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Seafinding in sea turtle hatchlings

Seafinding in sea turtle hatchlings. Seafinding in sea turtle hatchlings. Silhouettes, Beach Slope, and Light Cues . When hatchlings emerge from their nests in the dunes of the beach, what information could they use to determine the oceanward direction?.

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Seafinding in sea turtle hatchlings

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  1. Seafinding in sea turtle hatchlings

  2. Seafinding in sea turtle hatchlings

  3. Silhouettes, Beach Slope, and Light Cues When hatchlings emerge from their nests in the dunes of the beach, what information could they use to determine the oceanward direction? • Towards land, the dunes and associated vegetation form a dark silhouette. • The beach slopes down in the direction of the water. • Ambient light is reflected from the ocean, making that region brighter. http://www.unc.edu/depts/oceanweb/turtles/beach1.html

  4. Seafinding experiments • Hatchlings oriented down-slope when no light was present. If light was present and the horizon around the tank was level, hatchlings ignored the slope cues (implying that the slope cues aren't as important). • Hatchlings oriented to the side of the arena where the intensity of light was the brightest. • Hatchlings oriented away from dark silhouettes that were placed close to the horizon. Salmon, M., Wyneken, J., Fritz, E., and Lucas, M. (1992). Seafinding by hatchling sea turtles: Role of brightness, silhouette, and beach slope as orientation cues. Behaviour 122, 56-77. http://www.unc.edu/depts/oceanweb/turtles/beach2.html

  5. Neural control architectures Simple Braitenberg vehicle in sufficient for sea-finding problem turtles eye view of natural visual scenes

  6. Turtles Eye View of Natural Visual Scenes From: Witherington and Martin 1996

  7. Seafinding in sea turtle hatchlings

  8. Simple cross-wired solution is not robustunder natural conditions • Problems: • orders-of-magnitude variation in background intensity • gradients too weak (resulting radius of curvature r too large) • spatial and temporal input variability (scene structure, “noise”) r IL IR • Solutions: • sensory input  “internal model”  motor output • optimal spatiotemporal filtering of visual input velL velR

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