et al. (2018). Complex responses of global insect pests to climate change. bioRxiv, 425488. doi: https://dx.doi.org/10.1101/425488

[2] Donoghue, P. C., & Benton, M. J. (2007). Rocks and clocks: calibrating the Tree of Life using fossils and molecules. Trends in Ecology & Evolution, 22(8), 424-431. doi: https://dx.doi.org/10.1016/j.tree.2007.05.005

[3] Ho, S. Y., Lanfear, R., Bromham, L., Phillips, M. J., Soubrier, J., Rodrigo, A. G., & Cooper, A. (2011). Time‐dependent rates of molecular evolution. Molecular ecology, 20(15), 3087-3101. doi: https://dx.doi.org/10.1111/j.1365-294X.2011.05178.x

[4] Chapuis, M.-P., Raynal, L., Plantamp, C., Meynard, C. N., Blondin, L., Marin, J.-M. and Estoup, A. (2020). A young age of subspecific divergence in the desert locust Schistocerca gregaria, inferred by ABC Random Forest. bioRxiv, 671867, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. doi: https://dx.doi.org/10.1101/671867

5] Chapuis, M.-P., Plantamp, C., Streiff, R., Blondin, L., & Piou, C. (2015). Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations. Molecular ecology, 24(24), 6107-6119. doi: https://dx.doi.org/10.1111/mec.13465

[6] Raynal, L., Marin, J. M., Pudlo, P., Ribatet, M., Robert, C. P., & Estoup, A. (2018). ABC random forests for Bayesian parameter inference. Bioinformatics, 35(10), 1720-1728. doi: https://dx.doi.org/10.1093/bioinformatics/bty867

[7] Estoup, A., Jarne, P., & Cornuet, J. M. (2002). Homoplasy and mutation model at microsatellite loci and their consequences for population genetics analysis. Molecular ecology, 11(9), 1591-1604. doi: https://dx.doi.org/10.1046/j.1365-294X.2002.01576.x

[8] Moodley, Y. et al. (2018). Contrasting evolutionary history, anthropogenic declines and genetic contact in the northern and southern white rhinoceros (Ceratotherium simum). Proceedings of the Royal Society B, 285(1890), 20181567. doi: https://dx.doi.org/10.1098/rspb.2018.1567

[9] Kröpelin, S. et al. (2008). Climate-driven ecosystem succession in the Sahara: the past 6000 years. science, 320(5877), 765-768. doi: https://dx.doi.org/10.1126/science.1154913

[10] Maley, J. et al. (2018). Late Holocene forest contraction and fragmentation in central Africa. Quaternary Research, 89(1), 43-59. doi: https://dx.doi.org/10.1017/qua.2017.97

[11] Beheregaray, L. B. (2008). Twenty years of phylogeography: the state of the field and the challenges for the Southern Hemisphere. Molecular Ecology, 17(17), 3754-3774. doi: https://dx.doi.org/10.1111/j.1365-294X.2008.03857.x

[12] Dubey, S., & Shine, R. (2012). Are reptile and amphibian species younger in the Northern Hemisphere than in the Southern Hemisphere?. Journal of evolutionary biology, 25(1), 220-226. doi: https://dx.doi.org/10.1111/j.1420-9101.2011.02417.x

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12 Jul 2017
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Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly

The pros and cons of mating with strangers

Recommended by based on reviews by Joël Meunier and Michael D Greenfield

 

Interspecific matings are by definition rare events in nature, but when they occur they can be very important, and not only because they might condition gene flow between species. Even when such matings have no genetic consequence, for instance if they do not yield any fertile hybrid offspring, they can still have an impact on the population dynamics of the species involved [1]. Such atypical pairings between heterospecific partners are usually regarded as detrimental or undesired; as they interfere with the occurrence or success of intraspecific matings, they are expected to cause a decline in absolute fitness.
The story is not always so simple however, and it might all depend on the timing of events and on the identity of the partners. Using the herbivorous mite Tetranychus urticae as a model, Clemente et al. [2] experimentally arranged matings with two other Tetranychus species that commonly share the same host plants as T. urticae. They carefully controlled the history of events: heterospecific matings could occur just before, just after, 24h before, or 24h after, a conspecific mating. Interestingly, the oviposition rate (total fecundity) of females was increased when mating with a heterospecific individual. This suggests that heterospecic sperm can stimulate oogenesis just as conspecific sperm does. Such a positive effect was observed for matings involving T. ludeni females and T. urticae males, but a negative effect is found in the interaction with T. evansi. Sex-ratio (fertilization success in those species) could also be impacted but, unlike fertilization, this occurred when the mating events were distant in time. This is is at odds with what is observed in conspecific matings, where sperm displacement occurs only if mating events are temporally close. Overall, the effects of heterospecific mating were quite variable and it is challenging to predict a single, general, effect of interspecific matings. The net effect will likely be context-dependent, depending on the relative frequency of the difference mating sequences and on how fecundity and sex-ratio contribute to overall fitness, both aspect strongly influenced by the population dynamics and structure.

References

[1] Gröning J. & Hochkirch A. 2008. Reproductive interference between animal species. The Quarterly Review of Biology 83: 257-282. doi: 10.1086/590510

[2] Clemente SH, Santos I, Ponce AR, Rodrigues LR, Varela SAM & Magalhaes S. 2017 Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly. bioRxiv 113274, ver. 4 of the 30th of June 2017. doi: 10.1101/113274

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GREENFIELD Michael D

  • Equipe Neuro-Ethologie Sensorielle, ENES/Neuro-PSI, CNRS UMR 9197, , Université de Lyon/Saint-Etienne,, 42023 Saint Etienne, France
  • Behavior & Social Evolution, Evolutionary Ecology, Phenotypic Plasticity, Phylogeography & Biogeography, Quantitative Genetics, Sexual Selection
  • recommender

Recommendations:  3

Reviews:  3

Areas of expertise
B.A. New York University (1973 ; biology, engineering) Ph.D. University of Wisconsin, Madison (1978 ; entomology) assistant - associate professor ; University of California, Los Angeles (1981-1993) professor ; University of Kansas (1991 - 2007) adjunct professor ; University of Kansas (2007 - present) professeur / chercheur ; CNRS (IRBI, UMR 7261) , Tours, France (2006 - 2018) Chercheur Associé / Professeur Invité (2019 - present) Equipe Neuro-Ethologie Sensorielle, ENES/Neuro-PSI, CNRS UMR 9197, Université de Lyon/Saint-Etienne, 42023 Saint Etienne, France