The natural history of organisms can have major effects on the tempo and mode of evolution, but few examples show how unique natural histories affect rates of evolution at macroevolutionary scales. European plethodontid salamanders (Plethodontidae: Hydromantes) display a particular natural history relative to other members of the family. Hydromantes commonly occupy caves and small crevices, where they cling to the walls and ceilings. On the basis of this unique and strongly selected behavior, we test the prediction that rates of phenotypic evolution will be lower in traits associated with climbing. We find that, within Hydromantes, foot morphological traits evolve at significantly lower rates than do other phenotypic traits. Additionally, Hydromantes displays a lower rate of foot morphology evolution than does a nonclimbing genus, Plethodon. Our findings suggest that macroevolutionary trends of phenotypic diversification can be mediated by the unique behavioral responses in taxa related to particular attributes of their natural history.

Marine turtles are visual animals, yet we know remarkably little about how they use this sensory capacity. In this study, our purpose was to determine whether loggerhead turtles could discriminate between objects on the basis of color. We used light-adapted hatchlings to determine the minimum intensity of blue (450 nm), green (500 nm), and yellow (580 nm) visual stimuli that evoked a positive phototaxis (the phototaxis "threshold" [pt]). Juvenile turtles were later trained to associate each color (presented at 1 log unit above that color's pt) with food, then to discriminate between two colors (the original rewarded stimulus plus one of the other colors, not rewarded) when both were presented at 1 log unit above their pt. In the crucial test, turtles were trained to choose between the rewarded and unrewarded color when the colors varied in intensity. All turtles learned that task, demonstrating color discrimination. An association between blue and food was acquired in fewer trials than between yellow and food, perhaps because some prey of juvenile loggerheads in oceanic surface waters (jellyfishes, polyps, and pelagic gastropods) are blue or violet in color.

To quantify the performance of experimental ocean current turbines (OCTs) during offshore testing, important performance metrics are presented along with a proposed sensor suite and the mathematical relationships that can be used to calculate them. A numerical simulation of an OCT and numeric models of the selected sensors are utilized to synthesize measurements which are used to calculate relative free stream flow velocity, electric power output, total system efficiency, shaft power, and rotor efficiency. By evaluating the calculated performance metrics, both with and without sensor limitations, the impact of the sensor limitations on the calculated performance metrics are evaluated. The impact of averaging times on the repeatability of performance calculations are also evaluated for several operating conditions to guide offshore testing requirements. It is found that for a 2 m significant wave height the selected sensor system increases the standard deviation of the calculated performance metrics for 1 min averages and an operating depth of 10 m by 5-20%. For a depth of 20 m the OCT performance is more consistent and the sensors increase the variability of the calculated performance metrics by between 30-50% for 1 min averages. For the same significant wave height and a depth of 10 m the standard deviation of the 1 min averaged sensor measured system and rotor efficiencies for are shown to range from 0.9 and 3.3% of their mean value. However this can be decreased to a 0.13 and 0.52% if the operating depth is decreased to 10 m and the averaging time is increased to 10 min.