the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Nov 2021
Microbial soil characteristics of grassland and arable soils linked to thermogravimetry data: correlations, use and limits
Abstract. Thermogravimetry (TG) is a simple method that enables rapid analysis of soil properties such as the content of total organic C, nitrogen, clay and C fractions with different stability. However, the possible link between TG data and microbiological soil properties has not been systematically tested yet and limits TG application for soil and soil organic matter assessment. This work aimed to search and to validate relationships of thermal mass losses (TML) to total C and N contents, microbial biomass C and N, basal and substrate-induced respiration, extractable organic carbon content, anaerobic ammonification, urease activity, short-term nitrification activity, specific growth rate, and time to reach the maximum respiration rate for two sample sets of arable and grassland soils. Analyses of the training soil set revealed significant correlations of TML with basic soil properties such as carbon and nitrogen content with distinguishing linear regression parameters and temperatures of correlating mass losses for arable and grassland soils. In a second stage the equations of significant correlations were used for validation with an independent second sample set. This confirmed applicability of developed equations for prediction of microbiological properties mainly for arable soils. For grassland soils was the applicability lower, which was explained as the influence of rhizosphere processes. Nevertheless, the application of TG can facilitate the understanding of changes in soil caused by microorganism’s activity and the different regression equations between TG and soil parameters reflect changes in proportions between soil components caused by land use management.
This preprint has been withdrawn.
-
Withdrawal notice
This preprint has been withdrawn.
-
Preprint
(422 KB)
-
Supplement
(1022 KB)
-
This preprint has been withdrawn.
- Preprint
(422 KB) - Metadata XML
-
Supplement
(1022 KB) - BibTeX
- EndNote
Interactive discussion
Status: closed
-
RC1: 'Comment on soil-2021-109', Anonymous Referee #1, 29 Nov 2021
General comment
This paper tries to connect soil thermal fractions with different chemical and biological properties. This connection is well referenced by literature and there are different studies reporting results about this topic. In this paper, authors change the common procedure trying to settle correlations using soil fractions from very narrow temperature ranges and they relate this narrow ranges versus total C, or total N or total microbial biomass and microbial activity. The last is difficult to understand and it is causing spurious correlations since those temperature intervals are changed based on the existence or not of the correlation. It is not clear the real goal of this work and which is the advantage of the procedure. Authors also report a high number of correlations without an interpretation of the equations obtained.
Specific comments
Introduction
Lines 45 to 50: It is truth that the organic mass lost by thermogravimetry can be overlapped with clay mass and carbonates depending on the clay types and clay content of samples, but evaporation occurs before the organic mass starts to combust and it can be determined by thermogravimetry as the mass lost from 50 to 180 ºC.
Lines 50-51: only to try to separate CO2 and water from clays and organic samples…….which is not possible even by those methods because the CO2 from clay and organic matter overlaps from 200 to 650 ºC. This is significant for soils with low organic C content but not for soil with high C content where the contribution of clay masses is very low. I do not think they can be argued as limitations in the superficial way that is done by authors.
Line 59: Check the sentence after the references. It is the term “vary” correct there?
Experimental
2.2 TG analysis and TML determination
Lines 85-86: Considering that samples are combusted through the temperature scan, and that water is lost only during the first 180 ºC (excepting adsorbed water in clays) and can be easily measured, what is the reason for the procedure exposed dealing with RH?
Lines 88-90: Most of studies using TG for soils report air flows of 50 ml/ min and temperature rates of 10 ºC / min. There is literature showing how these rates may change the evolution of the DTG curves. Is there any reason for changing those rates to 100 ml/min and 5 ºC / min?. Specifically, too fast air flow rates can limit the complete oxidation of the organic matter.
Lines 92-93: I do not know what you mean as “the obtained dependences of mass loss on temperature were averaged”. Do you mean the soil organic matter was fractionated for different temperature intervals and shown as the average of the three replicates done? What you write is not understandable.
2.3 Determination of chemical and MB properties of soils. What is MB here? Why do you symbolize Microbial soil properties as MB? Would not it mean Microbial Biomass, MB ?
Lines 125-127: Why the water content change from 60 % of WHC for RB to 40 % of WHC for Rs? Substrate induced respiration adding glucose depends on water content as basal respiration.
2.4 Statistical data treatment
What is TML/LTML´s ?
What is the sense of searching for correlation with TMLs for such a low interval of temperature, 10 ºC? What is the connection of a 10 ºC soil organic matter fraction with any of the mentioned properties? To me, that criterion may yield spurious correlations. In special if you use as a criterion to increase the temperature interval when there is not a correlation with the 10 ºC interval until you find the correlation.
Then, how you can compare two sets of independent samples that have “different number of samples”’? 11 grasslands versus 5 grasslands, and 21 arable samples versus 10? That is against the comparative criteria settled by statistics.
I do not think the statistical design be correct.
Results
Figure 1: Do you represent the same SOC of one sample versus the 94 different TMLs? What is the sense of this method? What is the advantage to show results by this way? From my perspective it results very confusing and difficult to interpret. Which is the meaning of the negative correlations observed for some of the parameters?
How can you explain the high correlation for RS values from 300 to 450 ºC if you added glucose? Priming effect? Is not the glucose added consumed but the C soil?
Line 172-173: Which are the criteria to select LTMLs? In fact, the fractions would be the ones settled for the labile and recalcitrant organic matter which is something very well known.
Which the usefulness or advantage of Table 1?
Discussion
Authors can not explain most of the results obtained excepting the common ones linked to chemical soil properties.
Arguments exposed for the differences of TN among grassland and arable lands are speculative. Lower correlation simply would involve less organic N since it is not as attached to the mass lost from 200 to 450 ºC as in grasslands. The content of inorganic C, clays and carbonates of the samples could be influencing also the results.
Lines 205-206: what do you mean as “prediction of microbial activity” by the TML? In special by TML100, the fraction where evaporation starts and volatiles taking part of the organic matter are lost.
Table 3: As an example, the first equation shows the highest correlation with SOC at 200-300 ºC for grasslands and at 300-450 for arable lands. Do you really think we must use that equation to calculate SOC from those intervals? What is the really meaning and advantage of those equations given for such a narrow range of temperature? What is the meaning of the slope , SOC per degree of temperature? Or is that most of the soil C is lost so fast from 200 to 300 ºC? What is the meaning of the ordinate, the A value of the straight line?
Table 4: That is only for the temperature interval given in Table 4? What is the criterion to settle the applicability?
With respect to Cbio: Can we consider calculating the soil microbial biomass by the equations in table 3? Both are quite similar with the exception of the A value. What about the difference?
Lines 260-265: It follows the same trend of the carbon. Why the correlation is lower with most of the parameters you use after 400 ºC? SOM percentages obtained by TG from 180 to 600ºC usually correlate well with total C and organic C in literature. That is the correct way to settle the correlation since what you measure is the total C and N in soil. Your procedure makes sense if you could obtain the C for the same temperature intervals by the elemental analysis.
Conclusions
First paragraph: This paragraph is confusing because of the vague definition of MB commented before. TG is an useful technique to calculate soil organic matter, SOM, and there are different references about correlations of the thermal SOM fractions given by the TG with soil elemental properties and even with soil microbial metabolism.
Lines 269 to 271: You have to check that in your paper. There is not experimental evidence in your paper for that conclusion.
Citation: https://doi.org/10.5194/soil-2021-109-RC1 -
AC1: 'Reply on RC1', Jiri Kucerik, 03 Feb 2022
The comment was uploaded in the form of a supplement: https://soil.copernicus.org/preprints/soil-2021-109/soil-2021-109-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Jiri Kucerik, 03 Feb 2022
-
RC2: 'Comment on soil-2021-109', Anonymous Referee #2, 28 Dec 2021
General comments
The authors present a manuscript where they attempt to connect incremental thermal mass loss (TML) to various metrics associated with soil quality indicators (SQI), soil health, and soil microbial activity. Standard protocols for assessing SQI typically require multiple subsamples that are prepared for different measurements at different moisture contents and narrow temperature ranges. Authors suggest that TML may be a feasible technique to acquire data for multiple SQI metrics with a single measurement by correlating TML to select SQI. The TML temperature ranges are compared to measurements of SQI and linear regression is used to create models that are predictive of SQI values based on TML measurements. Although the authors present an interesting case for investigating connections between TML and SQI, their analytical approach does not clearly answer their objective due to obscure correlations that are not clear in interpretation. The predictive equations generated from their modeled data do not seem to provide a more reliable method of interpreting SQI and the authors fail to make a case for why they believe the generated equations have merit for SQI assessment. A different approach to analysis is suggested, and if authors do not find an analysis that is more fitting to the objective, perhaps a different experimental design is also needed.
18 – SQI are not officially standardized into groups or arranged in any official capacity. Authors should mention that the SQI listed here are the ones that they have considered and that the listed parameters do not cover all SQI that could be measured
22 – physical, chemical, and biological soil properties can change because of slight or major soil modification. I suggest avoiding categorizing them in this way because it limits which SQI are chosen to represent different soil processes.
28 – What do the authors imply here by ‘number of methods’. Do you refer to different methods that measure the same property or different methods to measure different SQI?
45 – the authors state that mass losses using TG do not have a clear meaning unless connected to accessory information. This is partially accurate, but there are many experiments connecting TG measurements to accessory measurements in ways that greatly increase the ability for TG to be predictive of certain soil properties. Thinking specifically of how gravimetric water content is measured and how the C:N ratio to soil organic matter is measured. The authors suggest that fractionated TML may also be useful for assessing SQI but fail to reasonably address that existing methods are conducted at narrow temperature ranges because those narrow ranges are typically most associated with the property being measured. How does a single measurement of TML over all those ranges collect valuable information
85 – this step to reach the same relative humidity across all samples seems unnecessary. Many researchers would instead focus on reaching a constant dry mass before analysis
88 – what is the rationale for this heating rate? A heating rate of 5*C per minute from 20-950*C minutes is approximately 186 minutes of heating on a 0.2 g sample. Do the authors have a reason for this protocol and why they expected this to produce reasonable results? There is no reference mentioned in this section
102 – what is meant by water holding capacity compared to water content? I interpret this to mean the water holding capacity of an intact soil sample based on porosity, texture, and related factors. Was WHC measured on these soils based on their natural state before being disturbed?
141 – at this point in the manuscript, the term LTML has not been described. I think it should not be abbreviated here.
144 – how are the TML being correlated to soil parameters here. Is the same TML range for each soil sample being correlated to the soil parameter measurement for each soil sample? It seems like this is what is being done, but please elaborate more clearly for readers.
160 – Although people highly versed in the field may know this information, it is important to include citations about the 30-600*C temperature range you are referring to for SOM degradation.
169 – What is the meaning of the equations when two or more TML ranges are used. How are we to interpret the meaning of each variable attached to this equation?
171 – Does your selection of large thermal mass loss areas have a significant quantitative meaning? It seems that you have selected wide ranges but do not explain a meaning for each lower and upper limit. This is also important because LTML values from table 2 are used to determine which linear equations are appropriate for further discussion in table 3 and beyond.
179 – for table 4, are there fewer applicable results for grassland because grassland had a smaller sample size? This outcome should have more explanation.
190 – you state that the closeness between TML and LTML correlation is close with a few exceptions. Is there interpretation about why some correlations were not close and others were (other than TN, for which you do provide speculation)? Does it have something to do with the LTML ranges selected for correlation? Other factors?
193 – Although there is speculation about why TN was among the biggest differences between the two soil types, the authors neglect to mention the relevant temperature ranges for soil N and why correlations with TML outside of those ranges would have meaning in this measurement. Are the authors confident that N is a significant part of mass loss across the entire range specified?
200 - It is well known that microbial biomass C and N are correlated with SOM, but your interpretation does not explain why TML in different temperature ranges are useful for this interpretation. For example, many researchers measure SOM by combustion between 300-400*C. Why are measurements outside of this range also valuable? Please elaborate.
205 – Belaboring the point here, but this is important for discussion. Microbial respiration in soil and microbial activity above 100°C is unlikely to have much meaning in practical situations. A measurement above 200°C is unlikely to be predictive of any microbial activity unless the prediction is that there is little to no microbial activity. The vast majority of microbes and microbial exudates are not part of the active C fraction at this point and greater. What do these correlations mean?
211-221 – Similar criticisms toward interpretation of N compounds. The authors present speculation with little connection to the objective based on TML and its use to interpret and assess results for different SQI
234 – I would like to see more exploration about how these factors like MB, TN, SOC, etc. overlap in terms of TML within a certain range. Considering most of the temperatures in the incremental TML are outside of microbial activity range of soil, I am curious to know if the correlations are confounded by other factors that are not currently discussed in the manuscript. The authors should discuss this in order to make their argument for using this method more convincing.
239 – I think your data do not currently support the idea that rhizosphere inputs for grassland are what negatively affected the validation. As stated on line 247, the sample set is limited and unbalanced. Authors are far too speculative in this regard.
262 – Microbial activity can still be correlated with stable C fractions. This data has been observed. I am not confident that authors have shown that the thermal intervals measured in this way are associated with microbial activity. It would be interesting to see how the measured microbial and SOM parameters correlated to each other rather than the TML.
268 – TML may be a useful proxy for some soil analyses, but the way that authors have analyzed data in this manuscript does not show this. Interpretations in this manuscript drifted away from the proposed objective of showing how TML is connected to various SQI. Authors present very little data and interpretations that answer this question in a coherent way.
267 – authors make claims in this concluding paragraph that are not supported by their data and interpretations. TML does not appear to be a useful proxy for the soil analyses mentioned because authors did not present a strong case for a reliable or more convenient predictive model. The validation step failed in most cases for grassland soil and interpretations of the model for arable soil are not well supported in the manuscript. Authors may benefit from adjusting the overall objective and analysis methods so that the value of TML data is more apparent to readers, specifically for matters of SOM and its various fractions. The TML connection to microbial activity is likely confounded by chemical fractions of SOM that authors did not do a satisfactory job of parsing through in their results and interpretations.
Technical error
59 – the word ‘vary’ may be a typo with the intended word as ‘various’.
252 – I think the intention is to write ‘intermediate pools (…‘ rather than ‘intermediate (pools…’ Parenthesis after the word ‘pools’.
Figures 1 and 2 should include the full text of abbreviated terms in the description (e.g. SOC = soil organic carbon).
Citation: https://doi.org/10.5194/soil-2021-109-RC2 -
AC2: 'Reply on RC2', Jiri Kucerik, 03 Feb 2022
The comment was uploaded in the form of a supplement: https://soil.copernicus.org/preprints/soil-2021-109/soil-2021-109-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Jiri Kucerik, 03 Feb 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on soil-2021-109', Anonymous Referee #1, 29 Nov 2021
General comment
This paper tries to connect soil thermal fractions with different chemical and biological properties. This connection is well referenced by literature and there are different studies reporting results about this topic. In this paper, authors change the common procedure trying to settle correlations using soil fractions from very narrow temperature ranges and they relate this narrow ranges versus total C, or total N or total microbial biomass and microbial activity. The last is difficult to understand and it is causing spurious correlations since those temperature intervals are changed based on the existence or not of the correlation. It is not clear the real goal of this work and which is the advantage of the procedure. Authors also report a high number of correlations without an interpretation of the equations obtained.
Specific comments
Introduction
Lines 45 to 50: It is truth that the organic mass lost by thermogravimetry can be overlapped with clay mass and carbonates depending on the clay types and clay content of samples, but evaporation occurs before the organic mass starts to combust and it can be determined by thermogravimetry as the mass lost from 50 to 180 ºC.
Lines 50-51: only to try to separate CO2 and water from clays and organic samples…….which is not possible even by those methods because the CO2 from clay and organic matter overlaps from 200 to 650 ºC. This is significant for soils with low organic C content but not for soil with high C content where the contribution of clay masses is very low. I do not think they can be argued as limitations in the superficial way that is done by authors.
Line 59: Check the sentence after the references. It is the term “vary” correct there?
Experimental
2.2 TG analysis and TML determination
Lines 85-86: Considering that samples are combusted through the temperature scan, and that water is lost only during the first 180 ºC (excepting adsorbed water in clays) and can be easily measured, what is the reason for the procedure exposed dealing with RH?
Lines 88-90: Most of studies using TG for soils report air flows of 50 ml/ min and temperature rates of 10 ºC / min. There is literature showing how these rates may change the evolution of the DTG curves. Is there any reason for changing those rates to 100 ml/min and 5 ºC / min?. Specifically, too fast air flow rates can limit the complete oxidation of the organic matter.
Lines 92-93: I do not know what you mean as “the obtained dependences of mass loss on temperature were averaged”. Do you mean the soil organic matter was fractionated for different temperature intervals and shown as the average of the three replicates done? What you write is not understandable.
2.3 Determination of chemical and MB properties of soils. What is MB here? Why do you symbolize Microbial soil properties as MB? Would not it mean Microbial Biomass, MB ?
Lines 125-127: Why the water content change from 60 % of WHC for RB to 40 % of WHC for Rs? Substrate induced respiration adding glucose depends on water content as basal respiration.
2.4 Statistical data treatment
What is TML/LTML´s ?
What is the sense of searching for correlation with TMLs for such a low interval of temperature, 10 ºC? What is the connection of a 10 ºC soil organic matter fraction with any of the mentioned properties? To me, that criterion may yield spurious correlations. In special if you use as a criterion to increase the temperature interval when there is not a correlation with the 10 ºC interval until you find the correlation.
Then, how you can compare two sets of independent samples that have “different number of samples”’? 11 grasslands versus 5 grasslands, and 21 arable samples versus 10? That is against the comparative criteria settled by statistics.
I do not think the statistical design be correct.
Results
Figure 1: Do you represent the same SOC of one sample versus the 94 different TMLs? What is the sense of this method? What is the advantage to show results by this way? From my perspective it results very confusing and difficult to interpret. Which is the meaning of the negative correlations observed for some of the parameters?
How can you explain the high correlation for RS values from 300 to 450 ºC if you added glucose? Priming effect? Is not the glucose added consumed but the C soil?
Line 172-173: Which are the criteria to select LTMLs? In fact, the fractions would be the ones settled for the labile and recalcitrant organic matter which is something very well known.
Which the usefulness or advantage of Table 1?
Discussion
Authors can not explain most of the results obtained excepting the common ones linked to chemical soil properties.
Arguments exposed for the differences of TN among grassland and arable lands are speculative. Lower correlation simply would involve less organic N since it is not as attached to the mass lost from 200 to 450 ºC as in grasslands. The content of inorganic C, clays and carbonates of the samples could be influencing also the results.
Lines 205-206: what do you mean as “prediction of microbial activity” by the TML? In special by TML100, the fraction where evaporation starts and volatiles taking part of the organic matter are lost.
Table 3: As an example, the first equation shows the highest correlation with SOC at 200-300 ºC for grasslands and at 300-450 for arable lands. Do you really think we must use that equation to calculate SOC from those intervals? What is the really meaning and advantage of those equations given for such a narrow range of temperature? What is the meaning of the slope , SOC per degree of temperature? Or is that most of the soil C is lost so fast from 200 to 300 ºC? What is the meaning of the ordinate, the A value of the straight line?
Table 4: That is only for the temperature interval given in Table 4? What is the criterion to settle the applicability?
With respect to Cbio: Can we consider calculating the soil microbial biomass by the equations in table 3? Both are quite similar with the exception of the A value. What about the difference?
Lines 260-265: It follows the same trend of the carbon. Why the correlation is lower with most of the parameters you use after 400 ºC? SOM percentages obtained by TG from 180 to 600ºC usually correlate well with total C and organic C in literature. That is the correct way to settle the correlation since what you measure is the total C and N in soil. Your procedure makes sense if you could obtain the C for the same temperature intervals by the elemental analysis.
Conclusions
First paragraph: This paragraph is confusing because of the vague definition of MB commented before. TG is an useful technique to calculate soil organic matter, SOM, and there are different references about correlations of the thermal SOM fractions given by the TG with soil elemental properties and even with soil microbial metabolism.
Lines 269 to 271: You have to check that in your paper. There is not experimental evidence in your paper for that conclusion.
Citation: https://doi.org/10.5194/soil-2021-109-RC1 -
AC1: 'Reply on RC1', Jiri Kucerik, 03 Feb 2022
The comment was uploaded in the form of a supplement: https://soil.copernicus.org/preprints/soil-2021-109/soil-2021-109-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Jiri Kucerik, 03 Feb 2022
-
RC2: 'Comment on soil-2021-109', Anonymous Referee #2, 28 Dec 2021
General comments
The authors present a manuscript where they attempt to connect incremental thermal mass loss (TML) to various metrics associated with soil quality indicators (SQI), soil health, and soil microbial activity. Standard protocols for assessing SQI typically require multiple subsamples that are prepared for different measurements at different moisture contents and narrow temperature ranges. Authors suggest that TML may be a feasible technique to acquire data for multiple SQI metrics with a single measurement by correlating TML to select SQI. The TML temperature ranges are compared to measurements of SQI and linear regression is used to create models that are predictive of SQI values based on TML measurements. Although the authors present an interesting case for investigating connections between TML and SQI, their analytical approach does not clearly answer their objective due to obscure correlations that are not clear in interpretation. The predictive equations generated from their modeled data do not seem to provide a more reliable method of interpreting SQI and the authors fail to make a case for why they believe the generated equations have merit for SQI assessment. A different approach to analysis is suggested, and if authors do not find an analysis that is more fitting to the objective, perhaps a different experimental design is also needed.
18 – SQI are not officially standardized into groups or arranged in any official capacity. Authors should mention that the SQI listed here are the ones that they have considered and that the listed parameters do not cover all SQI that could be measured
22 – physical, chemical, and biological soil properties can change because of slight or major soil modification. I suggest avoiding categorizing them in this way because it limits which SQI are chosen to represent different soil processes.
28 – What do the authors imply here by ‘number of methods’. Do you refer to different methods that measure the same property or different methods to measure different SQI?
45 – the authors state that mass losses using TG do not have a clear meaning unless connected to accessory information. This is partially accurate, but there are many experiments connecting TG measurements to accessory measurements in ways that greatly increase the ability for TG to be predictive of certain soil properties. Thinking specifically of how gravimetric water content is measured and how the C:N ratio to soil organic matter is measured. The authors suggest that fractionated TML may also be useful for assessing SQI but fail to reasonably address that existing methods are conducted at narrow temperature ranges because those narrow ranges are typically most associated with the property being measured. How does a single measurement of TML over all those ranges collect valuable information
85 – this step to reach the same relative humidity across all samples seems unnecessary. Many researchers would instead focus on reaching a constant dry mass before analysis
88 – what is the rationale for this heating rate? A heating rate of 5*C per minute from 20-950*C minutes is approximately 186 minutes of heating on a 0.2 g sample. Do the authors have a reason for this protocol and why they expected this to produce reasonable results? There is no reference mentioned in this section
102 – what is meant by water holding capacity compared to water content? I interpret this to mean the water holding capacity of an intact soil sample based on porosity, texture, and related factors. Was WHC measured on these soils based on their natural state before being disturbed?
141 – at this point in the manuscript, the term LTML has not been described. I think it should not be abbreviated here.
144 – how are the TML being correlated to soil parameters here. Is the same TML range for each soil sample being correlated to the soil parameter measurement for each soil sample? It seems like this is what is being done, but please elaborate more clearly for readers.
160 – Although people highly versed in the field may know this information, it is important to include citations about the 30-600*C temperature range you are referring to for SOM degradation.
169 – What is the meaning of the equations when two or more TML ranges are used. How are we to interpret the meaning of each variable attached to this equation?
171 – Does your selection of large thermal mass loss areas have a significant quantitative meaning? It seems that you have selected wide ranges but do not explain a meaning for each lower and upper limit. This is also important because LTML values from table 2 are used to determine which linear equations are appropriate for further discussion in table 3 and beyond.
179 – for table 4, are there fewer applicable results for grassland because grassland had a smaller sample size? This outcome should have more explanation.
190 – you state that the closeness between TML and LTML correlation is close with a few exceptions. Is there interpretation about why some correlations were not close and others were (other than TN, for which you do provide speculation)? Does it have something to do with the LTML ranges selected for correlation? Other factors?
193 – Although there is speculation about why TN was among the biggest differences between the two soil types, the authors neglect to mention the relevant temperature ranges for soil N and why correlations with TML outside of those ranges would have meaning in this measurement. Are the authors confident that N is a significant part of mass loss across the entire range specified?
200 - It is well known that microbial biomass C and N are correlated with SOM, but your interpretation does not explain why TML in different temperature ranges are useful for this interpretation. For example, many researchers measure SOM by combustion between 300-400*C. Why are measurements outside of this range also valuable? Please elaborate.
205 – Belaboring the point here, but this is important for discussion. Microbial respiration in soil and microbial activity above 100°C is unlikely to have much meaning in practical situations. A measurement above 200°C is unlikely to be predictive of any microbial activity unless the prediction is that there is little to no microbial activity. The vast majority of microbes and microbial exudates are not part of the active C fraction at this point and greater. What do these correlations mean?
211-221 – Similar criticisms toward interpretation of N compounds. The authors present speculation with little connection to the objective based on TML and its use to interpret and assess results for different SQI
234 – I would like to see more exploration about how these factors like MB, TN, SOC, etc. overlap in terms of TML within a certain range. Considering most of the temperatures in the incremental TML are outside of microbial activity range of soil, I am curious to know if the correlations are confounded by other factors that are not currently discussed in the manuscript. The authors should discuss this in order to make their argument for using this method more convincing.
239 – I think your data do not currently support the idea that rhizosphere inputs for grassland are what negatively affected the validation. As stated on line 247, the sample set is limited and unbalanced. Authors are far too speculative in this regard.
262 – Microbial activity can still be correlated with stable C fractions. This data has been observed. I am not confident that authors have shown that the thermal intervals measured in this way are associated with microbial activity. It would be interesting to see how the measured microbial and SOM parameters correlated to each other rather than the TML.
268 – TML may be a useful proxy for some soil analyses, but the way that authors have analyzed data in this manuscript does not show this. Interpretations in this manuscript drifted away from the proposed objective of showing how TML is connected to various SQI. Authors present very little data and interpretations that answer this question in a coherent way.
267 – authors make claims in this concluding paragraph that are not supported by their data and interpretations. TML does not appear to be a useful proxy for the soil analyses mentioned because authors did not present a strong case for a reliable or more convenient predictive model. The validation step failed in most cases for grassland soil and interpretations of the model for arable soil are not well supported in the manuscript. Authors may benefit from adjusting the overall objective and analysis methods so that the value of TML data is more apparent to readers, specifically for matters of SOM and its various fractions. The TML connection to microbial activity is likely confounded by chemical fractions of SOM that authors did not do a satisfactory job of parsing through in their results and interpretations.
Technical error
59 – the word ‘vary’ may be a typo with the intended word as ‘various’.
252 – I think the intention is to write ‘intermediate pools (…‘ rather than ‘intermediate (pools…’ Parenthesis after the word ‘pools’.
Figures 1 and 2 should include the full text of abbreviated terms in the description (e.g. SOC = soil organic carbon).
Citation: https://doi.org/10.5194/soil-2021-109-RC2 -
AC2: 'Reply on RC2', Jiri Kucerik, 03 Feb 2022
The comment was uploaded in the form of a supplement: https://soil.copernicus.org/preprints/soil-2021-109/soil-2021-109-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Jiri Kucerik, 03 Feb 2022
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 564 | 192 | 36 | 792 | 77 | 23 | 21 |
- HTML: 564
- PDF: 192
- XML: 36
- Total: 792
- Supplement: 77
- BibTeX: 23
- EndNote: 21
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Cited
Helena Doležalová-Weissmannová
Stanislav Malý
Martin Brtnický
Jiří Holátko
Michael Scott Demyan
Christian Siewert
David Tokarski
Eliška Kameníková
This preprint has been withdrawn.
- Preprint
(422 KB) - Metadata XML
-
Supplement
(1022 KB) - BibTeX
- EndNote