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Dear Dr. Wang,
All changes solicited from the reviewer were done. So, I am very pleased to say that your paper " Life history response of Echinops gmelinii Turcz. to variation in the rainfall pattern in a temperate desert " is accepted for publication in the PeerJ. Once again congratulations!
Thank you for submitting your work to PeerJ.
Yours sincerely,
Gabriele Casazza
[# PeerJ Staff Note - this decision was reviewed and approved by Dezene Huber, a PeerJ Section Editor covering this Section #]
The reviewer finds the paper improved and he was able to replicate the analyses. Nevertheless, he still has found some issues. He also supplied an annotated manuscript with some tips. So, I encourage you to carefully address these problems and to improve the manuscript according to tips of reviewers. Please, respond point-to-point to the comments of the reviewer.
Once again, thank you for submitting your manuscript to PeerJ and we look forward to receiving your revision.
Sincerely,
Gabriele Casazza
The basic reporting is good. There are minor problems of English usage and odd phrasing in the manuscript. I hope the editors at PeerJ can catch some of these. Overall it is fairly well written. Please see comments on the pdf for more notes.
Good.
I was able to recreate the ANOVA results reported in table 2 with SPSS.
Thank you for replying to my earlier comments and fixing the table with the updated values.
From a statistical perspective, I am somewhat concerned about one issue. There are five combinations of the two treatments (amount and frequency) that are completely missing due to the death of all the plants in those treatment combinations. The number of treatment combinations that were excluded due to missingness should be explicitly mentioned in the results. These missing levels of the interaction can cause large issues when using ANOVA with a fully factorial design.
I recommend the authors conduct a simple ANOVA without the interaction effects between precipitation amount and frequency and confirm that the significance of the main effects are unaffected.
If the main effects change substantially this may indicate some problems and it may be safer not to conduct the full factorial ANOVA. If the results remain the same, then there may not be an issue--although I am somewhat skeptical of the interaction effects nonetheless.
Thank you for considering my earlier comments.
Dear Dr. Wang,
The reviewer finds the paper strongly improved. Nevertheless, he could not reproduce the results you obtained using the methods described in the text. This suggests that something in methods description or in raw data is wrong. You will receive an email with the test performed by the reviewer as soon as possible.
I encourage you to address this problem and to improve the manuscript according to tips of reviewers. Please, respond point-to-point to the comments of reviewer.
Once again, thank you for submitting your manuscript to PeerJ and we look forward to receiving your revision.
Sincerely,
Gabriele Casazza
The basic reporting is mostly good. I appreciate the authors work to revise the statistical analyses and re-write the methods section.
The whole manuscript is much easier to read and comprehend in this draft. The figures are improved as well.
There are a few sentences that are ungrammatical and a few errors in the text. See the PDF with my annotations attached.
I also appreciate the authors sharing the raw data with the reviewers. This is really valuable.
The experimental design appears to be adequate. The authors have improved their description of the design.
I have several concerns about the validity of the findings:
1) I was unable to reproduce the F-values, eta^2 values and p-values found in Table 2. I used the raw data in sheet 2 of the excel spreadsheet provided. I tried to reproduce the results of the 2-way ANOVA's with R and with SPSS. Each time I got different F-values and different eta^2 values than are shown in the table. I will e-mail the editor the SPSS output from my tests if that is helpful for the authors.
Please confirm the results of your 2-way anovas. If there are extra steps in the data analysis required to reproduce your results, these should be reported in the main manuscript.
2) The F-statistic for the "Biomass" Anova in Table 2 changed in this draft compared to the last draft. Please confirm the value is correct.
3) The authors report that they "recorded plant mortality every three days" (Line 194). Was this true for the entire duration of the experiment (from September to July?). If mortality was checked regularly the authors may be able to use a more sophisticated survival analyses (not Chi^2) to determine treatment effects on survival.
4) The data for the survival analyses were not provided. It would be good to include these data with the manuscript.
The figures appear to be correct based on the data provided.
Thank you for your work to revise this. I have added my comments on the text to the attached PDF document.
Dear Dr. Li,
The reviewers find the paper based on a rigorous experimental design and in general well-written and well-organized, even if English have to be improved in some sections. Nevertheless, they highlight some major weakness in data analysis. In particular, they suggest to properly transform variables for analysis and to analyse binomial variables using an approach that accommodate for non-normal distributions like generalized linear model.
I encourage you to re-analyse data and to improve the manuscript according to tips of reviewers. Please, respond point-to-point to the comments of reviewers.
Once again, thank you for submitting your manuscript to PeerJ and we look forward to receiving your revision.
Sincerely,
Gabriele Casazza
No comment
No comment
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This manuscript presents results of a well-designed experiment on the effect of variation in rainfall amount and frequency on success of a cold desert annual in an arid sand dune ecosystem of northwestern China. It addresses an important question in desert plant establishment ecology. The key result is interesting and well-supported, namely that frequency of precipitation is as important in determining life history outcomes in this species as total amount, and that intermediate frequency is optimal, especially when total amount is below average. The paper is basically well-written and well-organized, with only very minor problems with English, and it does a good job of placing the study in the context of previous work.
My main issue is with the way the data are presented in graphical form and in the text. The bar graphs in Figures 2, 3 and 4 show the full factorial interaction between precipitation amount and frequency, and they present a visually compelling story, particularly in Figure 2. However I found the means separations on these graphs to be very difficult to follow. As these are main effects means separations, I think it would be best to include main effects graphs in addition to the full factorial interaction graphs, or perhaps even better, to present the main effects in table form with their means separations. The full interaction graphs could still be presented, possibly with means separations for the interactions presented when they are significant. The text tends to discuss all the interactions as if they were significant, but in many cases they were not; this needs to be considered in the way the results are described.
I could not find any statistical support in the paper for the means separations in Figure 2; this needs to be included in the ANOVA table. The main effects in Figure 2 are obviously significant, but the focus of the presentation in the results is on the interactions, so it is important to know whether the interaction term was significant. Also, Figures 2 and 5 are the only figures that contains error bars, and these are not defined—are they standard errors of the mean? Why are error bars included only on these graphs and not the others?
Another question I have is with data transformations for the ANOVA. Survival and seed germination are clearly binomial variables that are not normally distributed, and the best way to handle these is to use an alternative analysis that takes the binomial distribution into account. A traditional alternative has been to use arcsine-square root as a transformation for binomial data, but this has been shown to be less effective than a generalized linear model approach that can accommodate non-normal distributions. Seed mass and number and capitulum number could also benefit from log or square root transformations, but I am not sure why a log transformation was chosen for root-shoot ratio. Reproductive effort is never formally defined, so it is difficult to know how it should be treated statistically. It also appears to be a proportion; please clarify how it was calculated. Data transformation is unlikely to change any of the major take homes of the analysis, but the details of the means separations could change.
I would also like to see a better explanation of the variance component analysis. These variance components do not sum to one, so I assume the remaining variance is error variance? Or is that interpretation too simplistic? There is a citation for this method, which is good, but it is likely not a primary reference for this statistical method. In any case, a reader should not have to consult a primary reference to understand the paper. This index is stated to account for the ‘percentage of variation that is explained as a plastic effect’, but I am not sure what this means. The interpretation of the results depends on this analysis quite a bit, so it would be good to add a few more sentences to the methods to explain what it really means.
A few minor points:
In Figure 3, panel B needs a Y-axis label—it is possible to figure this out from the legend, but at first glance it looks like a drafting error, so why not include it?
Line 130. Talking about stabilizing mobile dunes after their stabilization creates confusion. Is it that the dune stabilization method with the straw checkerboards and revegetation is not totally effective, so that mobile dunes redevelop? This needs rewording.
Line 147. It is not possible to know exactly when a buried seed germinates—please refer to this a seedling emergence, not seed germination.
Line 180. The period of experimental treatment from spring to summer does not correspond to the life cycle of a winter annual, which starts when the seed germinates in fall. This just needs to be reworded.
Line 195-196. If overwinter survival is a key factor in population dynamics for this species as you state here, and as you measured overwinter survival in the prequel to your experiment, you could report the data. I know they are not part of your experimental design, but it would be interesting to know.
1) In the introduction hypothesis and predicted effects of the rainfall manipulation could be more specific. Currently the main hypothesis is that changing the rainfall regime would affect the plants somehow. This is a reasonable expectation but rather unspecific. Given the number of response variables measured it was very likely that at least some would respond to the treatments. Can the authors be more specific about which variables and in which direction they expected the plants to respond to each treatment?
2) Similarly, in the discussion section the authors should attempt to reach a more clear and concise conclusion. There were a lot of response variables measured, survival, germination, growth, height, root/shoot ratio, capitula number, etc. It can be easy to get lost in the details. I would appreciate a stronger attempt to synthesize the results into a few important points. For instance, I was surprised for at the strength of the response to rainfall frequency—the effect of rainfall frequency was nearly as strong as the effect of rainfall amount (Table 2).
3) There were errors in the raw data shared in the excel sheet. These prevented me from reproducing the results as shown in the paper. These need to be corrected so that the analyses can be reproduced:
- In sheet 3. The number of treatment rows in columns A and B, does not match the number of rows of data in the other columns.
- In sheet 3, row 105, column ‘C’. This shows an anomalous plant height of 322 (cm). This does not appear to match the average height shown for this treatment combination in figure 3c.
- In sheet 3, reference error on Line 104, column ‘E’
- In sheet 3, reference error on Line 72, column ‘H’
4) In Table 2, the numerator and denominator degrees of freedom MUST be given whenever reporting the results of an F-test.
5) The method used to analyze the survival data is not explained.
1) The “Experimental Design” section should be reorganized to more clearly convey the basic and most important aspects of the design. I would suggest starting that section with a description of the actual design, which now starts at about line 162. This part is so important that it should be brought up to the beginning of the section. This section should clearly and succinctly explain the number of treatments, treatment levels, number of replicates per treatment (see below), in one paragraph. Currently important elements of the experimental design are mixed in with other details about the plants, the measurements taken and the environment. This makes it difficult for the reader to quickly grasp the design.
1) As stated above there appear to be some errors in the excel spreadsheet that was distributed with this manuscript those need to be corrected.
2) All analyses are conducted with 2-way ANOVAS with an interaction. However, some of the response variables are not well suited to an analysis with an ANOVA. For instance, percent germination is bounded between 0 and 1 (or 0 and 100%), and capitula number is a positive integer and is generally a pretty small number. Neither of these variables match a normal distribution. Consider whether an ANOVA with normal errors is justified for each response variable. The authors could consider using generalized linear models for some of these measures, such as a binomial model with a logistic link for the percent germination, and a Poisson model with a log-link for capitula number, etc.
3) Likewise, because of plants dying some of the analyses will be unbalanced (that is have different numbers of replicates per treatment level). This can be problematic and the authors need to discuss whether the results of the ANOVA are robust to this.
4) The authors need to more clearly state the degrees of freedom for the tests as well. This is missing from Table 2 and it depends on how the replicates are counted. (mentioned above as well).
1) In general, I applaud the authors effort in using a rigorous experimental design to investigate the impact of precipitation on annual plant population ecology. I especially appreciate that both rainfall amount and rainfall frequency were manipulated separately in the experiment. I also appreciate the care taken to measure many aspects of plant performance.
2) This is only a suggestion, but the data here present an opportunity to build a population model for the species. A population model would be a powerful way to understand the overall effect of precipitation on this species. See Compagnoni (2014) for a good example of integrating separate vital rates into a simple population model for an annual plant species. This may be beyond the scope of the current manuscript so take it as only a suggestion. It could be a good topic for a future paper.
Compagnoni, A. 2014. Warming, soil moisture, and loss of snow increase Bromus tectorum’s population growth rate. Elementa: Science of the Anthropocene 2:000020. Doi: 10.12952/journal.elementa.000020
Minor points
• Line 69: Discussing plasticity of survival is bit odd. The survival rate is defined at a population level. Plasticity usually involves variation among individuals within a population.
• Line 69: Is fecundity an “early life-history stage”?
• Line 70 -74: Sentence is a bit long and hard to follow, consider revising for clarity.
• Line 51: Grammar, pluralize or use definite article “plant communities”
• Line 136: Grammar, pluralize “seedlings”
• Line 172: Grammar, need definite article at start of sentence: e.g. “[The] shelter was assembled…”
• Line 180 – 181: Information on the number of replicates per treatment is very important. This should not be confined to a parenthetical phrase and should be described earlier in the experimental design section. If I understand this correctly there were 25*12 = 300 total replicates (pots?) in the experiment.
• Line 241: How was seedling survival data analyzed? There is a p-value here, but I don’t see any mention of survival in the analysis section.
• In Figure 3 the x-axis is somewhat hard to read. It can be hard to tell which bar goes to which precipitation treatment (“Quantity change of rainfall”). I think that centering the tick marks below the treatment and making them bigger would help. Also maybe spreading the groups of bars for each rainfall amount apart would help.
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