Peer review of: Sexual signaling pattern correlates with habitat pattern in visually ornamented fishes (2020)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
This is an exciting finding within the field of visual ecology showing that spatial elements of 
sexual signals covary with habitat. The data are all about the physical characteristics of 
signals and background, which makes it puzzling that the interpretation focuses so heavily 
on the subjective evaluation of signals by receivers. While the connection to empirical 
aesthetics (a very small field with a Max-Planck Institute) is intriguing, these results fall 
squarely and elegantly within the realm of visual ecology and psychophysics. I understand 
the temptation to connect these results to the authors' recent conceptual paper on 
processing fluency, but I think the connection is far overstated here. The model being 
presented here is analogous to sensory drive: habitat characteristics drive perceptual 
biases. Signals are favored because they address these biases. With these data, it is 
impossible to distinguish between whether signals are favored because they are easier to 
detect by receivers, versus whether they are processed more pleasurably. I found it 
surprising that there wasn't more of a connection to psychophysics and what we already 
know about processing of spatial information. One of the interesting things about spatial 
frequency is that it is processed at multiple levels of the visual system, starting with 
receptive fields in the retina. Spatial frequency sensitivity is also famously sensitive to the 
early visual environment, providing a compelling mechanism for the tuning of frequency 
sensitivity to the local visual environment.It is possible that these spatial frequencies are 
more detectable or more attractive because they're parsed more easily in a given 
environment. But visual systems function by detecting contrast, and matching spatial 
frequency is a common feature of camouflage and mimicry. Indeed, I think the most 
parsimonious evolutionary explanation for this pattern is that the spots of male darters have 
evolved to minimize conspicuousness to color-insensitive fish predators. Colors thereby 
stand out for conspecific females while predators see a homogeneous background. 
It is worth revisiting some of the earlier literature on visual ecology, from Fleishman's work 
on temporal-frequency contrast in courtship displays to Changizi's work on written symbols 
and topological patterns in natural scenes to Justin Marshall's extensive work on 
communication and camouflage in reef fish. Rosenthal's Annual Review on visual 
communication talks about spatial frequency matching in camouflage. Finally, this work 
presents an exciting analogy to auditory frequency and pattern tuning and 
habitat/eavesdropper effects on signal/receiver evolution. That literature, grounded in 
psychophysics and neurophysiology, provides more promising grounds for future research 
building off this data set than does the interesting, but tenuously related, field of empirical 
aesthetics. The one substantive comment I would make is to reanalyze the data in terms of 
spatial frequency contrast and testing for contrast differences across the spatial-frequency 
spectrum. This will allow you to test whether there are spatial frequencies where darter 
signals stand out against the background. This will then provide direct predictions for future 
studies on the spatial-frequency sensitivity of receivers. To summarize, this is an interesting 
and important study that could make a substantial impact with some scholarly revision and 
additional analysis. 
 
 

 
Reviewer #2: 
Remarks to the Author: 
I really enjoyed reading this manuscript. In this manuscript, the authors tested the idea that 
what makes a particular signal attractive is based in what the sensory system is primed to 
see. This idea has been around for a while in the area of human perception of art and even 
in the way that letters are formed. The idea is that animals are very efficient at detecting 
particular patterns that are common in their environment. Things like art (in case of 
humans) or male secondary sex characters (in the case of the darters at hand) might have 
elements of their color patterns that reflect this bias. 
 
To test this, the authors took pictures of a number of male and female darter species that 
are widespread in their placement in the darter phylogeny. They took pictures of males and 
females below the second dorsal fin. They also took pictures of the environments in which 
the fish are found. Some are found in rocky areas, others in detritus, others over sandy 
substrate. 
 
They then performed an analysis involving the fourier transform. I will admit that I do not 
fully understand this method. I am not fully clear on what the 'slope of the Fourier power 
spectrum' represents. This should be spelled out a little bit more clearly in the methods. 
 
They then performed Anovas on the slopes. They also examined the relationships between 
the Flourier slope of habitats and darter color patterns, but for some reason they used an 
MCMCglmm approach. I don't understand why they didn't use a normal linear regression 
approach. My issue with the MCMCglmm is that you usually have to specify some type of 
underlying distribution. We don't know what that is in this case. I looked in the 
supplemental information but did not see it. The reason I am curious about this is because 
the confidence limits on line 133 the confidence limits for the slope gets super close to zero 
(1.5x10^-17). The value on this is pretty small (5 X10-3), but the upper limit on the 
confidence limit is 0.0252. This suggests that confidence limit is constrained to not go below 
zero. If this is the case, then this result needs to be reinterpreted. Again, we need more 
detail on the distribution of the MCMCglmm. 
 
More generally, I found myself wondering whether matching the energy spectrum (i.e., 
congruence between the two fourier slopes) should make one attractive or whether it should 
make one cryptic. If we had found the opposite pattern (i.e., a good match for females, but 
not for males), then would we be interpreting this in the light of crypsis. 
 
I also had a bit of difficulty in interpreting figures 3 and 4. 
 
My recommendation is that the authors make this paper a bit more reader friendly. Many of 
the folks reading this will be coming from an ecology and evolution perspective, so they are 
going to need some hand holding on the fourier analysis section. What is a fourier 
transform? I have done these in the past, but I would have problems explaining them. Lots 
of folks will have never done these. So a bit of hand holding in the supplemental materials 
would be appreciated. 

 
If the authors can fix these issues, then I think that this will make for a very nice paper in 
Nature Communications. 
 
 
 
Reviewer #3: 
Remarks to the Author: 
The manuscript “NCOMMS-19-24571 - Sexual signals of fish species mimic the spatial 
statistics of their habitat: evidence for processing bias in animal signal evolution” deals with 
the similarity of Fourier slopes between male darter fish and their habitat to test a signal 
drive hypothesis of evolutionary biology. It is a very well-written manuscript and a well-
controlled study. However, in the current state the justification of the exact research 
question and its novelty is not perfectly clear to me. Although I believe (but not know) that 
it is the first study that uses image processing methods to test a theory on sexual selection, 
it seems to disregard related literature from psychology, for example using human face 
stimuli. Therefore, I suggest the revision of the respective paragraphs in the introduction (is 
indicated below). I am also not contented that (only) fish species are considered in this 
study. Analyses of other groups of species would be much appreciated to strengthen the 
drawn conclusions. Furthermore, the result section needs to be revised because in the 
current state the analyses and their statistical indices are not clear and might be improved. 
Furthermore, some methodological aspects are not clear in the current state of the 
manuscript and should be addressed. Additionally, the discussion section doesn’t deal much 
with the actual data presented but rather more general with the hypothesis tested. In my 
opinion, the current data and its limitations should be discussed in more detail. Based on 
the more detailed comments below, I suggest a major revision of the manuscript. 
 
It should be noted that I read the manuscript in the order any ‘Nature communications’ 
reader would read it (Abstract – Introduction – Results – Discussion – Methods – 
Supplemental) and, therefore, some of my comments might be overridden after reading 
later sections (esp. Methods). However, it is an indication that information is missing at a 
point where it is necessary. So the authors should revise the respective sentences, even 
when it is described in detail at later sections. 
 
Line 31: The reference is not numbered. 
 
Lines 63ff: “In parallel, other studies have shown that…”. Please cite the studies you are 
referring to. 
 
Line 68: “hypothesize”  hypothesized 
 
Line 71f: Although I agree that in most studies natural scenes were not considered in their 
diversity, the current sentence seems to claim that no researcher ever thought about 
different sceneries and habitats. I’d prefer a less absolute wording. 
 
Line 80ff and generally to the research question and hypothesis: For me, it is not clear 

whether the current study is the first attempt to test the hypothesis stated here. What is 
about, for example, the relation of the characteristics of human faces and their assumed 
natural habitat? In fact, photographs of human faces have different statistical properties 
than natural scenes (Redies, Hänisch, Blickhan, & Denzler, 2007). Further and more 
importantly, how does this theory/hypothesis deals with the fact that several different-
looking animals live in the same habitat (even when considering only animals that use 
visual cues for mate attraction)? Additionally, the authors may also refer to other perception 
studies, e.g. on fore- and background segregation and sensory competition. So far, I also 
do not understand why the properties of the entire habitat rather than particular 
(rewarding) elements in it should correlate with the visual cues of the fish. I’d appreciate a 
more detailed explanation and justification of the research question and hypothesis. 
However, I should note that I am not very familiar with sensory drive models and related 
hypothesis. Furthermore, I was surprised that fish species were selected as the target (and 
the only one). At one point, it should be described whether and how visual perception of fish 
(in water) differ from other animals (on land) and whether this has an effect on the used 
measure. To allow a more universal conclusion, the authors may consider analysing data 
also from other species’ groups (preferably from land). Overall, the justification of the 
research question and hypothesis is not entirely clear and satisfying to me. 
 
Line 106f: The horizon line is represented by high rather than low spatial frequencies. The 
authors may rather refer to the change in luminance between sky and foreground for 
example. 
 
Line 111f and elsewhere: The authors may also refer to related work of other groups and 
research foci, such as work on visual discomfort and Fourier slope (e.g., Juricevic, Land, 
Wilkins, & Webster, 2010). Furthermore, although I agree with the appropriateness of the 
Fourier slope as the selected measure, it should be considered to analyse further statistical 
properties (and if decided against it, it should be briefly stated why the Fourier slope is 
considered the only relevant measure). 
 
Line 117ff: I don’t understand the indications for the statistical tests and therefore I am not 
able to approve their correctness. If that refers to an ANOVA, the statistical indices should 
be indicated correctly. Further, the p-values should be indicated as p < .001 or similar, 
rather than “p = 2e-16”. I am also not sure why sex seems to be not included in the ANOVA 
as a factor. Rather, it seems that two different ANOVAs were calculated for the two sexes. 
The indications for the statistical tests should be revised and if appropriate the statistical 
analyses should be redone including all factors in one analysis. 
 
Line 118ff: If “Overall, males had a higher slope than females…” refers to a main effect in 
the calculated ANOVA, this and the respective statistical indices should be indicated. If not 
(which might be indicated by “this difference was significant in 5 out of 10 species”), it 
shouldn’t be stated that “overall” males had a higher slope. In general, the description of 
the results is not precise and understandable. 
 
Line 123: It is not clear what “phylogeny” refers here to. It is also not clear to me, why sex 
and species is not entered to the model as fixed factors. 

 
Lines 128ff: The authors may reconsider the numbers of decimal places. 
 
Line 129f: “We did not find a strong effect of the…”  I’d prefer: “We found a rather small 
influence of…” since the authors did found a significant effect. 
 
Line 135: For the sake of completeness, the statistical indices for that alternative model 
should be stated. 
 
Line 148ff: This paragraph might be moved to the introduction because no current data are 
discussed here while it rather discusses the research gap the study aims to fill. If the 
authors prefer to keep it in the discussion, it should be shortened and the current data 
should be integrated. 
 
Lines 161ff: Again, this and the following paragraph do not discuss the current findings but 
rather (partly redundantly) describes previous research. They should be moved to the 
introduction, or shortened and connected to the current data. 
 
Line 191ff and elsewhere: Although I am much aware that it is not good manners to 
suggest own studies as a reviewer, I’d like to draw the authors’ attention to studies on 
human faces in front of patterns with different Fourier slope backgrounds (e.g., Menzel, 
Hayn-Leichsenring, Langner, Wiese, & Redies, 2015; Menzel, Hayn-Leichsenring, Redies, 
Németh, & Kovács, 2017; Wu, Xu, Dayan, & Qian, 2009). I am not asking for being cited 
but would like to point out that there exist studies on the perception of the similarity of 
statistical properties of backgrounds (which might be interpreted as ‘habitat’ in the context 
of perceiving and evaluating the target in the foreground) and the targets in the foreground. 
Furthermore, within this context, the authors may also discuss further perceptual 
mechanisms, such as sensory competition and (short-time) adaptation. 
 
Line 207: Because of its importance to the current study, I’d prefer a reference to original 
data on the Fourier slope in terrestrial compared to aquatic environments, rather than 
referring to an overview book. Also for aquatic environments, it should be explicitly stated 
whether this difference refers to photographs made from above or below the water surface. 
Further, I am surprised that the absolute numbers of the Fourier slope retrieved for the 
habitats and fish in the current data set are not discussed in relation to the fish, and to 
other image categories analysed in previous studies. The slopes of the fish habitats are 
rather steep compared to those of natural scenes found in previous studies. Also, the slopes 
of the fish are even steeper (and much likely significantly different from their habitats), 
which is a bit surprising when looking at the images because I can see a lot of fine detail on 
the fish surface. I am wondering whether the curve of the power spectrum is really a 
straight line for the fish. Similar to figure 2, the authors should include example curves for 
the fish. The authors should also make clear why they think the correlation between fish 
and habitat slope is more informative than comparing the slopes directly. Relatedly, the 
authors may revise their title and abstract to adjust the conclusion to their data. Since the 
conclusion is made based on a correlation and not a direct comparison, in my opinion, one 
cannot say that the fish “mimic” (title) the statistics of their habitat, and that these 

statistics are “compared” (abstract). 
 
Discussion in general: Overall, the current results are not discussed in much detail. I 
suggest, revising the discussion to reduce redundancy with the introduction and to address 
the current data in more detail as well as the limitations of the study (e.g., in statistical 
terms a quite low number of habitats and fish species which are correlated; focus on only 
one particular group of fish species’; focus only on aquatic animals; focus only on Fourier 
slope etc.). 
 
Line 271ff: Example images of the cropped and adapted versions of the fish photographs 
would be very helpful to follow the technical paragraphs and to interpret the Fourier slopes 
obtained. Please provide at least one example image that was used to measure the Fourier 
slope. 
 
Line 274: Please add a break/paragraph to separate the description for fish and habitat 
photographs. 
 
Line 276f: “Since the size of the habitat images is greater than the size of the darter’s flank, 
using a larger box size reduces variability in lower frequency coefficients.”  I don’t get that 
sentence. Please also explain why different image size is not a problem for your analysis of 
Fourier slope (usually it does affect the slope). The “Additionally” at the beginning of the 
following sentence makes no sense to me, because the previous one didn’t explain why 
different image sizes are no problem. 
 
Line 281ff: Related to the previous comment, I don’t understand why the same range of 
frequencies is considered for habitat and fish images which differed in size. When focusing 
on only a subset of frequencies for a larger image, information about the lower spatial 
frequencies are lost and the two slopes are not comparable. This should be explained and 
possibly changed. 
 
Line 287ff: Okay, I see that the authors tried to match the analyses by adjusting the bins. 
However, I am not sure whether it solves the problem of differing image sizes. I do not 
understand why it was worked with different image sizes at all. This should be made more 
clear. I’d suggest identical image sizes and analysis procedures for both image types. Also, 
the sentence in line 286f and the following one seem to contradict each other. When only 
frequencies between 10 and 110 were included, how can the binning include the frequencies 
10 to 200? This is not clear. 
 
Line 394ff: As stated above, it is not clear why not all relevant factors are included in one 
ANOVA. 
 
Line 299ff: I am not a statistician but in my understanding phylogeny should be included as 
a fixed rather than random factor because one might expect systematic and predictable 
influences of phylogeny (as for example sex which is usually entered as a fixed factor in 
such models). Please also explain how this information is entered in the model. So far, I 
cannot imagine how a phylogenetic tree can be entered to the model. 

 
Lines 305ff: I tried to access the slopes for the images but couldn’t find a respective file in 
the repository. Please check for completeness. Note that I did not check the python scripts 
for correctness or completeness. 
 
Figure 1: Example images of the female fish would be appreciated. 
 
Figure 2: Although I am aware that the presented images are examples, they may 
represent an important flaw: the vertical angle is different. On the top image one can see a 
“horizon line” and rays, while on the bottom image there is only ground depicted. However, 
since a large number of images was used to characterize the habitats, this might be no big 
problem. However, the authors should check, whether the angle systematically differed 
between habitats. 
 
 
Dr. Claudia Menzel, University of Koblenz-Landau, Germany. 
 
 
Referred references: 
Juricevic, I., Land, L., Wilkins, A., & Webster, M. A. (2010). Visual discomfort and natural 
image statistics. Perception, 39(7), 884–899. https://doi.org/10.1068/p6656 
 
Menzel, C., Hayn-Leichsenring, G. U., Langner, O., Wiese, H., & Redies, C. (2015). Fourier 
power spectrum characteristics of face photographs: Attractiveness perception depends on 
low-level image properties. Plos One, 10(4), e0122801. 
https://doi.org/10.1371/journal.pone.0122801 
 
Menzel, C., Hayn-Leichsenring, G. U., Redies, C., Németh, K., & Kovács, G. (2017). When 
noise is beneficial for sensory encoding: Noise adaptation can improve face processing. 
Brain and Cognition, 117, 73–83. https://doi.org/10.1016/j.bandc.2017.06.006 
 
Redies, C., Hänisch, J., Blickhan, M., & Denzler, J. (2007). Artists portray human faces with 
the Fourier statistics of complex natural scenes. Network: Computation in Neural Systems, 
18(3), 235–248. https://doi.org/10.1080/09548980701574496 
 
Wu, J., Xu, H., Dayan, P., & Qian, N. (2009). The role of background statistics in face 
adaptation. The Journal of Neuroscience, 29(39), 12035–12044. 
https://doi.org/10.1523/JNEUROSCI.2346-09.2009