Potential effects of cryogenic extraction biases on inferences drawn
from xylem water deuterium isotope ratios: case studies using stable
isotopes to infer plant water sources

Allen, Scott T.; Kirchner, James W.

doi:https://doi.org/10.5194/hess-2020-683

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https://doi.org/10.5194/hess-2020-683

Preprints

19 Jan 2021

Status: this preprint was under review for the journal HESS but the revision was not accepted.

Potential effects of cryogenic extraction biases on inferences drawn from xylem water deuterium isotope ratios: case studies using stable isotopes to infer plant water sources

Scott T. Allen¹ and James W. Kirchner^2,3 Scott T. Allen and James W. Kirchner

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¹Dept. of Natural Resources and Environmental Science, University of Nevada, Reno, USA
²Dept. of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
³Swiss Federal Research Institute WSL, Birmensdorf, Switzerland

Received: 10 Jan 2021 – Discussion started: 19 Jan 2021

Abstract. Recent studies have demonstrated that plant and soilwater extraction techniques can introduce biases and uncertainties in stable isotope analyses. Here we show how recently documented δ²H biases resulting from cryogenic vacuum distillation of water from xylem tissues may have influenced the conclusions of five previous studies, including ours, that have used δ²H to infer plant water sources. Cryogenic extraction biases that reduce xylem water δ²H will also introduce an artifactual evaporation signal in dual-isotope (δ²H vs. δ¹⁸O) analyses. Calculations that estimate the composition of the source precipitation of xylem waters by compensating for their apparent evaporation will amplify the bias in δ²H, and also introduce new biases in the δ¹⁸O of the inferred pre-evaporation source precipitation. Cryogenic extraction biases may substantially alter plant water source attributions if the spread in δ²H among the potential end members is relatively narrow. By contrast, if the spread in δ²H among the potential end members is relatively wide, the impact of cryogenic extraction biases will be less pronounced, and thus suggestions that these biases universally invalidate inferences drawn from plant water δ²H are unwarranted. Nonetheless, until reliable correction factors for cryogenic extraction biases become available, their potential impact should be considered in studies using xylem water isotopes.

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Scott T. Allen and James W. Kirchner

Status: closed

RC1:
'Comment on hess-2020-683', Anonymous Referee #1, 08 Feb 2021

The manuscript underlines existing issues with cryogenic vacuum extraction of plant water for isotope analysis. The authors demonstrate via five case studies how δ²H biases resulting from this extraction method may lead to misleading conclusions when interpreting plant water sources.

The authors heavily rely on results of a study by Chen et al. (2020) without going much into detail about this study. This is often tricky for the reader (since details are not mentioned) and it requires going back and reading the study by Chen et al.

The authors apply a δ²H bias correction to a handful of plant source water studies. But what are the selection criteria of these case studies? The manuscript does not go far beyond the discussion section of the Chen et al. (2020) study. The application of an average bias correction factor determined by Chen et al. to a limited selection of other studies is not enough. Are the tree species from the selected case studies even covered in the study by Chen et al (2020)? Otherwise, I highly question the overall applicability of an average bias correction factor to different tree species (from your case studies) that may react differently during cryogenic vacuum extraction. This would result in the necessity to calculate different bias correction factor for specific plant species. Chen et al. (2020) stress the fact that species-specific differences in the cryogenically obtained δ²H values exist and need to be accounted for (together with data on stem relative water content).

Overall, the manuscript is a bit light. It would benefit from 1) case studies that include the tested species of the Chen et al. study 2) selecting more than five case studies to underline the statements and conclusions of the present study and 3) from including recommendations on how to perform bias correction on your own data and which factors to consider for that (species-specific differences, extraction system bias correction, isotope measurement accuracy etc.). The authors further ignore the well-known fact that cryogenic vacuum extraction from certain soil types causes isotope effects that need to be corrected for (such effects may also differ for the selected case studies). I admit that this is difficult when the raw data of the selected case studies is not available but this could be overcome by choosing newer studies where authors might be willing to share their data or where data is already publically available.

Further, it would be interesting to know if a bias correction is necessary and how a potential bias correction would look like for artificial isotope labeling studies. How would results be shifted?

My specific comments can be found in the attached pdf.

References

Chen, Y., Helliker, B. R., Tang, X., Li, F., Zhou, Y. and Song, X.: Stem water cryogenic extraction biases estimation in deuterium isotope composition of plant source water, PNAS, 117(52), 33345–33350, https://doi.org/10.1073/pnas.2014422117, 2020.

Citation: https://doi.org/10.5194/hess-2020-683-RC1
- AC1: 'Reply on RC1', Scott T. Allen, 12 Mar 2021
  
  See attached.
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC1
RC2:
'Comment on hess-2020-683', Ansgar Kahmen, 23 Apr 2021

This manuscript by Scott Allen and James Kirchner evaluates the effects caused by biased xylem water d2H measurements in the assessment of plant water sources. The manuscript is motivated by several recent reports suggesting biases in the isotopic composition of water that are associated with the cryogenic extraction of water from soils and plant materials. In particular, the authors refer to a recent paper by Chen et al. 2020 who suggest using d2H values obtained for cryogenically extracted xylem water should be corrected for an average bias of -8.1 per mil.

The paper starts off with an explanation of error propagation and lays down in mathematical terms how a systematic bias in d2H values of xylem water affects the application and uncertainty in two-pool mixing models. In essence, the authors conceptually demonstrate with this exercise that the described bias of -8.1 per mil may be of concern if endmembers in mixing models are not sufficiently resolved but that this bias is of less concern, if the end members are clearly distinct in their hydrogen isotope composition. The authors then demonstrate their case by re-evaluating several "classic" water sourcing papers and show how a -8.1 per mil bias challenges the conclusions on plant water sources in studies where mixing model endmembers are isotopically similar but has little effect in studies that use mixing model end members with larger isotopic differences.

I enjoyed reading this manuscript. It addresses a timely topic and puts the relevance of recent reports on measurement or extraction biases carefully into critical perspective. I think that such a contribution is clearly needed in a debate that starts to become overheated and influences scientific progress where it should not. At the same time the authors caution that there are indeed experimental settings, where uncertainties in the data don't allow robust conclusions regarding distinct tree water sources.

From my perspective this manuscript is an important contribution and it can pretty much be published as it is. There are a few thoughts that came to my mind but these are rather ideas or suggestions that the authors may or may not consider in their revisions:

1) I found the choice of sample studies a bit redundant. Maybe, the number of studies discussed could be reduced or substituted with studies that are slightly different in scope. In particular, I would suggest to also discuss work that is less focused on quantifying the absolute water sources of plants but rather seeks to identify species specific differences in water sources. In plant ecology this has been and still is an important topic. In these cases it is the relative difference of water sources among plants that is of interest. Irrespective of the isotopic resolution of the end members in a potential model, an extraction bias would affect all species and thus introduce a systematic error but would not affect the identified differences among species (given a consistent bias for all species ...).

2) The authors focus on the -8.1 per mil bias in d2H values of cryogenic extracted soil water that was recently suggested by Chen et al. The authors correctly mention that other biases in d2H values occurring during the extraction of soil water and/or water uptake by the roots exist and that biases have also been reported for d18O values. To put the evaluation of a -8.1 per mil bias in xylem water d2H into perspective, it might be good to report a few values form other studies indicating the order of magnitude in biases e.g. in soil water extractions of for d18O that other studies have reported and that would cause similar issues as discussed in the current manuscript.

3) I like that the authors stress in the beginning of the manuscript that all sampling and analyses are associated with error. This brings up a point on analytical precision and accuracy that is increasingly forgotten in the discussion of cryogenic artefacts. In particular accuracy of measurements is rarely reported in plant water papers but accuracy can easily be off by several permil (for H) between labs and thus produce similar biases as cryogenic artefacts. This is in particular relevant when data from different labs (e.g using xylem water data from one lab that are referenced to precip data from another lab (e.g. GNIP) or instrument) are related. Interestingly, few authors and referees seem to care about this. I acknowledge that this is not really the scope of this manuscript but the authors may want to mention this with a sentence or two to put cryogenic artefacts into perspective.

Ansgar Kahmen

Citation: https://doi.org/10.5194/hess-2020-683-RC2
- AC2: 'Reply on RC2', Scott T. Allen, 04 Jun 2021
  
  The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC2
RC3:
'Comment on hess-2020-683', Anonymous Referee #3, 04 May 2021

The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-RC3-supplement.pdf

Citation: https://doi.org/10.5194/hess-2020-683-RC3
- AC3: 'Reply on RC3', Scott T. Allen, 04 Jun 2021
  
  The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC3

Status: closed

RC1:
'Comment on hess-2020-683', Anonymous Referee #1, 08 Feb 2021

The manuscript underlines existing issues with cryogenic vacuum extraction of plant water for isotope analysis. The authors demonstrate via five case studies how δ²H biases resulting from this extraction method may lead to misleading conclusions when interpreting plant water sources.

The authors heavily rely on results of a study by Chen et al. (2020) without going much into detail about this study. This is often tricky for the reader (since details are not mentioned) and it requires going back and reading the study by Chen et al.

The authors apply a δ²H bias correction to a handful of plant source water studies. But what are the selection criteria of these case studies? The manuscript does not go far beyond the discussion section of the Chen et al. (2020) study. The application of an average bias correction factor determined by Chen et al. to a limited selection of other studies is not enough. Are the tree species from the selected case studies even covered in the study by Chen et al (2020)? Otherwise, I highly question the overall applicability of an average bias correction factor to different tree species (from your case studies) that may react differently during cryogenic vacuum extraction. This would result in the necessity to calculate different bias correction factor for specific plant species. Chen et al. (2020) stress the fact that species-specific differences in the cryogenically obtained δ²H values exist and need to be accounted for (together with data on stem relative water content).

Overall, the manuscript is a bit light. It would benefit from 1) case studies that include the tested species of the Chen et al. study 2) selecting more than five case studies to underline the statements and conclusions of the present study and 3) from including recommendations on how to perform bias correction on your own data and which factors to consider for that (species-specific differences, extraction system bias correction, isotope measurement accuracy etc.). The authors further ignore the well-known fact that cryogenic vacuum extraction from certain soil types causes isotope effects that need to be corrected for (such effects may also differ for the selected case studies). I admit that this is difficult when the raw data of the selected case studies is not available but this could be overcome by choosing newer studies where authors might be willing to share their data or where data is already publically available.

Further, it would be interesting to know if a bias correction is necessary and how a potential bias correction would look like for artificial isotope labeling studies. How would results be shifted?

My specific comments can be found in the attached pdf.

References

Chen, Y., Helliker, B. R., Tang, X., Li, F., Zhou, Y. and Song, X.: Stem water cryogenic extraction biases estimation in deuterium isotope composition of plant source water, PNAS, 117(52), 33345–33350, https://doi.org/10.1073/pnas.2014422117, 2020.

Citation: https://doi.org/10.5194/hess-2020-683-RC1
- AC1: 'Reply on RC1', Scott T. Allen, 12 Mar 2021
  
  See attached.
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC1
RC2:
'Comment on hess-2020-683', Ansgar Kahmen, 23 Apr 2021

This manuscript by Scott Allen and James Kirchner evaluates the effects caused by biased xylem water d2H measurements in the assessment of plant water sources. The manuscript is motivated by several recent reports suggesting biases in the isotopic composition of water that are associated with the cryogenic extraction of water from soils and plant materials. In particular, the authors refer to a recent paper by Chen et al. 2020 who suggest using d2H values obtained for cryogenically extracted xylem water should be corrected for an average bias of -8.1 per mil.

The paper starts off with an explanation of error propagation and lays down in mathematical terms how a systematic bias in d2H values of xylem water affects the application and uncertainty in two-pool mixing models. In essence, the authors conceptually demonstrate with this exercise that the described bias of -8.1 per mil may be of concern if endmembers in mixing models are not sufficiently resolved but that this bias is of less concern, if the end members are clearly distinct in their hydrogen isotope composition. The authors then demonstrate their case by re-evaluating several "classic" water sourcing papers and show how a -8.1 per mil bias challenges the conclusions on plant water sources in studies where mixing model endmembers are isotopically similar but has little effect in studies that use mixing model end members with larger isotopic differences.

I enjoyed reading this manuscript. It addresses a timely topic and puts the relevance of recent reports on measurement or extraction biases carefully into critical perspective. I think that such a contribution is clearly needed in a debate that starts to become overheated and influences scientific progress where it should not. At the same time the authors caution that there are indeed experimental settings, where uncertainties in the data don't allow robust conclusions regarding distinct tree water sources.

From my perspective this manuscript is an important contribution and it can pretty much be published as it is. There are a few thoughts that came to my mind but these are rather ideas or suggestions that the authors may or may not consider in their revisions:

1) I found the choice of sample studies a bit redundant. Maybe, the number of studies discussed could be reduced or substituted with studies that are slightly different in scope. In particular, I would suggest to also discuss work that is less focused on quantifying the absolute water sources of plants but rather seeks to identify species specific differences in water sources. In plant ecology this has been and still is an important topic. In these cases it is the relative difference of water sources among plants that is of interest. Irrespective of the isotopic resolution of the end members in a potential model, an extraction bias would affect all species and thus introduce a systematic error but would not affect the identified differences among species (given a consistent bias for all species ...).

2) The authors focus on the -8.1 per mil bias in d2H values of cryogenic extracted soil water that was recently suggested by Chen et al. The authors correctly mention that other biases in d2H values occurring during the extraction of soil water and/or water uptake by the roots exist and that biases have also been reported for d18O values. To put the evaluation of a -8.1 per mil bias in xylem water d2H into perspective, it might be good to report a few values form other studies indicating the order of magnitude in biases e.g. in soil water extractions of for d18O that other studies have reported and that would cause similar issues as discussed in the current manuscript.

3) I like that the authors stress in the beginning of the manuscript that all sampling and analyses are associated with error. This brings up a point on analytical precision and accuracy that is increasingly forgotten in the discussion of cryogenic artefacts. In particular accuracy of measurements is rarely reported in plant water papers but accuracy can easily be off by several permil (for H) between labs and thus produce similar biases as cryogenic artefacts. This is in particular relevant when data from different labs (e.g using xylem water data from one lab that are referenced to precip data from another lab (e.g. GNIP) or instrument) are related. Interestingly, few authors and referees seem to care about this. I acknowledge that this is not really the scope of this manuscript but the authors may want to mention this with a sentence or two to put cryogenic artefacts into perspective.

Ansgar Kahmen

Citation: https://doi.org/10.5194/hess-2020-683-RC2
- AC2: 'Reply on RC2', Scott T. Allen, 04 Jun 2021
  
  The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC2
RC3:
'Comment on hess-2020-683', Anonymous Referee #3, 04 May 2021

The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-RC3-supplement.pdf

Citation: https://doi.org/10.5194/hess-2020-683-RC3
- AC3: 'Reply on RC3', Scott T. Allen, 04 Jun 2021
  
  The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2020-683/hess-2020-683-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/hess-2020-683-AC3

Scott T. Allen and James W. Kirchner

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https://doi.org/10.5194/hess-2020-683-supplement

Scott T. Allen and James W. Kirchner

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Short summary

Extracting water from plant stems can introduce analytical errors in isotope analyses. We demonstrate that sensitivities to suspected errors can be evaluated and that conclusions drawn from extracted plant water isotope ratios are neither generally valid nor generally invalid. Ultimately, imperfect measurements of plant and soil water isotope ratios can continue to support useful inferences if study designs are appropriately matched to their likely biases and uncertainties.


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