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Journal articles on the topic 'Mimicry'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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1

Jamie, Gabriel A. "Signals, cues and the nature of mimicry." Proceedings of the Royal Society B: Biological Sciences 284, no. 1849 (February 22, 2017): 20162080. http://dx.doi.org/10.1098/rspb.2016.2080.

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‘Mimicry’ is used in the evolutionary and ecological literature to describe diverse phenomena. Many are textbook examples of natural selection's power to produce stunning adaptations. However, there remains a lack of clarity over how mimetic resemblances are conceptually related to each other. The result is that categories denoting the traditional subdivisions of mimicry are applied inconsistently across studies, hindering attempts at conceptual unification. This review critically examines the logic by which mimicry can be conceptually organized and analysed. It highlights the following three evolutionarily relevant distinctions. (i) Are the model's traits being mimicked signals or cues? (ii) Does the mimic signal a fitness benefit or fitness cost in order to manipulate the receiver's behaviour? (iii) Is the mimic's signal deceptive? The first distinction divides mimicry into two broad categories: ‘signal mimicry’ and ‘cue mimicry’. ‘Signal mimicry’ occurs when mimic and model share the same receiver, and ‘cue mimicry’ when mimic and model have different receivers or when there is no receiver for the model's trait. ‘Masquerade’ fits conceptually within cue mimicry. The second and third distinctions divide both signal and cue mimicry into four types each. These are the three traditional mimicry categories (aggressive, Batesian and Müllerian) and a fourth, often overlooked category for which the term ‘rewarding mimicry’ is suggested. Rewarding mimicry occurs when the mimic's signal is non-deceptive (as in Müllerian mimicry) but where the mimic signals a fitness benefit to the receiver (as in aggressive mimicry). The existence of rewarding mimicry is a logical extension of the criteria used to differentiate the three well-recognized forms of mimicry. These four forms of mimicry are not discrete, immutable types, but rather help to define important axes along which mimicry can vary.

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2

Pimonov, V. I. "MIMICRY AND THEATRICALITY: A FORMAL MODEL." Izvestiya of the Samara Science Centre of the Russian Academy of Sciences. Social, Humanitarian, Medicobiological Sciences 24, no. 87 (2022): 83–90. http://dx.doi.org/10.37313/2413-9645-2022-24-87-83-90.

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Object of the article: mimicry and theatricality. Subject of the article: difference and similarity between mimicry and theatricality. Purpose of the research: creating the semiotic model of transformation of mimicry into theatricality. Results: in mimicry, three meta-roles are at play: the mimic, the dupe and the model. The mimic imitates signals, emitted by the model. The dupe, being an enemy of the mimic, is thus deceived by the mimic's signals. Mimicry can be expressed by the scheme: “A” acts in front of “B” in the role of “C”, where “A” is the mimic, “B” is the dupe - a victim of deception, “C” is the model. Mimicry formally resembles theatricality, where "A" is the character of the play (functionally corresponding to the mimic), "B" is the character-spectator, corresponding to the dupe (victim of deception), "C" is another character, functionally corresponding to the "model". Even so, the difference between signals in mimicry and signs in theater is crucial. Field of application: semiotics, literary studies. Conclusions: The mimicry-to-theatricality transformation requires a real or imaginary border between the space of everyday life and “marked” territory (museum, houseof-worship, stage) that serves as a stop-signal inhibiting (or preventing) automatic actions.

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3

Kikuchi, David W., and David W. Pfennig. "A Batesian mimic and its model share color production mechanisms." Current Zoology 58, no. 4 (August 1, 2012): 658–67. http://dx.doi.org/10.1093/czoolo/58.4.658.

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Abstract Batesian mimics are harmless prey species that resemble dangerous ones (models), and thus receive protection from predators. How such adaptive resemblances evolve is a classical problem in evolutionary biology. Mimicry is typically thought to be difficult to evolve, especially if the model and mimic produce the convergent phenotype through different proximate mechanisms. However, mimicry may evolve more readily if mimic and model share similar pathways for producing the convergent phenotype. In such cases, these pathways can be co-opted in ancestral mimic populations to produce high-fidelity mimicry without the need for major evolutionary innovations. Here, we show that a Batesian mimic, the scarlet kingsnake Lampropeltis elapsoides, produces its coloration using the same physiological mechanisms as does its model, the eastern coral snake Micrurus fulvius. Therefore, precise color mimicry may have been able to evolve easily in this system. Generally, we know relatively little about the proximate mechanisms underlying mimicry.

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4

McLean, Donald James, and Marie E. Herberstein. "Mimicry in motion and morphology: do information limitation, trade-offs or compensation relax selection for mimetic accuracy?" Proceedings of the Royal Society B: Biological Sciences 288, no. 1952 (June 9, 2021): 20210815. http://dx.doi.org/10.1098/rspb.2021.0815.

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Many animals mimic dangerous or undesirable prey as a defence from predators. We would expect predators to reliably avoid animals that closely resemble dangerous prey, yet imperfect mimics are common across a wide taxonomic range. There have been many hypotheses suggested to explain imperfect mimicry, but comparative tests across multiple mimicry systems are needed to determine which are applicable, and which—if any—represent general principles governing imperfect mimicry. We tested four hypotheses on Australian ant mimics and found support for only one of them: the information limitation hypothesis. A predator with incomplete information will be unable to discriminate some poor mimics from their models. We further present a simple model to show that predators are likely to operate with incomplete information because they forage and make decisions while they are learning, so might never learn to properly discriminate poor mimics from their models. We found no evidence that one accurate mimetic trait can compensate for, or constrain, another, or that rapid movement reduces selection pressure for good mimicry. We argue that information limitation may be a general principle behind imperfect mimicry of complex traits, while interactions between components of mimicry are unlikely to provide a general explanation for imperfect mimicry.

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5

Finkbeiner, Susan D., Patricio A. Salazar, Sofía Nogales, Cassidi E. Rush, Adriana D. Briscoe, Ryan I. Hill, Marcus R. Kronforst, Keith R. Willmott, and Sean P. Mullen. "Frequency dependence shapes the adaptive landscape of imperfect Batesian mimicry." Proceedings of the Royal Society B: Biological Sciences 285, no. 1876 (April 4, 2018): 20172786. http://dx.doi.org/10.1098/rspb.2017.2786.

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Despite more than a century of biological research on the evolution and maintenance of mimetic signals, the relative frequencies of models and mimics necessary to establish and maintain Batesian mimicry in natural populations remain understudied. Here we investigate the frequency-dependent dynamics of imperfect Batesian mimicry, using predation experiments involving artificial butterfly models. We use two geographically distinct populations of Adelpha butterflies that vary in their relative frequencies of a putatively defended model ( Adelpha iphiclus ) and Batesian mimic ( Adelpha serpa ). We found that in Costa Rica, where both species share similar abundances, Batesian mimicry breaks down, and predators more readily attack artificial butterfly models of the presumed mimic, A. serpa . By contrast, in Ecuador, where A. iphiclus (model) is significantly more abundant than A. serpa (mimic), both species are equally protected from predation. Our results provide compelling experimental evidence that imperfect Batesian mimicry is frequency-dependent on the relative abundance of models and mimics in natural populations, and contribute to the growing body of evidence that complex dynamics, such as seasonality or the availability of alternative prey, influence the evolution of mimetic traits.

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6

Cheney, Karen L., and Isabelle M. Côté. "Aggressive mimics profit from a model–signal receiver mutualism." Proceedings of the Royal Society B: Biological Sciences 274, no. 1622 (June 25, 2007): 2087–91. http://dx.doi.org/10.1098/rspb.2007.0543.

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Mimetic species have evolved to resemble other species to avoid predation (protective mimicry) or gain access to food (aggressive mimicry). Mimicry systems are frequently tripartite interactions involving a mimic, model and ‘signal receiver’. Changes in the strength of the relationship between model and signal receiver, owing to shifting environmental conditions, for example, can affect the success of mimics in protective mimicry systems. Here, we show that an experimentally induced shift in the strength of the relationship between a model (bluestreak cleaner fish, Labroides dimidiatus ) and a signal receiver (staghorn damselfish, Amblyglyphidodon curacao ) resulted in increased foraging success for an aggressive mimic (bluestriped fangblenny, Plagiotremus rhinorhynchos ). When the parasite loads of staghorn damselfish clients were experimentally increased, the attack success of bluestriped fangblenny on damselfish also increased. Enhanced mimic success appeared to be due to relaxation of vigilance by parasitized clients, which sought cleaners more eagerly and had lower overall aggression levels. Signal receivers may therefore be more tolerant of and/or more vulnerable to attacks from aggressive mimics when the net benefit of interacting with their models is high. Changes in environmental conditions that cause shifts in the net benefits accrued by models and signal receivers may have important implications for the persistence of aggressive mimicry systems.

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7

Russell, Avery L., David W. Kikuchi, Noah W. Giebink, and Daniel R. Papaj. "Sensory bias and signal detection trade-offs maintain intersexual floral mimicry." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1802 (May 18, 2020): 20190469. http://dx.doi.org/10.1098/rstb.2019.0469.

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Mimicry is common in interspecies interactions, yet conditions maintaining Batesian mimicry have been primarily tested in predator–prey interactions. In pollination mutualisms, floral mimetic signals thought to dupe animals into pollinating unrewarding flowers are widespread (greater than 32 plant families). Yet whether animals learn to both correctly identify floral models and reject floral mimics and whether these responses are frequency-dependent is not well understood. We tested how learning affected the effectiveness and frequency-dependence of imperfect Batesian mimicry among flowers using the generalist bumblebee, Bombus impatiens , visiting Begonia odorata , a plant species exhibiting intersexual floral mimicry. Unrewarding female flowers are mimics of pollen-rewarding male flowers (models), though mimicry to the human eye is imperfect. Flower-naive bees exhibited a perceptual bias for mimics over models, but rapidly learned to avoid mimics. Surprisingly, altering the frequency of models and mimics only marginally shaped responses by naive bees and by bees experienced with the distribution and frequency of models and mimics. Our results provide evidence both of exploitation by the plant of signal detection trade-offs in bees and of resistance by the bees, via learning, to this exploitation. Critically, we provide experimental evidence that imperfect Batesian mimicry can be adaptive and, in contrast with expectations of signal detection theory, functions largely independently of the model and mimic frequency. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

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8

Pfennig, David W., and David W. Kikuchi. "Competition and the evolution of imperfect mimicry." Current Zoology 58, no. 4 (August 1, 2012): 608–19. http://dx.doi.org/10.1093/czoolo/58.4.608.

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Abstract Mimicry is widely used to exemplify natural selection’s power in promoting adaptation. Nonetheless, it has become increasingly clear that mimicry is frequently imprecise. Indeed, the phenotypic match is often poor between mimics and models in many Batesian mimicry complexes and among co-mimics in many Müllerian mimicry complexes. Here, we consider whether such imperfect mimicry represents an evolutionary compromise between predator-mediated selection favoring mimetic convergence on the one hand and competitively mediated selection favoring divergence on the other hand. Specifically, for mimicry to be effective, mimics and their models/co-mimics should occur together. Yet, co-occurring species that are phenotypically similar often compete for resources, successful reproduction, or both. As an adaptive response to minimize such costly interactions, interacting species may diverge phenotypically through an evolutionary process known as character displacement. Such divergence between mimics and their models/co-mimics may thereby result in imperfect mimicry. We review the various ways in which character displacement could promote imprecise mimicry, describe the conditions under which this process may be especially likely to produce imperfect mimicry, examine a possible case study, and discuss avenues for future research. Generally, character displacement may play an underappreciated role in fostering inexact mimicry.

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9

Hlaváček, Antonín, Klára Daňková, Daniel Benda, Petr Bogusch, and Jiří Hadrava. "Batesian-Müllerian mimicry ring around the Oriental hornet (Vespa orientalis)." Journal of Hymenoptera Research 92 (August 31, 2022): 211–28. http://dx.doi.org/10.3897/jhr.92.81380.

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Mimicry is usually understood to be an adaptive resemblance between phylogenetically distant groups of species. In this study, we focus on Batesian and Müllerian mimicry, which are often viewed as a continuum rather than distinct phenomena, forming so-called Batesian-Müllerian mimicry rings. Despite potent defence and wide environmental niche of hornets, little attention has been paid to them as potential models in mimicry research. We propose a Batesian-Müllerian mimicry ring of the Oriental hornet (Vespa orientalis, Hymenoptera: Vespidae) consisting of eight species that coexist in the Mediterranean region. To reveal general ecological patterns, we reviewed their geographical distribution, phenology, and natural history. In accordance with the ‘model-first’ theory, Batesian mimics of this ring occurred later during a season than the Müllerian mimics. In the case of Batesian mimic Volucella zonaria (Diptera: Syrphidae), we presume that temperature-driven range expansion could lead to allopatry with its model, and, potentially, less accurate resemblance to an alternative model, the European hornet (Vespa crabro: Hymenoptera: Vespidae). Colour morphs of polymorphic species Cryptocheilus alternatus (Hymenoptera: Vespidae), Delta unguiculatum (Hymenoptera: Vespidae), Rhynchium oculatum (Hymenoptera: Vespidae), and Scolia erythrocephala (Hymenoptera: Scoliidae) appear to display distinct geographical distribution patterns, and this is possibly driven by sympatry with alternative models from the European hornet (Vespa crabro) complex. General coevolution patterns of models and mimics in heterogenous and temporally dynamic environments are discussed, based on observations of the proposed Oriental hornet mimicry ring.

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10

Pinheiro, Carlos E. G. "Asynchrony in daily activity patterns of butterfly models and mimics." Journal of Tropical Ecology 23, no. 1 (January 2007): 119–23. http://dx.doi.org/10.1017/s0266467406003749.

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Bates' theory of mimicry (Bates 1862) postulates that vertebrate predators avoid attacks on chemically defended butterflies, and a profitable species, usually referred to as the mimic, can obtain protection by resembling one or more unpalatable models. The evolution of Batesian mimicry requires that predators meet, taste and learn to avoid the models before meeting the mimics. For this reason, some authors have adopted the assumption that mimic population sizes must be smaller than the models' populations (Fisher 1930, Huheey 1980, Lindström et al. 1997).

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11

Franks, Daniel W., and Jason Noble. "Batesian mimics influence mimicry ring evolution." Proceedings of the Royal Society of London. Series B: Biological Sciences 271, no. 1535 (January 22, 2004): 191–96. http://dx.doi.org/10.1098/rspb.2003.2582.

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12

Dryden, D. T. F., and M. R. Tock. "DNA mimicry by proteins." Biochemical Society Transactions 34, no. 2 (March 20, 2006): 317–19. http://dx.doi.org/10.1042/bst0340317.

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It has been discovered recently, via structural and biophysical analyses, that proteins can mimic DNA structures in order to inhibit proteins that would normally bind to DNA. Mimicry of the phosphate backbone of DNA, the hydrogen-bonding properties of the nucleotide bases and the bending and twisting of the DNA double helix are all present in the mimics discovered to date. These mimics target a range of proteins and enzymes such as DNA restriction enzymes, DNA repair enzymes, DNA gyrase and nucleosomal and nucleoid-associated proteins. The unusual properties of these protein DNA mimics may provide a foundation for the design of targeted inhibitors of DNA-binding proteins.

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13

Westall, Fred C. "Molecular mimicry or structural mimicry?" Molecular Immunology 43, no. 7 (March 2006): 1062–64. http://dx.doi.org/10.1016/j.molimm.2005.06.039.

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14

Lehtonen, Jussi, and Michael R. Whitehead. "Sexual deception: Coevolution or inescapable exploitation?" Current Zoology 60, no. 1 (February 1, 2014): 52–61. http://dx.doi.org/10.1093/czoolo/60.1.52.

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Abstract Sexual deception involves the mimicry of another species’ sexual signals in order to exploit behavioural routines linked to those signals. Known sexually deceptive systems use visual, acoustic or olfactory mimicry to exploit insects for prédation, cleptoparasitism and pollination. It is predicted that where sexual deception inflicts a cost on the receiver, a coevolutìonary arms race could result in the evolution of discriminating receivers and increasingly refined mimicry. We constructed a conceptual model to understand the importance of trade-offs in the coevolution of sexually deceptive mimic and receiver. Four components examined were: the cost of mimicry, the cost to receiver for being fooled, the density of mimics and the relative magnitude of a mimicry-independent component of fitness. The model predicts that the exploitation of non-discriminating receivers by accurate signal mimicry will evolve as an evolutionary stable strategy under a wide range of the parameter space explored. This is due to the difficulty in minimising the costs of being fooled without incurring the cost of falsely rejecting real mating opportunities. In the model, the evolution of deception is impeded when mimicry imposes substantial costs for both sides of the arms race. Olfactory signals that are potentially cheap to produce are therefore likely to be more vulnerable to exploitation than expensive visual ornaments.

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15

Iserbyt, Arne, Jessica Bots, Stefan Van Dongen, Janice J. Ting, Hans Van Gossum, and Thomas N. Sherratt. "Frequency-dependent variation in mimetic fidelity in an intraspecific mimicry system." Proceedings of the Royal Society B: Biological Sciences 278, no. 1721 (March 2, 2011): 3116–22. http://dx.doi.org/10.1098/rspb.2011.0126.

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Contemporary theory predicts that the degree of mimetic similarity of mimics towards their model should increase as the mimic/model ratio increases. Thus, when the mimic/model ratio is high, then the mimic has to resemble the model very closely to still gain protection from the signal receiver. To date, empirical evidence of this effect is limited to a single example where mimicry occurs between species. Here, for the first time, we test whether mimetic fidelity varies with mimic/model ratios in an intraspecific mimicry system, in which signal receivers are the same species as the mimics and models. To this end, we studied a polymorphic damselfly with a single male phenotype and two female morphs, in which one morph resembles the male phenotype while the other does not. Phenotypic similarity of males to both female morphs was quantified using morphometric data for multiple populations with varying mimic/model ratios repeated over a 3 year period. Our results demonstrate that male-like females were overall closer in size to males than the other female morph. Furthermore, the extent of morphological similarity between male-like females and males, measured as Mahalanobis distances, was frequency-dependent in the direction predicted. Hence, this study provides direct quantitative support for the prediction that the mimetic similarity of mimics to their models increases as the mimic/model ratio increases. We suggest that the phenomenon may be widespread in a range of mimicry systems.

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16

Srygley, Robert B. "Locomotor mimicry in Heliconius butterflies: contrast analyses of flight morphology and kinematics." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 354, no. 1380 (January 29, 1999): 203–14. http://dx.doi.org/10.1098/rstb.1999.0372.

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Müllerian mimicry is a mutualism involving the evolutionary convergence of colour patterns of prey on a warning signal to predators. Behavioural mimicry presumably adds complexity to the signal and makes it more difficult for Batesian mimics to parasitize it. To date, no one has quantified behavioural mimicry in Müllerian mimicry groups. However, morphological similarities among members of mimicry groups suggested that pitching oscillations of the body and wing–beat frequency (WBF) might converge with colour pattern. I compared the morphology and kinematics of four Heliconius species, which comprised two mimicry pairs. Because the mimics arose from two distinct lineages, the relative contributions of mimicry and phylogeny to variation in the species' morphologies and kinematics were examined. The positions of the centre of body mass and centre of wing mass and wing shape diverged among species within lineages, and converged among species within mimicry groups. WBF converged within mimicry groups, and it was coupled with body pitching frequency. However, body–pitching frequency was too variable to distinguish mimicry groups. Convergence in WBF may be due, at least in part, to biomechanical consequences of similarities in wing length, wing shape or the centre of wing mass among co–mimics. Nevertheless, convergence in WBF among passion–vine butterflies serves as the first evidence of behavioural mimicry in a mutualistic context.

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17

Gross, Dawn M., and Brigitte T. Huber. "The mimic of molecular mimicry uncovered." Trends in Microbiology 6, no. 6 (June 1998): 211–12. http://dx.doi.org/10.1016/s0966-842x(98)01287-6.

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18

Cheney, Karen L., and Isabelle M. Côté. "Frequency-dependent success of aggressive mimics in a cleaning symbiosis." Proceedings of the Royal Society B: Biological Sciences 272, no. 1581 (October 4, 2005): 2635–39. http://dx.doi.org/10.1098/rspb.2005.3256.

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Batesian mimics—palatable organisms that resemble unpalatable ones—are usually maintained in populations by frequency-dependent selection. We tested whether this mechanism was also responsible for the maintenance of aggressive mimicry in natural populations of coral reef fishes. The attack success of bluestriped fangblennies ( Plagiotremus rhinorhynchos ), which mimic juvenile bluestreaked cleaner wrasses ( Labroides dimidiatus ) in colour but tear flesh and scales from fishes instead of removing ectoparasites, was frequency-dependent, increasing as mimics became rarer relative to their model. However, cleaner mimics were also more successful on reefs with higher densities of potential victims, perhaps because a dilution-like effect creates few opportunities for potential victims to learn to avoid mimics. Further studies should reveal whether this second mechanism is specific to aggressive mimicry.

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Jønsson, Knud Andreas, Kaspar Delhey, George Sangster, Per G. P. Ericson, and Martin Irestedt. "The evolution of mimicry of friarbirds by orioles (Aves: Passeriformes) in Australo-Pacific archipelagos." Proceedings of the Royal Society B: Biological Sciences 283, no. 1833 (June 29, 2016): 20160409. http://dx.doi.org/10.1098/rspb.2016.0409.

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Observations by Alfred Wallace and Jared Diamond of plumage similarities between co-occurring orioles ( Oriolus ) and friarbirds ( Philemon ) in the Malay archipelago led them to conclude that the former represent visual mimics of the latter. Here, we use molecular phylogenies and plumage reflectance measurements to test several key predictions of the mimicry hypothesis. We show that friarbirds originated before brown orioles, that the two groups did not co-speciate, although there is one plausible instance of co-speciation among species on the neighbouring Moluccan islands of Buru and Seram. Furthermore, we show that greater size disparity between model and mimic and a longer history of co-occurrence have resulted in a stronger plumage similarity (mimicry). This suggests that resemblance between orioles and friarbirds represents mimicry and that colonization of islands by brown orioles has been facilitated by their ability to mimic the aggressive friarbirds.

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Holen, Øistein Haugsten, and Rufus A. Johnstone. "Reciprocal mimicry: kin selection can drive defended prey to resemble their Batesian mimics." Proceedings of the Royal Society B: Biological Sciences 285, no. 1890 (October 31, 2018): 20181149. http://dx.doi.org/10.1098/rspb.2018.1149.

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Established mimicry theory predicts that Batesian mimics are selected to resemble their defended models, while models are selected to become dissimilar from their mimics. However, this theory has mainly considered individual selection acting on solitary organisms such as adult butterflies. Although Batesian mimicry of social insects is common, the few existing applications of kin selection theory to mimicry have emphasized relatedness among mimics rather than among models. Here, we present a signal detection model of Batesian mimicry in which the population of defended model prey is kin structured. Our analysis shows for most of parameter space that increased average dissimilarity from mimics has a twofold group-level cost for the model prey: it attracts more predators and these adopt more aggressive attack strategies. When mimetic resemblance and local relatedness are sufficiently high, such costs acting in the local neighbourhood may outweigh the individual benefits of dissimilarity, causing kin selection to drive the models to resemble their mimics. This requires model prey to be more common than mimics and/or well-defended, the conditions under which Batesian mimicry is thought most successful. Local relatedness makes defended prey easier targets for Batesian mimicry and is likely to stabilize the mimetic relationship over time.

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Wu, Ziwei, and Lingdong Huang. "Mimicry." Proceedings of the ACM on Computer Graphics and Interactive Techniques 4, no. 2 (July 30, 2021): 1–8. http://dx.doi.org/10.1145/3465615.

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The authors have collaborated on a machine learning multiscreen video installation powered by computer algorithms and inspired by mimicry in the natural world. The artwork explores a pseudo-environment loop system in nature and artificial mechanical organisms combining living flowers with projectors, webcams, and computer monitors. Technically, the software adopts a genetic algorithm to simulate the process of mimicry; conceptually, this real-time art installation is in conversation with Nam June Paik's piece TV Garden. The project explores the possibilities of integrating artificial intelligence and nature in the landscape of the future.

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22

Allen, J. A., and J. M. Cooper. "Mimicry." Journal of Biological Education 29, no. 1 (March 1995): 23–26. http://dx.doi.org/10.1080/00219266.1995.9655414.

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23

Grasser, J. P. "Mimicry." Ecotone 17, no. 2 (2021): 123. http://dx.doi.org/10.1353/ect.2021.0039.

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Sennhauser, S., L. May, S. Sakaleshpura Mallikarjunappa, K. Bhatt, and A. Van Beuningen. "Mimicry." Journal of Heart and Lung Transplantation 42, no. 4 (April 2023): S220. http://dx.doi.org/10.1016/j.healun.2023.02.496.

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Pillai, Harikrishna, Harikumar, S. Harikumar, S, Pramod kumar, R. Pramod kumar, R, and Anuraj, K. S. Anuraj, K.S. "Dna Mimicry by Proteins." International Journal of Scientific Research 3, no. 8 (June 1, 2012): 471–72. http://dx.doi.org/10.15373/22778179/august2014/150.

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Akcali, Christopher K., Hibraim Adán Pérez-Mendoza, David W. Kikuchi, and David W. Pfennig. "Multiple models generate a geographical mosaic of resemblance in a Batesian mimicry complex." Proceedings of the Royal Society B: Biological Sciences 286, no. 1911 (September 18, 2019): 20191519. http://dx.doi.org/10.1098/rspb.2019.1519.

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Batesian mimics—benign species that receive protection from predation by resembling a dangerous species—often occur with multiple model species. Here, we examine whether geographical variation in the number of local models generates geographical variation in mimic–model resemblance. In areas with multiple models, selection might be relaxed or even favour imprecise mimicry relative to areas with only one model. We test the prediction that model–mimic match should vary with the number of other model species in a broadly distributed snake mimicry complex where a mimic and a model co-occur both with and without other model species. We found that the mimic resembled its model more closely when they were exclusively sympatric than when they were sympatric with other model species. Moreover, in regions with multiple models, mimic–model resemblance was positively correlated with the resemblance between the model and other model species. However, contrary to predictions, free-ranging natural predators did not attack artificial replicas of imprecise mimics more often when only a single model was present. Taken together, our results suggest that multiple models might generate a geographical mosaic in the degree of phenotype matching between Batesian mimics and their models.

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Kazemi, Baharan, Gabriella Gamberale-Stille, and Olof Leimar. "Multi-trait mimicry and the relative salience of individual traits." Proceedings of the Royal Society B: Biological Sciences 282, no. 1818 (November 7, 2015): 20152127. http://dx.doi.org/10.1098/rspb.2015.2127.

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Mimicry occurs when one species gains protection from predators by resembling an unprofitable model species. The degree of mimic–model similarity is variable in nature and is closely related to the number of traits that the mimic shares with its model. Here, we experimentally test the hypothesis that the relative salience of traits, as perceived by a predator, is an important determinant of the degree of mimic–model similarity required for successful mimicry. We manipulated the relative salience of the traits of a two-trait artificial model prey, and subsequently tested the survival of mimics of the different traits. The unrewarded model prey had two colour traits, black and blue, and the rewarded prey had two combinations of green, brown and grey shades. Blue tits were used as predators. We found that the birds perceived the black and blue traits to be similarly salient in one treatment, and mimic–model similarity in both traits was then required for high mimic success. In a second treatment, the blue trait was the most salient trait, and mimic–model similarity in this trait alone achieved high success. Our results thus support the idea that similar salience of model traits can explain the occurrence of multi-trait mimicry.

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Shamble, Paul S., Ron R. Hoy, Itai Cohen, and Tsevi Beatus. "Walking like an ant: a quantitative and experimental approach to understanding locomotor mimicry in the jumping spider Myrmarachne formicaria." Proceedings of the Royal Society B: Biological Sciences 284, no. 1858 (July 12, 2017): 20170308. http://dx.doi.org/10.1098/rspb.2017.0308.

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Protective mimicry, in which a palatable species avoids predation by being mistaken for an unpalatable model, is a remarkable example of adaptive evolution. These complex interactions between mimics, models and predators can explain similarities between organisms beyond the often-mechanistic constraints typically invoked in studies of convergent evolution. However, quantitative studies of protective mimicry typically focus on static traits (e.g. colour and shape) rather than on dynamic traits like locomotion. Here, we use high-speed cameras and behavioural experiments to investigate the role of locomotor behaviour in mimicry by the ant-mimicking jumping spider Myrmarachne formicaria , comparing its movement to that of ants and non-mimicking spiders. Contrary to previous suggestions, we find mimics walk using all eight legs, raising their forelegs like ant antennae only when stationary. Mimics exhibited winding trajectories (typical wavelength = 5–10 body lengths), which resemble the winding patterns of ants specifically engaged in pheromone-trail following, although mimics walked on chemically inert surfaces. Mimics also make characteristically short (approx. 100 ms) pauses. Our analysis suggests that this makes mimics appear ant-like to observers with slow visual systems. Finally, behavioural experiments with predatory spiders yield results consistent with the protective mimicry hypothesis. These findings highlight the importance of dynamic behaviours and observer perception in mimicry.

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Stoddard, Mary Caswell. "Mimicry and masquerade from the avian visual perspective." Current Zoology 58, no. 4 (August 1, 2012): 630–48. http://dx.doi.org/10.1093/czoolo/58.4.630.

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Abstract Several of the most celebrated examples of visual mimicry, like mimetic eggs laid by avian brood parasites and palatable insects mimicking distasteful ones, involve signals directed at the eyes of birds. Despite this, studies of mimicry from the avian visual perspective have been rare, particularly with regard to defensive mimicry and masquerade. Defensive visual mimicry, which includes Batesian and Müllerian mimicry, occurs when organisms share a visual signal that functions to deter predators. Masquerade occurs when an organism mimics an inedible or uninteresting object, such as a leaf, stick, or pebble. In this paper, I present five case studies covering diverse examples of defensive mimicry and masquerade as seen by birds. The best-known cases of defensive visual mimicry typically come from insect prey, but birds themselves can exhibit defensive visual mimicry in an attempt to escape mobbing or dissuade avian predators. Using examples of defensive visual mimicry by both insects and birds, I show how quantitative models of avian color, luminance, and pattern vision can be used to enhance our understanding of mimicry in many systems and produce new hypotheses about the evolution and diversity of signals. Overall, I investigate examples of Batesian mimicry (1 and 2), Müllerian mimicry (3 and 4), and masquerade (5) as follows: 1) Polymorphic mimicry in African mocker swallowtail butterflies; 2) Cuckoos mimicking sparrowhawks; 3) Mimicry rings in Neotropical butterflies; 4) Plumage mimicry in toxic pitohuis; and 5) Dead leaf-mimicking butterflies and mantids.

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Dudgeon, Christine L., and William T. White. "First record of potential Batesian mimicry in an elasmobranch: juvenile zebra sharks mimic banded sea snakes?" Marine and Freshwater Research 63, no. 6 (2012): 545. http://dx.doi.org/10.1071/mf11211.

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Various forms of mimicry have been recorded in a large number of marine fishes; however, there have been no records of mimicry for any elasmobranch species. We propose that the distinctly banded neonates of the zebra shark (Stegostoma fasciatum) are Batesian mimics of banded sea snakes (Elapidae). Observations of banded juveniles of S. fasciatum swimming close to the surface strongly resemble banded sea snakes in colour and body form as well as the undulatory swimming movements. Sea snakes are venomous and are known to defend themselves against predators. Although several shark species prey on them, most species appear to avoid sea snakes as prey items. Juvenile S. fasciatum possess a very long, single-lobed caudal fin that remarkably resembles the broad, paddle-like tail of sea snakes. This may be an adaptation enabling this species to mimic sea snakes, at least in the earliest life stages. There is a need for empirical testing of the hypothesis that juvenile S. fasciatum is a true example of Batesian mimicry, but here we provide evidence that suggests this may be the first example of mimicry in an elasmobranch species.

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Goodman, Jonathan R., Andrew Caines, and Robert A. Foley. "Shibboleth: An agent-based model of signalling mimicry." PLOS ONE 18, no. 7 (July 31, 2023): e0289333. http://dx.doi.org/10.1371/journal.pone.0289333.

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Mimicry is an essential strategy for exploiting competitors in competitive co-evolutionary relationships. Protection against mimicry may, furthermore, be a driving force in human linguistic diversity: the potential harm caused by failing to detect mimicked group-identity signals may select for high sensitivity to mimicry of honest group members. Here we describe the results of five agent-based models that simulate multi-generational interactions between two groups of individuals: original members of a group with an honest identity signal, and members of an outsider group who mimic that signal, aiming to pass as members of the in-group. The models correspond to the Biblical story of Shibboleth, where a tribe in conflict with another determines tribe affiliation by asking individuals to pronounce the word, ‘Shibboleth.’ In the story, failure to reproduce the word phonetically resulted in death. Here, we run five different versions of a ‘Shibboleth’ model: a first, simple version, which evaluates whether a composite variable of mimicry quality and detection quality is a superior predictor to the model’s outcome than is cost of detection. The models thereafter evaluate variations on the simple model, incorporating group-level behaviours such as altruistic punishment. Our results suggest that group members’ sensitivity to mimicry of the Shibboleth-signal is a better predictor of whether any signal of group identity goes into fixation in the overall population than is the cost of mimicry detection. Thus, the likelihood of being detected as a mimic may be more important than the costs imposed on mimics who are detected. This suggests that theoretical models in biology should place greater emphasis on the likelihood of detection, which does not explicitly entail costs, rather than on the costs to individuals who are detected. From a language learning perspective, the results suggest that admission to group membership through linguistic signals is powered by the ability to imitate and evade detection as an outsider by existing group members.

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Siu-Hoong, Stephanie Teh. "Myasthenia mimicry." Clinical Medicine 22, Suppl 4 (July 2022): 35. http://dx.doi.org/10.7861/clinmed.22-4-s35.

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Weiss, Rick. "Mutant Mimicry." Science News 137, no. 3 (January 20, 1990): 43. http://dx.doi.org/10.2307/3974398.

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Christensen, Damaris. "Medicinal Mimicry." Science News 159, no. 5 (February 3, 2001): 74. http://dx.doi.org/10.2307/3981862.

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35

Gowthaman, Uthaman, and Veraragavan P. Eswarakumar. "Molecular mimicry." Virulence 4, no. 6 (August 15, 2013): 433–34. http://dx.doi.org/10.4161/viru.25780.

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Soten, Ivana, Natalia Varaksa, and Geoffrey A. Ozin. "Bone Mimicry." Connective Tissue Research 38, no. 1-4 (January 1998): 147. http://dx.doi.org/10.3109/03008209809017031.

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Molloy, Sheilagh. "Innate mimicry." Nature Reviews Microbiology 6, no. 5 (May 2008): 329. http://dx.doi.org/10.1038/nrmicro1903.

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Mitchell, Alison. "Molecular mimicry." Nature Reviews Molecular Cell Biology 3, no. 12 (December 2002): 888. http://dx.doi.org/10.1038/nrm983.

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Tay, N. S. W. T., K. C. Ong, S. Y. Tan, and G. J. L. Kaw. "Tuberculosis mimicry." European Respiratory Journal 26, no. 3 (September 2005): 554–56. http://dx.doi.org/10.1183/09031936.05.00003505.

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Radzikowska, E. "Tuberculosis mimicry." European Respiratory Journal 27, no. 3 (March 1, 2006): 652. http://dx.doi.org/10.1183/09031936.06.00121205.

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Bhatia, M. "Microenvironment Mimicry." Science 329, no. 5995 (August 26, 2010): 1024–25. http://dx.doi.org/10.1126/science.1194919.

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Rennie, John. "Malignant Mimicry." Scientific American 269, no. 3 (September 1993): 34–38. http://dx.doi.org/10.1038/scientificamerican0993-34.

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Wells, J. A. "Hormone Mimicry." Science 273, no. 5274 (July 26, 1996): 449–50. http://dx.doi.org/10.1126/science.273.5274.449.

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Farokhzad, Omid C. "Platelet mimicry." Nature 526, no. 7571 (September 16, 2015): 47–48. http://dx.doi.org/10.1038/nature15218.

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Vinson, V. "Uninhibited Mimicry." Science 327, no. 5964 (January 21, 2010): 395. http://dx.doi.org/10.1126/science.327.5964.395-b.

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Nissen, Poul, Morten Kjeldgaard, and Jens Nyborg. "Macromolecular mimicry." EMBO Journal 19, no. 4 (February 15, 2000): 489–95. http://dx.doi.org/10.1093/emboj/19.4.489.

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FOLBERG, ROBERT, and ANDREW J. MANIOTIS. "Vasculogenic mimicry." APMIS 112, no. 7-8 (July 2004): 508–25. http://dx.doi.org/10.1111/j.1600-0463.2004.apm11207-0810.x.

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Kelley, Laura A., and Susan D. Healy. "Vocal mimicry." Current Biology 21, no. 1 (January 2011): R9—R10. http://dx.doi.org/10.1016/j.cub.2010.11.026.

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Mitchell, Alison. "Molecular mimicry." Nature Reviews Cancer 2, no. 12 (December 2002): 894. http://dx.doi.org/10.1038/nrc956.

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Bucci, Mirella. "Mimicry origins." Nature Chemical Biology 9, no. 8 (July 18, 2013): 468. http://dx.doi.org/10.1038/nchembio.1301.

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