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Warning coloration deters predators from attacking prey that are defended, usually by being distasteful, toxic, or otherwise costly for predators to pursue and consume. Predators may have an innate response to warning colors or learn to associate them with a defense through trial and error. In general, predators should select

Warning coloration deters predators from attacking prey that are defended, usually by being distasteful, toxic, or otherwise costly for predators to pursue and consume. Predators may have an innate response to warning colors or learn to associate them with a defense through trial and error. In general, predators should select for warning signals that are easy to learn and recognize. Previous research demonstrates long-wavelength colors (e.g. red and yellow) are effective because they are readily detected and learned. However, a number of defended animals display short-wavelength coloration (e.g. blue and violet), such as the pipevine swallowtail butterfly (Battus philenor). The role of blue coloration in warning signals had not previously been explicitly tested. My research showed in laboratory experiments that curve-billed thrashers (Toxostoma curvirostre) and Gambel's quail (Callipepla gambelii) can learn and recognize the iridescent blue of B. philenor as a warning signal and that it is innately avoided. I tested the attack rates of these colors in the field and blue was not as effective as orange. I concluded that blue colors may function as warning signals, but the effectiveness is likely dependent on the context and predator.

Blue colors are often iridescent in nature and the effect of iridescence on warning signal function was unknown. I reared B. philenor larvae under varied food deprivation treatments. Iridescent colors did not have more variation than pigment-based colors under these conditions; variation which could affect predator learning. Learning could also be affected by changes in appearance, as iridescent colors change in both hue and brightness as the angle of illuminating light and viewer change in relation to the color surface. Iridescent colors can also be much brighter than pigment-based colors and iridescent animals can statically display different hues. I tested these potential effects on warning signal learning by domestic chickens (Gallus gallus domesticus) and found that variation due to the directionality of iridescence and a brighter warning signal did not influence learning. However, blue-violet was learned more readily than blue-green. These experiments revealed that the directionality of iridescent coloration does not likely negatively affect its potential effectiveness as a warning signal.
ContributorsPegram, Kimberly Vann (Author) / Rutowski, Ronald L (Thesis advisor) / Hoelldobler, Berthold (Committee member) / Liebig, Juergen (Committee member) / McGraw, Kevin (Committee member) / Smith, Brian H. (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that operate within those structures. In this work, published mouse experimental data were synthesized to develop an extensible, open-source platform for

The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that operate within those structures. In this work, published mouse experimental data were synthesized to develop an extensible, open-source platform for modeling the mouse main olfactory bulb and other brain regions. A “virtual slice” model of a main olfactory bulb glomerular column that includes detailed models of tufted, mitral, and granule cells was created to investigate the underlying mechanisms of a gamma frequency oscillation pattern (“gamma fingerprint”) often observed in rodent bulbar local field potential recordings. The gamma fingerprint was reproduced by the model and a mechanistic hypothesis to explain aspects of the fingerprint was developed. A series of computational experiments tested the hypothesis. The results demonstrate the importance of interactions between electrical synapses, principal cell synaptic input strength differences, and granule cell inhibition in the formation of the gamma fingerprint. The model, data, results, and reproduction materials are accessible at https://github.com/justasb/olfactorybulb. The discussion includes a detailed description of mechanisms underlying the gamma fingerprint and how the model predictions can be tested experimentally. In summary, the modeling platform can be extended to include other types of cells, mechanisms and brain regions and can be used to investigate a wide range of experimentally testable hypotheses.
ContributorsBirgiolas, Justas (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Committee member) / Smith, Brian H. (Committee member) / Neisewander, Janet (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2019