Review Reports - Environmental Factors Driving Diversification of Ponderosa Pine in the Western United States

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

From my point of view, the work is well argued, however, when characterizing ten groups, I think it is necessary to make a description of the natural conditions in which each of the groups develop, making an analysis of the similarity of conditions in which the groups develop

They have the "floristic" analysis, I would combine it with a more ecological analysis with the conditions of each site and thus I would have a more complete ecological analysis, using the clusters vs the natural conditions of each one of them and we would know exactly what is separating those groups

Saving the editor's criteria, these would be my suggestions for the authors

Author Response

Reviewer 1 Comments

I included an extensive paragraph in the discussion that covers these ecological drivers.

The patterns we observe make sense with the Pacific Northwest clustered with northern California because of their similar moist maritime climate suggesting that researchers should find genetic similarity between varieties ponderosa and benthamiana. Variety scopulorum maps out as a distinctive group in almost all of our clusters. This suggests that the dry northern Midwest region (with minimal influence from monsoon rains) creates a distinctive habitat for ponderosa pine. Region 3 with variety brachyptera is the most heterogeneous cluster which matches the landscape. This region is topographically diverse which creates a feedback with climate and fire effects. This region is also has a gradient of monsoon precipitation affects with more seasonal rain in the southern portion of the region and less monsoon precipitation in the northern portion of the region. This heterogeneity creates a complex landscape of slope, aspect, micro-climate, and fire. We hypothesize that variety brachyptera is likely to have greater genetic diversity than the other groups. Pandora moth outbreaks are more heterogenous across the landscape and will affect individual populations of trees rather than the entire region in most outbreaks. It is possible that the frequency of outbreaks in an area could be a genetic driver, but it does not appear to be an organizing agent across entire regions.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors,

I red your manuscript with a great interest. I guess, it is a brilliant idea to use the cluster analysis for such purposes. But I have some comments about the implementation of this approach. I hope, my comments will be useful.

Major comments:

L. 167–169: You do not describe the procedure of Euclidean distance calculation. Did you use the width of tree rings for this purpose? Or, may be, it was tree-ring indices? Please, describe the calculation in details.
Why don’t you use the algorithms for estimation the optimal number of cluster (e.g., simple elbow method or more complex methods implemented in some R packages [https://cran.r-project.org/view=Cluster])?
L. 224–225: ‘...but no clear geographic patterns of the 224groupings in region 3’. It is arbitrarily, of course, but I can not completely agree with this conclusion. In my opinion, the ‘red’ cluster in the Fig. 5C distinctly separated from the ‘blue’ and ‘purple’ ones by the NW–SE line. Possibly, this separation can be interpreted in any way.
L. 252–255: Two parts of this sentence are mutually exclusive. The results of your cluster analysis shows the Pinus ponderosa var ponderosa have the same drivers like P. ponderosa var benthamiana. Therefore, these factors can not trigger the divergence between these varieties.
L. 257–263 and the Discussion section in the whole: This part of section is brilliant. But you don’t discussed the role of environmental factors in the cluster formation. Please, reveal the contribution of environmental drivers and territorial characteristics (possibly, defoliation, fires, droughts, air masses movement, relief etc.) to the differences between tree-ring chronologies.

Minor comments:

L. 113: May be, data instead of date?
Figure 3: The caption is not self-explaining. Please, add the description of regions and p-values like for Fig. 2.
References: Sometimes the Latin names of species are not italicized (#12, 13, 33, 49). Please, check in throughout the text.
References: in #38 ‘F-statistics’ is italicized, but in #39 is not. Please, make it uniform.

Best regards!

Author Response

Reviewer 2

I read your manuscript with a great interest. I guess, it is a brilliant idea to use the cluster analysis for such purposes. But I have some comments about the implementation of this approach. I hope, my comments will be useful.

Major comments:

1. L. 167–169: You do not describe the procedure of Euclidean distance calculation. Did you use the width of tree rings for this purpose? Or, may be, it was tree-ring indices? Please, describe the

calculation in details.

Yes, we used the standardized tree-ring indices to calculate the similarity between chronologies and develop the clusters. I included a statement regarding this in this paragraph,

2. Why don’t you use the algorithms for estimation the optimal number of cluster (e.g., simple elbow method or more complex methods implemented in some R packages [https://cran.r-project.org/view=Cluster])?

We have now described this more clearly in the paper at lines 192-198.

3. L. 224–225: ‘...but no clear geographic patterns of the 224groupings in region 3’. It is arbitrarily, of course, but I can not completely agree with this conclusion. In my opinion, the ‘red’ cluster in the Fig. 5C distinctly separated from the ‘blue’ and ‘purple’ ones by the NW–SE line. Possibly, this separation can be interpreted in any way.

We agree with you observation and changed our comment about region three to the following: “Region three combines many clusters that still have some spatial pattern that might represent microclimatic and elevational differences.” This distinct region is also discussed in the first paragraph of the discussion.

4. L. 252–255: Two parts of this sentence are mutually exclusive. The results of your cluster analysis shows the Pinus ponderosa var ponderosa have the same drivers like P. ponderosa var

benthamiana. Therefore, these factors can not trigger the divergence between these varieties.

We corrected the wording in the discussion to explain that traditional mapping makes var ponderosa a separate group, but our analysis shows that it always clusters with benthamiana.

5. L. 257–263 and the Discussion section in the whole: This part of section is brilliant. But you don’t discussed the role of environmental factors in the cluster formation. Please, reveal the

contribution of environmental drivers and territorial characteristics (possibly, defoliation,

fires, droughts, air masses movement, relief etc.) to the differences between tree-ring chronologies.

I included a paragraph in the discussion that discusses these environmental factors and their effect on diversification.

Minor comments:

1. L. 113: May be, data instead of date?

Correct. Thanks for the edit.

2. Figure 3: The caption is not self-explaining. Please, add the description of regions and p-values like for Fig. 2.

Done.

3. References: Sometimes the Latin names of species are not italicized (#12, 13, 33, 49). Please,

check in throughout the text.

Done

4. References: in #38 ‘F-statistics’ is italicized, but in #39 is not. Please, make it uniform.

Done

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Dear colleagues,

Thank you very much for your efforts. I guess the manuscript is appropriate in the current form.

Best wishes!