Male displaying wing during courtship. |
For the next week I’ll give a presentation
on the work of fruit fly WIPs I’ve been doing. Also Anais and I will show you
the video footage of male mating preference on both wild type LHm and Androchrome
females. Hope to hear your thoughts and advises.
To continue with the theme of WIPs, I think
we can read this paper Erik suggested earlier about the new tool for studying
animal colour patterns and the possible application on our studies. Fika will
be served!
Summary:
1. The information in animal colour
patterns plays a key role in many ecological interactions; quanitification
would help us to study them, but this is problematic. Comparing patterns using
human judgement is subjective and inconsistent. Traditional shape analysis is
unsuitable as patterns do not usually contain conserved landmarks. Alternative
statistical approaches also have weaknesses, particularly as they are generally
based on summary measures that discard most or all of the spatial information
in a pattern.
2. We present a method for quantifying the
similarity of a pair of patterns based on the distance transform of a binary
image. The method compares the whole pattern, pixel by pixel, while being
robust to small spatial variations among images.
3. We demonstrate the utility of the
distance transform method using three ecological examples. We generate a
measure of mimetic accuracy between hoverflies (Diptera: Syrphidae) and wasps
(Hymenoptera) based on abdominal pattern, and show that this correlates
strongly with the perception of a model predator (humans). We calculate similarity
values within a group of mimetic butterflies and compare this with proposed
pairings of Müllerian comimics.
4. Finally, we characterise variation in
clypeal badges of a paper wasp (Polistes dominula) and compare this with
previous measures of variation.
While our results generally support the
findings of existing studies that have used simpler ad hoc methods for
measuring differences among patterns, our method is able to detect more subtle
variation and hence reveal previously overlooked trends.
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