the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Region effects and local climate jointly shape the global distribution of sexual systems in woody flowering plants
Minhua Zhang
Xiaoqing Hu
Fangliang He
Abstract. Understanding the evolution and maintenance of plant sexual diversity needs to incorporate both regional processes and local climate factors across large geographic scales. Using data of woody flowering plants from a global set of large-scale forest plots and multinomial logistic regression, we quantified region effects on the proportion of dioecy, monoecy, and hermaphrodite species count and abundance while incorporating evolutionary history and local climate factors. We demonstrated that plants were more likely to be dioecy than monoecy in tropical regions than in temperate regions, supporting the role of colonization processes suggested by Baker’s law in structuring the geographic patterns of plant sexual systems. We further found plants were more likely to be dioecious than monoecious in areas with younger mean species age. Plants were more likely to be hermaphrodite than dioecious in areas with high annual potential evapotranspiration and precipitation seasonality but were more likely to be dioecious than monoecious in areas with high precipitation of driest month. Our results suggest that both regional processes and local climate factors play important roles in shaping the geographic distribution of plant sexual systems, providing a baseline for predicting future changes in forest communities under global change.
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Minhua Zhang et al.
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RC1: 'Comment on bg-2023-154', Anonymous Referee #1, 07 Nov 2023
This study addressed an interesting question of the effects of multi-level processes on the geographic distribution of forest woody plant sexual diversity, which helps to advance the understandings of the underlying drivers of geographical pattern of forest plant diversity. The manuscript is overall clearly written. However, at the moment I still have a couple of concerns and some minor comments, listed as below,
Major concerns:
1. According to my understanding, "region" in the text means continent-level landmass (Lines 123-124) and its effects on shaping plot-level plant sexual diversities were important (Lines 161-162), while latitude effects were unimportant when other factors' effects were controlled (Lines 155-157). It would be better not to group the regions as either tropical regions or temperate regions, which is confusing.2. As the authors stated in the Introduction, if (a) dioceious is more likely associated with dry or poor resource habitats (Lines 61-56), and (b) areas with younger species age is expected to have a higher incidence of diocey (Lines 55-57), then an interactive effect likely exists between (a) and (b) on uplifting the incidence of diocey. Have the authors considered of including this interactive term in the regression models?
Minor comments:
Lines 14-16 I am not sure this finding (not significant when the effects of climate etc. were controlled as shown in the Results at Lines 155-157) supports Baker's law. Lack of dioecy in temperate regions can be a result of biotic and/or abiotic filters, apart from the expected low colonization capacity of dioecious plants.Lines 40-41 Mathematical inference? What is the underlying biological/ecological meaning?
Line 43 replace "showed" with "show"?
Lines 53-55 I am not sure this expectation holds, if the effects of abiotic and biotic filters have not been ruled out first. Besides, I think the authors meant that dioecious plant species would have lower relative incidence in temperate than tropical regions compared with other sexual systems plant species, due to the expected low colonization rates of dioecious plants in temperature regions.
Line 81 what does "PET" stand for?
Lines 85 should be "forest dynamics plots"?
Lines 112, 132 replace "number of trees" with "number of stems"?
Lines 127-134 A common format is that R package name be in italics and R function name in quotation marks, please check and be consistent in the text.
Line 180 add a "be" between "to" and "hermaphrodite". replace "Fig. 5, S4" with "Fig. 5, S5"?
Line 181 "Fig. S5" should be replaced with "Fig. S4 "?
Lines 196-199 These two findings contradict each other. Why low colonization capacity is important in one case but not important in another?
Please elaborate more on this.Lines 221-222 How do these results support Baker's law?
Lines 224-226 It is not clear what regional processes or climate factors, can the authors give an example?
Line 229 replace "less" with "more".
Citation: https://doi.org/10.5194/bg-2023-154-RC1 -
RC2: 'Comment on bg-2023-154', Anonymous Referee #2, 28 Nov 2023
I thank the authors for their interesting study. I have enjoyed reading the manuscript, which is mostly presented clearly and concisely, and I find the emergence of biogeographic patterns in plant reproductive traits quite exciting, personally. I have nevertheless a few general points that I think need the author's attention:
- I am a bit unsure about the chosen modelling strategy. At the very least, some more details should be given (in the appendix), like the correlation between the different variables, and the results of the VIF analyses. I also have some doubts that fitting “regions” is the most meaningful variable to fit. I wonder if it wouldn’t make more sense, at least as an alternative approach, to model this variable as a random factor in a mixed model.
- Another aspect that I think is somewhat problematic, is the apparent overfitting of the models. As can be seen in all the graphs of the logistic models, the blue line fits almost individual data points, which is also expressed in the relatively high variances explained in the different models. I think that this “better” fit clearly comes at the cost of interpretability. I suspect that also here the region variable plays a major role, which again makes me wonder if it wouldn't be better to fit it as a random factor. Another point in this context is that you present certain variables as not significant in the models, but then still visualize their relationships with sexual system in the presented graphs (e.g. latitude etc.).
- In some places in the discussion I have problems following what you are trying to say, and you can find those in my detailed comments below.
Detailed comments:
Line 15: Throughout the manuscript, you are constantly confusing the use of adjectives and nouns, when referring to the sexual systems. Please make sure that you use dioecious/dioecy, monoecious/monoecy, hermaphroditic/hermaphroditism appropriately.
Line 112, “plot characters”: These seem to me two important potentially confounding variables, and I don't understand why they have not been kept in the models (no matter their VIF). In addition, I would also think species richness in the plots could be another important covariate.
Line 128f: I don't understand how you can estimate lambda for a discrete trait, as lambda is based on a Brownian motion model of trait evolution, which is models continuous traits. Could you please comment and specify how that works for discrete traits? Could that also be the reason that you get either 0 or very high values for lambda?
Line 136ff: This selection procedure based on variance inflation, while maybe statistically valid, is somewhat elusive. First, it would be good to see the results of this in the appendix, also to get a better overview of what variables were used and which were excluded, and also how they were all correlated with each other. I would also argue that it could be important to keep some potentially confounding variables (i.e. the plot characteristics plus plot species richness) in the model, no matter their VIF. Otherwise, what is the point of having those variables in the first place?
Line 156f: I would be more careful in how you express that here. Latitude is clearly reflected in the "region" variable, so it is not that it is unimportant, it is just that in the model all the explanatory power is "taken away" by the region variable, but that region variable still expresses latitude as well. See also my earlier general comment about the use of region as a variable.
Line 162, “plot characteristics”: I can't see the plot characteristics in these tables. In general, since you never show what the “full” model was that you tested, it is not possible to understand from these table what variables where included and which excluded, as you seem to present only the significant variables. As mentioned earlier, it would be good if you could provide more details on that (see my comments about VIF and correlation between variables).
Line 174: This table does not show anything about lambda. Again, it would be helpful to see the correlations between variables presented somewhere. Also, if it wasn't significant in the models, why did you decide to include plots in the appendix? Also, I am sceptical about the calculation of lambda for these traits. First because of the aforementioned doubt that lambda is meaningful for discrete variables. Second, because as can be clearly seen in the graphs you provide in the appendix, the lambda is either very high, or zero, which does not seem very meaningful, certainly not for including lambda as an explanatory variable.
Line 194-195: I don’t understand how that relates to the previous sentence. You say that dioecy is disadvantageous for long distance colonisation, but what has that to do with tropical regions? Why should they disfavour species with long distance colonisation ability? Also, the end of the sentence doesn't make sense.
Line 197, “which supports…”: Again, I don't follow the logic here. Please try to express yourself clearer.
Line 246: Unclear what processes you mean here, and it results in this phrase sounding quite vague.
Citation: https://doi.org/10.5194/bg-2023-154-RC2
Minhua Zhang et al.
Minhua Zhang et al.
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