The authors have included the conversion to sap flow as suggested in the previous review. However, there are a number of points which still need to be addressed. With regards to the analytical approach, the relationship with soil moisture should be better explored and Fig. 4 should be improved to better depict the complexity of the dataset (co-variation of species, geology, aspect, etc; see my comments below). Moreover, there are several points to improve in the discussion, mainly the interpretations of species and aspect effects.
Specific comments
P. 5., L. 8. Could you specify which oak species was the allometry below derived from?
P. 6, L. 34. You have Q. robur and Q. petraea in your study site. Could you specify how many oaks from each species were measured in Table 1?
P. 8, L. 24-25. I think this analysis should be improved because soil moisture effects on transpiration are highly non-linear (Duursma et al., 2008) and here you’re relying on linear correlations. Moreover, in analysing sap flow vs soil moisture individually you’re not taking into account the variability due to variation in Epot. I suggest that:
You calculate SF/Epot, as sap flow relative to evaporative demand.
Optionally, rescale soil moisture values to relative values, obtaining relative extractable water or soil moisture deficit values (Granier et al. 1999; Granier & Loustau 1994)..
Plot SF/Epot as a function of (rescaled) soil moisture and check whether there is a threshold below SF/Epot starts to decline
Use an appropriate modelling approach to describe this behaviour: nonlinear models (e.g. sigmoidal, Sánchez-Costa 2015), piecewise/segmented regression (cf. Muggeo 2008) to detect possible breakpoints in this relationship, etc.
This analysis can be done to detect soil moisture effects both in the temporal and the spatial analysis.
Duursma, R., Kolari, P., Perämäki, M., Nikinmaa, E., Hari, P., Delzon, S., Loustau, D., Ilvesniemi, H., Pumpanen, J. & Mäkelä, A. (2008) Predicting the decline in daily maximum transpiration rate of two pine stands during drought based on constant minimum leaf water potential and plant hydraulic conductance. Tree Physiology, 28, 265–276.
Granier, A. & Loustau, D. (1994) Measuring and modelling the transpiration of a maritime pine canopy from sap-flow data. Agricultural and Forest Meteorology, 71, 61–81.
Granier, A., Reichstein, M., Breda, N., Janssens, I., Falge, E., Ciais, P., Grunwald, T., Aubinet, M., Berbigier, P., Bernhofer, C. & others. (2007) Evidence for soil water control on carbon and water dynamics in European forests during the extremely dry year: 2003. Agricultural and Forest Meteorology, 143, 123–145.
Sánchez-Costa, E., Poyatos, R. & Sabaté, S. (2015) Contrasting growth and water use strategies in four co-occurring Mediterranean tree species revealed by concurrent measurements of sap flow and stem diameter variations. Agricultural and Forest Meteorology, 207, 24–37.
Vito M. R. Muggeo (2008). segmented: an R Package to Fit Regression Models with Broken-Line Relationships. R News, 8/1, 20-25. URL https://cran.r-project.org/doc/Rnews/.
P. 8, L. 31. With regards to this section and also to Fig. 4, I already suggested in the previous review that grouping data by species (or by aspects in the first panel) would support some of the points you make (see my comment below on P. 12., L. 25-32)
P. 10, L. 8-9. It seems that when you leave out species-specific predictors ( compare Fig. 6 with Fig. 8), geology seems to gain a prominent role in explaining variability. Is there an association between species distribution and geological substrate that could explain this result?
P. 10, L. 20-30. You don’t need to repeat the values of r, as they’re already shown in Table 2.
P.10, L. 39 - p. 11, L. 1. Temperate tree species as the ones in this study will show declining transpiration rates with decreasing soil moisture below a certain threshold, and well before any visual sign of foliar water stress. The fact that in given localities water stress has been detected yet you don’t find any soil moisture effect on sap flow rates seems a bit odd to me.
P. 11, L. 2-10. I agree that we often lack the most complete picture of the available water sources for plants, but I suspect that the reason you’re not detecting any soil moisture effect is because of the analytical approach employed (see my previous comment on the suggestion of Sf/Epot analysis).
P. 11, L. 29 - 31. I already commented on this in my first review, and there are different issues to discuss here. First of all, the heat ratio method is well known to underestimate sap flow density as the method plateaus (loses sensitivity) at ~ 45 cm3 cm-2 h-1 (Fuchs et al. ,2017, Vandegehuchte & Steppe, 2013). Deciduous Quercus have large earlywood vessels, highly conductive and possibly allowing large sap flow density values, compared to Fagus, which shows a diffuse porous wood anatomy. What I mean is that the HRM may be possibly missing these high sap flow densities in oaks and therefore leading to an underestimation.
Moreover, comparative studies between Q. petraea and F. sylvatica show higher sap flow density in the former (Aranda et al 2005), pointing towards higher sap flow density in deciduous oaks compared to beech. A rough estimation from published values for Q. robur (Bréda et al. 1993, Fig. 2) also shows mean daily values closer to 10 cm3 cm-2 h-1, higher than those shown in Fig. 4 for oak. There is an additional uncertainty arising from potential differences between oak species. Overall, these issues should at least be discussed when interpreting differences between beech and oak.
Aranda I, Gil L, Pardos JA (2005) Seasonal changes in apparent hydraulic conductance and their implications for water use of European beech (Fagus sylvatica L.) and sessile oak [Quercus petraea (Matt.) Liebl] in South Europe. Plant Ecology 179:155–167.
Fuchs S, Leuschner C, Link R, Coners H, Schuldt B Calibration and comparison of thermal dissipation, heat ratio and heat field deformation sap flow probes for diffuse-porous trees. Agricultural and Forest Meteorology. http://www.sciencedirect.com/science/article/pii/S0168192317301314 (16 June 2017, date last accessed ).
Vandegehuchte MW, Steppe K (2013) Sap-flux density measurement methods: working principles and applicability. Functional Plant Biology 40:213–223.
P. 12., L. 25-32. I find this reasoning a bit convoluted, because to explain the lower sap flow rates in southern aspects, you’re invoking long-term drought adaptations without having detected soil moisture limitation effect on sap flow. Moreover, you don’t provide any reference supporting possible mechanisms for these drought adaptations and how they could possibly influence sap flow density patterns (e.g. changes in hydraulic conductivity, adjustments in leaf-to-sapwood area ratios,etc.).
I was thinking whether it could be an effect of oak, with lower sap flow density, being preferentially distributed in southern slopes, but I’ve seen in a response to Reviewer #1 that beech trees also show lower sap flow rates in southern aspects. I think that you should provide this information to the reader, not only to the reviewers, so the results can be discussed properly. One possible way would be to add conditioning factors (e.g. species, or aspect in the first panel) in the plots of figure 4. This is something I already proposed in the first version of the manuscript and which I mentioned in an earlier comment (on P. 8, L.31).
You mention geology as a possible influence on these patterns. Do the southern slopes sampled correspond to schist substrate (which seems to be associated with lower sap flow density)? It is not clear whether you mean this in your explanation of lines 32-34 (P. 12).
P. 12, L. 40-42. Then, Epot is not higher in southern slopes so one should not expect higher sap flow as discussed in the previous paragraph. These results here are more consistent with the fact that sap flow was not higher in southern aspects. Maybe you should integrate this part of the discussion in a single paragraph (e.g. from P. 12. L. 25 to P. 13, L. 2), because the ideas are very tightly linked.
P. 13, L. 23-25. See the issues on species comparisons mentioned in the comment on P. 11, L. 29 - 31. |