the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Coordination of rooting, xylem, and stoma strategies explains the response of conifer forest stands to multi-year drought in the Southern Sierra Nevada of California
Polly Buotte
Roger Bales
Bradley Christoffersen
Rosie A. Fisher
Michael Goulden
Ryan Knox
Lara Kueppers
Jacquelyn Shuman
Chonggang Xu
Charles D. Koven
Abstract. Extreme droughts are a major determinant of ecosystem disturbance, which impact plant communities and feed back to climate change through changes in plant functioning. However, the complex relationships between above- and belowground plant hydraulic traits, and their role in governing plant responses to drought, are not fully understood. In this study, we use a plant hydraulics model, FATES-Hydro, to investigate ecosystem responses to the 2012–2015 California drought, in comparison with observations, for a site in the southern Sierra Nevada that experienced widespread tree mortality during this drought.
We conduct a sensitivity analysis to explore how different plant water sourcing and hydraulic strategies lead to differential responses during normal and drought conditions.
The analysis shows that:
1) deep roots that sustain productivity through the dry season are needed for the model to capture observed seasonal cycles of ET and GPP in normal years, and that deep-rooted strategies are nonetheless subject to large reductions in ET and GPP when the deep soil reservoir is depleted during extreme droughts, in agreement with observations.
2) risky stomatal strategies lead to greater productivity during normal years as compared to safer stomatal control, but lead to high risk of xylem embolism during the 2012–2015 drought.
3) for a given stand density, the stomatal and xylem traits have a stronger impact on plant water status than on ecosystem level fluxes.
Our study reveals the importance of resolving plant water sourcing strategies in order to represent drought impacts on plants, and consequent feedbacks, in models.
- Preprint
(1309 KB) -
Supplement
(1611 KB) - BibTeX
- EndNote
Junyan Ding et al.
Status: open (until 30 Mar 2023)
-
RC1: 'Comment on bg-2023-16', Anonymous Referee #1, 16 Mar 2023
reply
Ding et al present an interesting study using the FATES model at the Soaproot site in the southern Sierra Nevada Mountains, USA, which is dominated by ponderosa pine trees. The authors explore parameter space for root depth, hydraulic, and stomatal parameters in their experimental design. The authors initialize FATES with the observed demography and turn off growth and mortality to observe how changes in climate over a major drought period impact simulated physiology, soil moisture, and water and carbon fluxes. The model is forced with 4km resolution MACA climate. Model predicted ET and GPP are compared to flux tower observed LH and tower modeled GPP. The exploration of hydraulic parameter space and rooting depths is a really interesting and important set of model experiments to perform for hydraulically enabled vegetation models and their application to terrestrial ecosystem processes. However, I have several major methodological concerns that I hope the authors can address
Method clarity: Some aspects of the experimental design are not clear. For example, how was the soil moisture initialized or spun up? Did the authors test the sensitivity of their conclusions to this method? What is the vertical resolution of the new multi soil layer model? Given that soil water is fundamental to these experiments, I think these are important details. I also wonder why the authors forced the model with MACA instead of the flux tower met.
Assessment of model performance: I see this as a contextualized OSSE experiment. However, I do think that the authors should do a little more than calculate TMSE relative to GPP/ET. Perhaps use some of the standard ILAMB metrics in addition to RMSE like inter annual variability, monthly variability and phase shifts in annual cycles?
The authors come off as defensive about the model predicted leaf water potentials, understandably because they are a physical (there are basically no trees that allow for LWP lower than -4 MPa, the -10 MPa cited in the text is for California chaparral and the correct citation is Tyree 1997 not Vesala 2017). I do appreciate that the experiments are designed to test relative sensitivities of physiological diagnostics to model parameters and that ecosystem dynamics are turned off, but with some of the parameterizations all the trees would be VERY dead before the drought started. I think with such ridiculous LWP values, the authors are going to lose the confidence of a large portion of their audience that has a physiology but not a modeling background, so I hope they will try to make some modifications to their experiments. The fact that the LWPs are dropping so low suggests that the authors might want to reconsider the vulnerability curve parameterization and parameter space that they explore for their experiments. Another option is to use the simulated water potentials to tell us more about the system (for example, to screen what parameter combinations are physiologically impossible at the site). It seems like these trees must have really deep roots to exist at this site with is in agreement with the conclusions of Goulden and Bales 2019. Why not direct the discussion in this direction instead?
Minor line specific comments
There are grammatical problems throughout the text which could use further proofreading (tense problems etc)
Almost everywhere water potential units are written as ‘Mpa’ when they should be ‘MPa’. Similarly, the authors should be consistent with capitalization/abbreviation of ‘Fig.’, ‘fig’, ‘Figure’ throughout the text. Id also like the authors to denote the denominator as either 1/x or x-1 rather than using both in the text
Instead of using kLWP as one of the parameters, can the authors choose a different letter, this is easily confused with conductance (k)
All of the figures would benefit from increased font size.
L359-361 I am having trouble understanding what the authors mean here, can they clarify?
Make sure to write out all abbreviations in figures in the captions
Citation: https://doi.org/10.5194/bg-2023-16-RC1
Junyan Ding et al.
Junyan Ding et al.
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 185 | 69 | 10 | 264 | 23 | 5 | 8 |
- HTML: 185
- PDF: 69
- XML: 10
- Total: 264
- Supplement: 23
- BibTeX: 5
- EndNote: 8
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
