The normalized segment classification model: A new tool to compare spectral reflectance curves.

Color patterns are complex traits under selective pressures from conspecifics, mutualists, and antagonists. To evaluate the salience of a pattern or the similarity between colors, several visual models are available. Color discrimination models estimate the perceptual difference between any two colors. Their application to a diversity of taxonomic groups has become common in the literature to answer behavioral, ecological, and evolutionary questions. To use these models, we need information about the visual system of our beholder species. However, many color patterns are simultaneously subject to selective pressures from different species, often from different taxonomic groups, with different visual systems. Furthermore, we lack information about the visual system of many species, leading ecologists to use surrogate values or theoretical estimates for model parameters.Here, we present a modification of the segment classification method proposed by Endler (Biological Journal of the Linnean Society, 1990 41, 315-352): the normalized segment classification model (NSC). We explain its logic and use, exploring how NSC differs from other visual models. We also compare its predictions with available experimental data.Even though the NSC model includes no information about the visual system of the receiver species, it performed better than traditional color discrimination models when predicting the output of some behavioral tasks. Although vision scientists define color as independent of stimulus brightness, a likely explanation for the goodness of fit of the NSC model is that its distance measure depends on brightness differences, and achromatic information can influence the decision-making process of animals when chromatic information is missing.Species-specific models may be insufficient for the study of color patterns in a community context. The NSC model offers a species-independent solution for color analyses, allowing us to calculate color differences when we ignore the intended viewer of a signal or when different species impose selective pressures on the signal.

Learning in two butterfly species when using flowers of the tropical milkweed Asclepias curassavica: No benefits for pollination.

PREMISE OF THE STUDY: The ability of insect visitors to learn to manipulate complex flowers has important consequences for foraging efficiency and plant fitness. We investigated learning by two butterfly species, Danaus erippus and Heliconius erato, as they foraged on the complex flowers of Asclepias curassavica, as well as the consequences for pollination. METHODS: To examine learning with respect to flower manipulation, butterflies were individually tested during four consecutive days under insectary conditions. At the end of each test, we recorded the number of pollinaria attached to the body of each butterfly and scored visited flowers for numbers of removed and inserted pollinia. We also conducted a field study to survey D. erippus and H. erato visiting flowers of A. curassavica, as well as to record numbers of pollinaria attached to the butterflies' bodies, and surveyed A. curassavica plants in the field to inspect flowers for pollinium removal and insertion. KEY RESULTS: Learning improves the ability of both butterfly species to avoid the nonrewarding flower parts and to locate nectar more efficiently. There were no experience effects, for either species, on the numbers of removed and inserted pollinia. Heliconius erato removed and inserted more pollinia than D. erippus. For both butterfly species, pollinium removal was higher than pollinium insertion. CONCLUSION: This study is the first to show that Danaus and Heliconius butterflies can learn to manipulate complex flowers, but this learning ability does not confer benefits to pollination in A. curassavica.

Out of the blue: the spectral sensitivity of hummingbird hawkmoths.

The European hummingbird hawkmoth Macroglossum stellatarum is a diurnal nectar forager like the honeybee, and we expect similarities in their sensory ecology. Using behavioural tests and electroretinograms (ERGs), we studied the spectral sensitivity of M. stellatarum. By measuring ERGs in the dark-adapted eye and after adaptation to green light, we determined that M. stellatarum has ultraviolet (UV), blue and green receptors maximally sensitive at 349, 440 and 521 nm, and confirmed that green receptors are most frequent in the retina. To determine the behavioural spectral sensitivity (action spectrum) of foraging moths, we trained animals to associate a disk illuminated with spectral light, with a food reward, and a dark disk with no reward. While the spectral positions of sensitivity maxima found in behavioural tests agree with model predictions based on the ERG data, the sensitivity to blue light was 30 times higher than expected. This is different from the honeybee but similar to earlier findings in the crepuscular hawkmoth Manduca sexta. It may indicate that the action spectrum of foraging hawkmoths does not represent their general sensory capacity. We suggest that the elevated sensitivity to blue light is related to the innate preference of hawkmoths for blue flowers.