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Peer review report 1 On “Variability of the radial profile of sap velocity in Pinus patula from contrasting stands within the seasonal cloud forest zone of Veracruz, Mexico”
Agricultural and Forest Meteorology 201S (2015) 500–501
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer review report
Peer review report 1 On “Variability of the radial profile of sap velocity in Pinus patula from contrasting stands within the seasonal cloud forest zone of Veracruz, Mexico”
Original Submission Recommendation Minor Revision Comments to Author Review of “Tree-to-tree and temporal variability of the radial profile of sap velocity in Pinus patula from contrasting stands within the seasonal cloud forest zone of Veracruz, Mexico” This is an interesting study that builds on the work of Dragoni et al. to investigate the manner of variation in the radial profile of sap velocity as well as the utility of a beta-pdf approach for estimating whole-tree sap flow. In particular, the authors do an excellent job of testing the method’s assumptions regarding the consistency and time-invariance of the radial profile of sap velocity both within and between trees. Furthermore, they have extended the work in meaningful ways by looking in a more rigorous manner into how probe geometry affects the estimation of vs profiles, and the use of a more robust statistical model for explaining variation in cs. They focus on an important species with a differing xylem structure (conifer) than prior efforts to use this approach, thus broadening the range of applications and providing insight into the generality of the methods across woody species. Their research questions are clearly stated and the data provided address these questions directly and support the conclusions that the authors draw from their work. Overall, I find this manuscript is highly suitable for publication in Ag & ForMet, and I found the work to be of interest, novel, and well-presented. Some general and specific comments follow: I would prefer the authors use “young” and “mature” as descriptors throughout the manuscript, rather than the abbreviation “Y” and “M”. The reader makes the mental substitution anyway, but why force this when there is no real need to abbreviate the text? L148 - Isn’t the HMP45 C a temp/RH probe? So why is the VPD determined psychometrically? L154-155 - Is this a standard method? I have not heard of it before, so perhaps the authors could just explain that this is
DOI of original article: http://dx.doi.org/10.1016/j.agrformet.2012.08.004. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.105
commonly used (only 1 ref is provided) and/or the particular “M-of-N” definition does not greatly affect cloud immersion detection? L157 - Again, I think HRM isn’t a necessary abbreviation (although admittedly this is more commonly seen in the literature). In general, anytime the authors can avoid abbreviations in their manuscript, the reader will benefit. L226-227 - I’m not completely clear on how a graduated cylinder was used to measure water loss from the bucket during the wholetree experiment. L333-336 - What was the actual percent error for the Q H method? How was bias higher, but the agreement better? L366-370 - During low evaporative demand, was v s even significant? Part of the low r2ˆ could be due to both radial homogeneity and uncertainty in the v s value using the HRM methods during low sap velocity. L425-427 - Caylor & Dragoni pegged their curve fits using zeros (i.e. v s = 0 at x = 0 and x = 1). This could have constrained the curves to a greater degree than the current study, which appears to have only fit the three observed points, but not used the zeros themselves as an additional constraint to the fit? L463 - missing “rho” L484 - missing “rho”? Table 1-3 - I am not sure this data is necessary for the presentation. Most of this could be summarized in the text by giving ranges of observations, or means and std. dev. of values like rho, etc. Table 5 - I think this Table has some critical information in it, but I am sure the text was much more clear about these results than this presentation. Perhaps the authors could compare these different estimates in a scatter plot between Qb and the other methods? Figure 2b - I found this difficult to interpret. Figures 3-4 - Could this be simplified to show some “characteristic” trees rather than every profile? If every profile is to be presented, then the figure seems appropriate more for a “supplemental” on-line rather in the main text. Figure 5b - Obviously, I am as excited about this presentation as Figure 2b. If the authors feel strongly that this presentation should remain, then I think they need to work harder to explain how to interpret this subplot. Figure 6 The x axis should be hour of day (0-24), not HH. Figure 7 This figure, since it describes the meteorological setting of the data collection should probably appear before some of the
Peer review report / Agricultural and Forest Meteorology 201S (2015) 500–501
other material. However, I leave it to the authors to decide. Panel e - while demonstrating the consistency of “rho” through time could easily be a set of histograms instead? That would make the same point, but allow the reader to see the variability in observations, etc. instead of these flat lines, which make the point but do so with little additional informational content. Figure 8 Can the authors speculate on why their model of c s starts to flatten out at high observed c s values? This seems like an
501
interesting result, but the possible reasons for it aren’t explored in much detail within the discussion. Anonymous Available online 6 August 2015
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer review report
Peer review report 1 On “Variability of the radial profile of sap velocity in Pinus patula from contrasting stands within the seasonal cloud forest zone of Veracruz, Mexico”
Original Submission Recommendation Minor Revision Comments to Author Review of “Tree-to-tree and temporal variability of the radial profile of sap velocity in Pinus patula from contrasting stands within the seasonal cloud forest zone of Veracruz, Mexico” This is an interesting study that builds on the work of Dragoni et al. to investigate the manner of variation in the radial profile of sap velocity as well as the utility of a beta-pdf approach for estimating whole-tree sap flow. In particular, the authors do an excellent job of testing the method’s assumptions regarding the consistency and time-invariance of the radial profile of sap velocity both within and between trees. Furthermore, they have extended the work in meaningful ways by looking in a more rigorous manner into how probe geometry affects the estimation of vs profiles, and the use of a more robust statistical model for explaining variation in cs. They focus on an important species with a differing xylem structure (conifer) than prior efforts to use this approach, thus broadening the range of applications and providing insight into the generality of the methods across woody species. Their research questions are clearly stated and the data provided address these questions directly and support the conclusions that the authors draw from their work. Overall, I find this manuscript is highly suitable for publication in Ag & ForMet, and I found the work to be of interest, novel, and well-presented. Some general and specific comments follow: I would prefer the authors use “young” and “mature” as descriptors throughout the manuscript, rather than the abbreviation “Y” and “M”. The reader makes the mental substitution anyway, but why force this when there is no real need to abbreviate the text? L148 - Isn’t the HMP45 C a temp/RH probe? So why is the VPD determined psychometrically? L154-155 - Is this a standard method? I have not heard of it before, so perhaps the authors could just explain that this is
DOI of original article: http://dx.doi.org/10.1016/j.agrformet.2012.08.004. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.105
commonly used (only 1 ref is provided) and/or the particular “M-of-N” definition does not greatly affect cloud immersion detection? L157 - Again, I think HRM isn’t a necessary abbreviation (although admittedly this is more commonly seen in the literature). In general, anytime the authors can avoid abbreviations in their manuscript, the reader will benefit. L226-227 - I’m not completely clear on how a graduated cylinder was used to measure water loss from the bucket during the wholetree experiment. L333-336 - What was the actual percent error for the Q H method? How was bias higher, but the agreement better? L366-370 - During low evaporative demand, was v s even significant? Part of the low r2ˆ could be due to both radial homogeneity and uncertainty in the v s value using the HRM methods during low sap velocity. L425-427 - Caylor & Dragoni pegged their curve fits using zeros (i.e. v s = 0 at x = 0 and x = 1). This could have constrained the curves to a greater degree than the current study, which appears to have only fit the three observed points, but not used the zeros themselves as an additional constraint to the fit? L463 - missing “rho” L484 - missing “rho”? Table 1-3 - I am not sure this data is necessary for the presentation. Most of this could be summarized in the text by giving ranges of observations, or means and std. dev. of values like rho, etc. Table 5 - I think this Table has some critical information in it, but I am sure the text was much more clear about these results than this presentation. Perhaps the authors could compare these different estimates in a scatter plot between Qb and the other methods? Figure 2b - I found this difficult to interpret. Figures 3-4 - Could this be simplified to show some “characteristic” trees rather than every profile? If every profile is to be presented, then the figure seems appropriate more for a “supplemental” on-line rather in the main text. Figure 5b - Obviously, I am as excited about this presentation as Figure 2b. If the authors feel strongly that this presentation should remain, then I think they need to work harder to explain how to interpret this subplot. Figure 6 The x axis should be hour of day (0-24), not HH. Figure 7 This figure, since it describes the meteorological setting of the data collection should probably appear before some of the
Peer review report / Agricultural and Forest Meteorology 201S (2015) 500–501
other material. However, I leave it to the authors to decide. Panel e - while demonstrating the consistency of “rho” through time could easily be a set of histograms instead? That would make the same point, but allow the reader to see the variability in observations, etc. instead of these flat lines, which make the point but do so with little additional informational content. Figure 8 Can the authors speculate on why their model of c s starts to flatten out at high observed c s values? This seems like an
501
interesting result, but the possible reasons for it aren’t explored in much detail within the discussion. Anonymous Available online 6 August 2015