Undergraduate Honors Theses

Thesis Defended

Spring 2018

Document Type


Type of Thesis

Departmental Honors


Ecology and Evolutionary Biology

First Advisor

Dr. Andrew Martin

Second Advisor

Dr. Barbara Demmig-Adams

Third Advisor

Dr. Susan Hendrickson


Animals use vision for many important ecological processes including foraging, avoiding predation, finding a mate, and navigation. Mathematical models are often used to predict contrast detection for a given animal visual system to investigate color and color vision in nature. One commonly used model is the receptor noise limited (RNL) model that assumes noise in the photoreceptors is the limiting factor for discrimination between objects. This model was developed for color vision, but has since been adapted to predict achromatic discrimination thresholds. However, the validity of using the RNL model for achromatic contrast discrimination has never been thoroughly investigated. Furthermore, despite significant advances in the understanding of color vision of reef fish, very little is known about their luminance vision. The aim of this study was to determine luminance detection threshold in Picasso triggerfish (Rhinecanthus aculeatus) in order to assess the legitimacy of using this model to predict luminance vision and to better understand how this species, as well as other similar species, perceives its environment. This was investigated by conditioning R. aculeatus to peck at achromatic spots on an achromatic background of varying contrast values. The success of the fish to find the spots was recorded and analyzed. The thresholds found ranged from 4.84 to 10.64 Michelson contrast depending on the scenario of contrast. The thresholds found appeared to be extremely context dependent, which may be the result of common scenarios found in their environment. Although the results are not directly applicable to the RNL model, the use of this model to predict luminance discrimination thresholds appears to be applicable to the detectability of a large-size stimulus against a uniform background. By understanding this threshold, a better understanding of visual ecology can be obtained, that may contribute to a more accurate interpretation of animal behavior.

Available for download on Tuesday, April 12, 2022

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