DOI: 10.5061/dryad.qfttdz0ns
title: Data from: how to generate and test hypotheses about colour: insights from half a century of guppy research

description: Colouration facilitates evolutionary investigations in nature because the
 interaction between genotype, phenotype and environment is relatively
 accessible. In a landmark set of studies, Endler addressed this complexity
 by demonstrating that the evolution of male Trinidadian guppy colouration
 is shaped by the local balance between selection for mate attractiveness
 versus crypsis. This became a textbook paradigm for how antagonistic
 selective pressures may determine evolutionary trajectories in the wild.
 Recent studies have, however, challenged the generality of this paradigm.
 Here we respond to these challenges by reviewing five important yet
 underappreciated factors that contribute to colour pattern evolution: (1)
 inter-population variation in female preference, (2) differences in how
 predators versus conspecifics view males, (3) biased assessment of
 pigmentary versus structural colouration, (4) the importance of accounting
 for multi-species predator communities, and (5) the importance of
 considering the multivariate genetic architecture and multivariate context
 of selection. We elaborate upon these points specifically in relation to
 two papers that illustrate the challenges raised by the recent body of
 work on guppies. More broadly, we emphasise the depth of consideration
 necessary for testing evolutionary hypotheses using complex multi-trait
 phenotypes such as guppy colour patterns.
description: For more detail, refer Notes.txt file.
description: # Data from: how to generate and test hypotheses about colour: insights
 from half a century of guppy research | File Name | Data Summary | |
 --------- | ------------ | | Spot area and number.csv | average area in
 mm<sup>2</sup> of orange, black, and yellow color on body,
 body area, and number of spots of each color per fish. | |
 Colormesh\_data.csv | raw RBG values for each pixel sampled by colormesh.
 | | Aripo1.s1.4.5.78.bmp | group photo for Aripo 1 population (low
 predation). | | Aripo1.s2.4.5.78.bmp | " | | Aripo1.s3.4.5.78.bmp |
 " | | Aripo1.s4.4.5.78.bmp | " | | Aripo6.s1.2.3.78.bmp | group
 photo for Aripo 6 population (high predation). | | Aripo6.s2.02.03.78.bmp
 | " | | Aripo6.s3.02.03.78.bmp | " | | Arima1.s1.16.7.75.bmp |
 group photo for Arima 1 population (high predation). | |
 Arima1.s2.16.7.75.bmp | " | | Arima5.12.07.75.bmp | group photo for
 Arima 5 population (low predation). | ### A description of column headings
 #### Spot area and number.csv * pop = population * River = river, Aripo or
 Arima * pred = predation regime (low predation or high predation) *
 black\_avg = average area (mm<sup>2</sup>) of black spots on
 that fish * orange\_avg = average area (mm<sup>2</sup>) of
 orange spots on that fish * yellow\_avg = average area
 (mm<sup>2</sup>) of yellow spots on that fish (not used in
 analysis) * black\_N = number of black spots on that fish * orange\_N =
 number of orange spots on that fish * yellow\_N = number of yellow spots
 on that fish (not used in analysis) * Body\_area = area
 (mm<sup>2</sup>) of body + tail fin #### Colormesh\_data.csv *
 photo = fish measured. population.photograph.fish (A1=Aripo1, A6=Aripo6,
 Arima1=Arima1, Arima5=Arima5). "s1" indicates photo s1 (or s2,
 s3, etc). Number indicates fish counting from upper right corner, moving
 down the column, then top of next column to the right, etc. * unwrp =
 unwarped photographed actually used to measure RGB values in colormesh. *
 r\_interior1 = red value of first pixel (0-1) * g\_interior1 = green value
 of first pixel (0-1) * b\_interior1 = blue value of first pixel (0-1) *
 ... * ... * r\_perimeter1 = red value of pixel at first landmark digitized
 to outline the fish. * ... * ... * ... * b\_perimeter58 = blue value of
 pixel at last (58th) landmark digitized to outline fish.