the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Apr 2025
A global meta-analysis of rhizosphere impacts on soil and microbial stoichiometry in agroecosvstems
Abstract. The stoichiometry of the rhizosphere, particularly concerning carbon (C), nitrogen (N), and phosphorus (P), reflects the balance between nutrient mineralization and retention during organic matter decomposition. However, the magnitude and underlying mechanisms of rhizospheric influences on soil and microbial stoichiometry remain insufficiently quantified at the global scale across diverse agroecosystems. This study synthesizes data from 113 peer-reviewed sources, encompassing 882 individual observations. The results reveal that the rhizosphere significantly increases soil C:N, C:P, and N:P ratios, while concurrently decreasing microbial C:N, C:P, and N:P ratios relative to bulk soil conditions. Notably, the rhizospheric effects on soil C:N ratios is amplified in humid regions and diminished in arid environments. In contrast the influence on microbial C:N exhibits a positive correlation with increasing soil organic C and ammonium N concentrations. Moreover, sensitive crops such as maize and vegetables enhance the rhizospheric soil C:N ratio by 5.68 % and 8.91 % respectively, while reducing the microbial C:N ratio by 11.00 % and 19.44 %. Soil organic C and ammonium N emerge as key determinants of rhizospheric soil and microbial C:N ratios, contributing 37.9 % and 30.3 % to their varations, respectively. The study establishes a coupled relationship between rhizospheric soil and microbial stoichiometry. These findings offer critical insights into rhizospheric nutrient cycling, which are essentials for improving soil health and optimizing nutrient use efficiency through targeted management practices.
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Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-1382', Anonymous Referee #1, 23 May 2025
This is a meta-analysis study of broad applied significance, providing the first systematic assessment of the rhizosphere influences on ecological stoichiometry in global agricultural systems. However, the current manuscript has major shortcomings.
The introduction and discussion are disorganized, with abrupt transitions that hinder the logical flow.
When describing your results, please use terms like 'significantly' or report P-values, and ensure consistency throughout the manuscript.
There are numerous grammatical errors and unclear expressions and should be edited by a native English speaker or a professional scientific editing service, to ensure grammatical accuracy and fluency. Substantial revisions are required before the scientific rigor and readability of the paper can be properly evaluated.
More details below:
L22, “is” to “are”
L24, what’s “sensitive crops”?
L38, “root a activity”?
L44-45, Repeat the importance of agroecosystems is not necessary
L 47-48 “This knowledge is vital for….” is not necessary
L50-52, I don’t understand here, please rephrase.
L54-59, is it necessary? The logical is a little broken
L68, what’s “soil P ratio”?
L70-71, please add the references
L90, please highlight your work at the end of this paragraph and explain your hypothesis
L111, “822”? it is not consistent with “882” in abstract, I am not sure how many observations do you have.
L122, how did you get the missing latitude and longitude data from google map, I mean sometimes, they provide the name, but maybe it is a huge area, like a province.
L124-125, you have some Climatic data from the targeted literatures and some from Worldclimate, did you compare the data here?
L135-145, please provide classification criteria, reference or something you consider
L147, please clarify what your random factors are.
L167, why did you consider median value other than mean value?
L176-178, some grammatical errors, please check.
L193 “the selected environmental variables explained…”, please be specific, which variables?
L202-203, something I can’t follow, seems to be a repeat description
L211, grammatical errors, please check
L213, you didn’t define “TN” before.
L249-250, I can’t follow “reflecting projected precipitation ….”
L251, why do you mention climate change? It is a logical jump here.
L279-280, I didn’t see any necessary to say “Increased acidity can alter SOC quality and composition” here
L288, what’s “stoichiometric decomposition theory”? please explain it a little bit and add the reference.
L303-304, remove “variable” and rephrase this sentence
L306, “altered soil textures C, N, and P cycles”, rephrase this sentence
L309-310, There is an over-inference here, it is correlation, not causation
Fig.1, I didn’t see where is the letters and what’s the meaning of the “◆”?
Citation: https://doi.org/10.5194/egusphere-2025-1382-RC1 -
AC1: 'Reply on RC1', Andong Cai, 28 Jun 2025
Reviewer #1:
This is a meta-analysis study of broad applied significance, providing the first systematic assessment of the rhizosphere influences on ecological stoichiometry in global agricultural systems. However, the current manuscript has major shortcomings.
- The introduction and discussion are disorganized, with abrupt transitions that hinder the logical flow.
When describing your results, please use terms like 'significantly' or report P-values, and ensure consistency throughout the manuscript. There are numerous grammatical errors and unclear expressions and should be edited by a native English speaker or a professional scientific editing service, to ensure grammatical accuracy and fluency. Substantial revisions are required before the scientific rigor and readability of the paper can be properly evaluated.
Re: We thank you for recognizing the significance of our work and for the helpful suggestions. We have now substantially revised the Introduction and Discussion to improve logical flow and clarity. We have also carefully checked and corrected grammatical issues and improved the consistency in terminology, particularly in reporting statistical results (e.g., indicating significance levels and P-values). A professional language editing service has been consulted to ensure fluency and correctness.
More details below:
- L22, “is” to “are”
Re: Corrected to “are” to maintain subject-verb agreement.
- L24, what’s “sensitive crops”?
Re: To avoid ambiguity, we have removed the expression “sensitive crops” without affecting the meaning of the sentence
- L38, “root a activity”?
Re: Corrected to “root activity.”
- L44-45, Repeat the importance of agroecosystems is not necessary
Re: Thanks, we agree with your comment and have deleted this sentence.
- L 47-48 “This knowledge is vital for….” is not necessary
Re: Thanks, we agree with your comment and have deleted this sentence.
- L50-52, I don’t understand here, please rephrase.
Re: Thanks, we agree with your comment and have deleted this sentence.
- L54-59, is it necessary? The logical is a little broken
Re: Thanks, we agree with your suggestion, and this paragraph has been revised for better logical flow.
Before revised: Ecological stoichiometry, a discipline focused on the balance and interactions of key elements in ecosystems, has provided valuable insights into individual growth population dynamics, limiting factors, community succession, and vegetation stability (Güsewell, 2004). understanding individual growth (Güsewell, 2004). Soil C:N:P ratios vary significantly due to differences in vegetation type and soil organic matter content (Luo et al., 2020). Microbial communities respond to stoichiometric changes in four primary ways: First, adjusting biomass composition to match available resources, though these changes are generally modest and driven more by shifts in microbial community structure than by cellular storage. Second, mobilizing resources via enzyme production, which is often limited by C and N availability (Ashraf et al., 2021). Third, regulating element use efficiency allow for the release of excess nutrients. Fourthly, utilizing diastrophic bacteria and saprotrophic fungi to acquiring exogenous N and P (Mooshammer et al., 2014). Globally, current knowledge on soil and microbial biomass stoichiometry is primarily focused on bulk soil (Luo et al., 2020). However, rhizospheric nutrients and microbial communities are more susceptible to environmental fluctuations than those in bulk soil. Thus, a comprehensive understanding of rhizospheric characteristics and their interactive stoichiometric interactions is crucial for improving agroecosystem productivity and management. This insight is critical for developing strategies that enhance soil fertility, optimize nutrient use efficiency, and support sustainable agricultural practices worldwide.
After revised: Ecological stoichiometry, which examines the elemental balance and interactions within ecosystems, offers a powerful framework to explore the nutrient dynamics in the rhizosphere (Güsewell, 2004). The stoichiometric ratios of C:N:P in soils and microbial biomass are widely used as indicators of nutrient cycling and ecosystem functioning (Cleveland and Liptzin, 2007). Soil C:N:P ratios integrate long-term processes such as organic input, decomposition, mineral weathering, and nutrient retention, thereby reflecting the cumulative nutrient status of the soil matrix (Tipping et al., 2016). In contrast, microbial biomass C:N:P ratios are sensitive indicators of the physiological demands of soil microorganisms, responding more rapidly to environmental fluctuations (Gao et al., 2022; Wasner et al., 2024). While microbial C:N:P ratios tend to remain relatively constrained across ecosystems due to homeostatic regulation, soil stoichiometry varies more widely due to complex biotic and abiotic influences (Chen and Chen, 2021). Rhizospheric processes further shape both soil and microbial stoichiometry by modifying nutrient availability and altering microbial community structure and function (Bell et al., 2014a). Despite this, most studies have examined either bulk soil or rhizosphere soil independently, without fully characterizing the differences in stoichiometric patterns and their underlying drivers (Luo et al., 2020). A more integrative understanding of rhizospheric stoichiometry is essential for informing management practices aimed at enhancing soil fertility, improving nutrient use efficiency, and sustaining agroecosystem productivity under changing environmental conditions.
- L68, what’s “soil P ratio”?
Re: Thanks, we have revised to “soil P:N ratio”.
- L70-71, please add the references
Re: Additional supporting references have been added (Jones et al., 2018; Pei et al., 2024).
- L90, please highlight your work at the end of this paragraph and explain your hypothesis
Re: Revised to explicitly state the novelty of our global-scale rhizosphere meta-analysis and clearly articulated two hypotheses
Before revised: Although previous studies have extensively examined the C:N:P stoichiometry in soils, plants, and microbes across natural and managed ecosystems, agricultural rhizospheric soils are often underrepresented. To fill this gap, we compiled a comprehensive dataset comprising 882 unique cases from 113 peer-reviewed sources across global agroecosystems. The objectives of this study were to: (1) quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry across global agroecosystems; and (2) identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry.
After revised: Although the rhizosphere’s unique biogeochemical properties are increasingly recognized, its stoichiometric distinctions from bulk soil have not been systematically evaluated on a global scale. Moreover, the extent to which these patterns are governed by climate, soil properties, and management remains poorly resolved. To address this knowledge gap, we assembled a global dataset comprising 1,673 unique cases from 121 peer-reviewed studies encompassing diverse agroecosystems. Our study aimed to (1) quantify the patterns and coupling relationships of rhizospheric soil and microbial stoichiometry at a global scale and (2) identify the environmental and management-related drivers of these patterns. We hypothesized that that (1) rhizospheric soils would exhibit significantly higher C:N and C:P ratios but lower microbial biomass C:N ratios than bulk soils due to root-induced nutrient enrichment and microbial activation, and (2) these differences would be strongly modulated by aridity, soil organic carbon content, and ammonium nitrogen availability.
- L111, “822”? it is not consistent with “882” in abstract, I am not sure how many observations do you have.
Re: This was an error. After updating the literature, we confirmed the correct number to be 1,683 and have revised it accordingly throughout the Abstract and Methods sections.
- L122, how did you get the missing latitude and longitude data from google map, I mean sometimes, they provide the name, but maybe it is a huge area, like a province.
Re: Thank you for this insightful comment. We acknowledge that our initial explanation was not sufficiently detailed. We have now clarified this section in the revised manuscript. Specifically, for studies that did not report geographic coordinates, we adopted a three-step approach:
(1) We first searched for other publications by the authors to find related studies that might contain location information;
(2) If such information could not be retrieved, we contacted the corresponding author directly via email to request site coordinates;
(3) If neither of these approaches yielded the necessary data, we excluded the study from our analysis.
This clarification has been added to the Methods section, and we now acknowledge the associated uncertainties in the Discussion as a potential limitation of our dataset.
- L124-125, you have some Climatic data from the targeted literatures and some from Worldclimate, did you compare the data here?
Re: Thank you for your comment. Since the temperature and precipitation data used in our analysis are long-term averages, they are relatively stable over time. The corresponding indicators provided by WorldClim are widely recognized for their representativeness and have been cited in numerous high-impact international journals. Therefore, we directly used the climatic data obtained from WorldClim in our study.
In response to your suggestion, we further compared part of the climatic data extracted directly from the original publications with the corresponding values obtained from WorldClim. The results showed no significant differences between the two sources, which further supports the reliability of using WorldClim data in our analysis.- L135-145, please provide classification criteria, reference or something you consider
Re: Thanks, we have added some references and provide corresponding explanationsfor some classification.
- L147, please clarify what your random factors are.
Re: Thanks, we have clarified the random factors.
After revised: Linear mixed-effects models were used to evaluate the influence of environmental factors—climatic zone, AI, crop type, fertilization, tillage, crop growth stage, SOC, soil pH, NO3--N, and NH₄⁺-N—on rhizospheric differences in stoichiometric ratios.
- L167, why did you consider median value other than mean value?
Re: Thank you for your suggestion. Considering the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L176-178, some grammatical errors, please check.
Re: Sentences rephrased for clarity and checked during language polishing
- L193 “the selected environmental variables explained…”, please be specific, which variables?
Re: Thanks, we have clarified the variables (including AI, crop types, fertilization, SOC, pH, TP, AP, NO3—N, and NH4+-N).
- L202-203, something I can’t follow, seems to be a repeat description
Re: Thanks, we have revised this description, please check it.
- L211, grammatical errors, please check
Re: Sentence rewritten during editing.
- L213, you didn’t define “TN” before.
Re: Now defined as “total nitrogen (TN)” at its first occurrence.
- L249-250, I can’t follow “reflecting projected precipitation ….”
Re: Thank you for pointing out our mistake. This is an incomplete statement, as detailed below:
After revised: As aridity increases, soil C:P and N:P ratios tend to decline, while C:N ratios increase, suggesting that continued warming and reduced precipitation could decouple C-N-P cycling and limit plant productivity in arid agroecosystems.
- L251, why do you mention climate change? It is a logical jump here.
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L279-280, I didn’t see any necessary to say “Increased acidity can alter SOC quality and composition” here
Re: Thanks, we agree with your suggestion and have removed this sentence.
- L288, what’s “stoichiometric decomposition theory”? please explain it a little bit and add the reference.
Re: Thank you for your suggestion and we have explained it a little bit and add the reference.
- L303-304, remove “variable” and rephrase this sentence
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L306, “altered soil textures C, N, and P cycles”, rephrase this sentence
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L309-310, There is an over-inference here, it is correlation, not causation
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- Fig.1, I didn’t see where is the letters and what’s the meaning of the “◆”?
Re: Thanks, we have revised the figure legends to clearly explain.
Citation: https://doi.org/10.5194/egusphere-2025-1382-AC1
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AC1: 'Reply on RC1', Andong Cai, 28 Jun 2025
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RC2: 'Comment on egusphere-2025-1382', Anonymous Referee #2, 24 May 2025
The manuscript provides a meta-analysis comparing the soil and microbial biomass stochiometric relations between the rhizosphere and non-rhizosphere (bulk soil) from worldwide agroecosystems. This work fits within the scope of the Biogeoscience journal. However, it lacks multiple key elements to be accepted for publication.
The article pursues two objectives: 1) to quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry from agroecosystems and 2) to identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry. The introduction is repetitive in parts (e.g., lines 47-48, 63-65, 81-83) and overlooks the presentation of the agroecosystems management effect on soil and rhizosphere stochiometry. The authors omitted the potential influence of agroecosystem management and restricted their analysis to pedoclimatic effects, which may be misleading due to confounded effects. Several details in the methodology are missing, and sentences that do not follow a logical narrative (e.g., 93-98). The collection of studies does not follow minimum guidelines (e.g., PRISMA), which guarantees standards to perform the data collection and meta-analysis. The manuscript requires exhaustive inclusion and exclusion criteria for the references gathered during the bibliographic search. The conditions for the data extraction (e.g., soil depth(s), average over the season, or final point over the season) are not clear from the study. This is important when dealing with data dependencies (pseudoreplication) during data analysis. Moreover, the definition of control treatments is unclear, and there are no details about how the response ratio was calculated or transformed (to the percentage of change) for interpretation. The authors gave limited justification for discretizing abiotic factors to assess their effect (lines 133-145). The presentation of results is insufficient, lacking the description of the statistical model (e.g., weighting and random components), sensitivity and influence analyses, and heterogeneity indicators to study the effect of abiotic features and other factors properly. Moreover, there are insufficient details about the global distribution of the observations and their effect sizes, which will help assess the representativeness of the dataset. The assessment of other moderators, such as main agronomic practices (e.g., fertilization source or organic matter incorporation), should be incorporated, given their potential importance in regulating stoichiometric relations. The authors complemented their meta-analysis with a boosted regression tree, but insufficient details regarding the hyperparameter optimization and the response and predictor variables are provided. I recommend starting the results section by giving an overview of data regarding the geographic distribution in function of different stochiometric relations, pedoclimatic conditions, and management practices. Several grammatical, semantic, and punctuation errors need to be revised (e.g., lines 38, 51, 317). I encourage the authors to store the dataset and code in an open repository to increase the credibility of their meta-analysis. For these reasons, I recommend that the authors undertake an extensive major revision before the manuscript can be considered for publication.
Citation: https://doi.org/10.5194/egusphere-2025-1382-RC2 -
AC2: 'Reply on RC2', Andong Cai, 28 Jun 2025
Reviewer #2:
The manuscript provides a meta-analysis comparing the soil and microbial biomass stochiometric relations between the rhizosphere and non-rhizosphere (bulk soil) from worldwide agroecosystems. This work fits within the scope of the Biogeoscience journal. However, it lacks multiple key elements to be accepted for publication.
- The article pursues two objectives: 1) to quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry from agroecosystems and 2) to identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry. The introduction is repetitive in parts (e.g., lines 47-48, 63-65, 81-83) and overlooks the presentation of the agroecosystems management effect on soil and rhizosphere stochiometry.
Re: Thank you for pointing this out. We have significantly revised the Introduction to remove redundant statements and improve clarity. Specifically: Lines 47-48, 63-65, and 81-83 were either deleted or rephrased to avoid repetition. We also incorporated the importance of agroecosystem management, as you suggested. Please check the part of Introduction.
- The authors omitted the potential influence of agroecosystem management and restricted their analysis to pedoclimatic effects, which may be misleading due to confounded effects.
Re: Thank you for pointing this out. We agree that agroecosystem management plays a vital role in shaping soil and rhizosphere stoichiometry. In the revised manuscript: (1) We expanded the Introduction and Discussion to explicitly highlight how practices such as fertilization, tillage, and organic matter addition can affect rhizosphere nutrient dynamics. (2) In addition, we have added analysis on management measures such as fertilization and tillage in the manuscript.
- Several details in the methodology are missing, and sentences that do not follow a logical narrative (e.g., 93-98).
Re: Thanks, we agree with your comment and have removed these sentences.
- The collection of studies does not follow minimum guidelines (e.g., PRISMA), which guarantees standards to perform the data collection and meta-analysis. The manuscript requires exhaustive inclusion and exclusion criteria for the references gathered during the bibliographic search
Re: We appreciate this critical point. Although PRISMA is typically used in clinical meta-analyses, we agree that a structured framework improves transparency. In the revised manuscript: We added a detailed workflow diagram following PRISMA guidelines (Fig. S1), including: literature search, screening, eligibility, inclusion criteria, and final study count. Additionally, we have made corresponding revisions in the Materials and Methods section to enhance the reliability of our data.
- The conditions for the data extraction (e.g., soil depth(s), average over the season, or final point over the season) are not clear from the study. This is important when dealing with data dependencies (pseudoreplication) during data analysis
Re: Thank you for this observation.
(1) Considering that our research focuses on agricultural crops and their root systems are mostly distributed in the topsoil layer of 0-20 cm, we mainly focused on the topsoil layer when collecting data. In the revised manuscript: We added clarification that only data from the topsoil layer were included.
(2) Given that microbial stoichiometric ratios can vary substantially across plant growth stages, we collected data not only at harvest but also during other key developmental stages to ensure a more comprehensive analysis. Based on your feedback, we have incorporated subgroup analyses based on growth stages (Fig. 4), which have further enhanced the accuracy and robustness of our findings.
- Moreover, the definition of control treatments is unclear, and there are no details about how the response ratio was calculated or transformed (to the percentage of change) for interpretation.
Re: We apologize for the oversight. In the revised Materials and Methods, we now clearly define control treatments as the bulk soil adjacent to rhizosphere zones, sampled from the same plots and under the same management conditions. Moreover, we also provided the detail equations about how the response ratio was calculated or transformed (2.3 Meta-analysis).
- The authors gave limited justification for discretizing abiotic factors to assess their effect (lines 133-145).
Re: We appreciate this point. We have now added a detailed rationale for discretization:
(1) For continuous variables (e.g., AI, SOC, NH4+-N, and pH) were initially assessed using line regression (Fig. 7 and S5), and subgroups were divided based on the frequency of data distribution.
(2) For categorical analysis (e.g., climate zones, crop types, fertilization, and tillage), we discretized variables into quantiles based on the previous study.
(3) We also added some reference that support such discretization strategies in ecological meta-analyses (e.g., Xu et al., 2021b; Zomer et al., 2022; Cai et al., 2023)
- The presentation of results is insufficient, lacking the description of the statistical model (e.g., weighting and random components), sensitivity and influence analyses, and heterogeneity indicators to study the effect of abiotic features and other factors properly.
Re: We thank the reviewer for highlighting this important issue. We have significantly expanded the statistical methods section:
(1) All models were run using the metafor package in R, employing a random-effects model with study identity as a random factor.
(2) Each effect size was weighted by the inverse of its variance.
(3) We now report heterogeneity statistics (Q, τ², I²) for each model.
(4) Funnel plots were employed to assess publication bias (Figs. S2).
- Moreover, there are insufficient details about the global distribution of the observations and their effect sizes, which will help assess the representativeness of the dataset.
Re: We have added a global map of the observation’s locations and their effect sizes (new Fig. 1). We also discussed the potential spatial biases and representativeness in the revised Discussion.
- The assessment of other moderators, such as main agronomic practices (e.g., fertilization source or organic matter incorporation), should be incorporated, given their potential importance in regulating stoichiometric relations.
Re: As mentioned above, we now include management-related moderators (fertilization type and tillage) in meta-regression models (Figs. 3 and 4).
- The authors complemented their meta-analysis with a boosted regression tree, but insufficient details regarding the hyperparameter optimization and the response and predictor variables are provided.
Re: We appreciate the reviewer's comment regarding the boosted regression tree (BRT) analysis details. In our study, the BRT was implemented using the 'dismo' package in R (v4.2.0) with the rhizospheric soil and microbial C:N ratio as the response variable and environmental factors (climate, soil properties, and management) as predictors. Key hyperparameters were optimized through 10-fold cross-validation: learning rate (0.005), tree complexity (3), bag fraction (0.75), and number of trees (1500 determined by early stopping). Model performance was evaluated via cross-validated deviance explained. These methodological details have been added to Section 2.4 of the revised manuscript.
- I recommend starting the results section by giving an overview of data regarding the geographic distribution in function of different stochiometric relations, pedoclimatic conditions, and management practices.
Re: As mentioned above, we added a global map of the observation’s locations and their effect sizes at the starting of the results section.
- Several grammatical, semantic, and punctuation errors need to be revised (e.g., lines 38, 51, 317).
Re: We acknowledge this and have carefully revised the manuscript for grammar, clarity, and scientific language. A native English-speaking editor with expertise in ecology performed full language editing.
- I encourage the authors to store the dataset and code in an open repository to increase the credibility of their meta-analysis.
Re: We fully support open science. We have added all the literature related to the dataset in the supplementary and the dataset and code will be made available on request.
EIC Comments:
1.) Lines 363-648 - Format for full citation references here do not conform to the requested journal type. This includes missing an ampersand (&) before the last author's name in citations with 7 or less authors, listing more than 7 authors (if more than 7, list #1 to #6, then " ... ", then last author's name), use of a comma before the year, missing parentheses around the year, use of comma after the journal name, italicization of the journal name and volume number, etc. Please see the instructions to authors, and revise these to match that format. See https://www.keaipublishing.com/en/journals/international-soil-and-water-conservation-research/guide-for-authors/Re: Thanks for your suggestions and we have revised it based on the request. Moreover, the English expression of the whole manuscript has been professionally edited for English usage, grammar, spelling, and punctuation by a native English speaker and a skilled professional editor. Therefore, we would appreciate it if any comments regarding language.
We deeply thank you again for your comprehensive and insightful review. Your feedback has helped us substantially improve the rigor, structure, and clarity of our manuscript. We hope that the revised version addresses all your concerns and meets the standard for publication. Thanks again for your kind evaluation and suggestions to improve our current manuscript, and we look forward to receiving your valuable reply.
Citation: https://doi.org/10.5194/egusphere-2025-1382-AC2
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AC2: 'Reply on RC2', Andong Cai, 28 Jun 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-1382', Anonymous Referee #1, 23 May 2025
This is a meta-analysis study of broad applied significance, providing the first systematic assessment of the rhizosphere influences on ecological stoichiometry in global agricultural systems. However, the current manuscript has major shortcomings.
The introduction and discussion are disorganized, with abrupt transitions that hinder the logical flow.
When describing your results, please use terms like 'significantly' or report P-values, and ensure consistency throughout the manuscript.
There are numerous grammatical errors and unclear expressions and should be edited by a native English speaker or a professional scientific editing service, to ensure grammatical accuracy and fluency. Substantial revisions are required before the scientific rigor and readability of the paper can be properly evaluated.
More details below:
L22, “is” to “are”
L24, what’s “sensitive crops”?
L38, “root a activity”?
L44-45, Repeat the importance of agroecosystems is not necessary
L 47-48 “This knowledge is vital for….” is not necessary
L50-52, I don’t understand here, please rephrase.
L54-59, is it necessary? The logical is a little broken
L68, what’s “soil P ratio”?
L70-71, please add the references
L90, please highlight your work at the end of this paragraph and explain your hypothesis
L111, “822”? it is not consistent with “882” in abstract, I am not sure how many observations do you have.
L122, how did you get the missing latitude and longitude data from google map, I mean sometimes, they provide the name, but maybe it is a huge area, like a province.
L124-125, you have some Climatic data from the targeted literatures and some from Worldclimate, did you compare the data here?
L135-145, please provide classification criteria, reference or something you consider
L147, please clarify what your random factors are.
L167, why did you consider median value other than mean value?
L176-178, some grammatical errors, please check.
L193 “the selected environmental variables explained…”, please be specific, which variables?
L202-203, something I can’t follow, seems to be a repeat description
L211, grammatical errors, please check
L213, you didn’t define “TN” before.
L249-250, I can’t follow “reflecting projected precipitation ….”
L251, why do you mention climate change? It is a logical jump here.
L279-280, I didn’t see any necessary to say “Increased acidity can alter SOC quality and composition” here
L288, what’s “stoichiometric decomposition theory”? please explain it a little bit and add the reference.
L303-304, remove “variable” and rephrase this sentence
L306, “altered soil textures C, N, and P cycles”, rephrase this sentence
L309-310, There is an over-inference here, it is correlation, not causation
Fig.1, I didn’t see where is the letters and what’s the meaning of the “◆”?
Citation: https://doi.org/10.5194/egusphere-2025-1382-RC1 -
AC1: 'Reply on RC1', Andong Cai, 28 Jun 2025
Reviewer #1:
This is a meta-analysis study of broad applied significance, providing the first systematic assessment of the rhizosphere influences on ecological stoichiometry in global agricultural systems. However, the current manuscript has major shortcomings.
- The introduction and discussion are disorganized, with abrupt transitions that hinder the logical flow.
When describing your results, please use terms like 'significantly' or report P-values, and ensure consistency throughout the manuscript. There are numerous grammatical errors and unclear expressions and should be edited by a native English speaker or a professional scientific editing service, to ensure grammatical accuracy and fluency. Substantial revisions are required before the scientific rigor and readability of the paper can be properly evaluated.
Re: We thank you for recognizing the significance of our work and for the helpful suggestions. We have now substantially revised the Introduction and Discussion to improve logical flow and clarity. We have also carefully checked and corrected grammatical issues and improved the consistency in terminology, particularly in reporting statistical results (e.g., indicating significance levels and P-values). A professional language editing service has been consulted to ensure fluency and correctness.
More details below:
- L22, “is” to “are”
Re: Corrected to “are” to maintain subject-verb agreement.
- L24, what’s “sensitive crops”?
Re: To avoid ambiguity, we have removed the expression “sensitive crops” without affecting the meaning of the sentence
- L38, “root a activity”?
Re: Corrected to “root activity.”
- L44-45, Repeat the importance of agroecosystems is not necessary
Re: Thanks, we agree with your comment and have deleted this sentence.
- L 47-48 “This knowledge is vital for….” is not necessary
Re: Thanks, we agree with your comment and have deleted this sentence.
- L50-52, I don’t understand here, please rephrase.
Re: Thanks, we agree with your comment and have deleted this sentence.
- L54-59, is it necessary? The logical is a little broken
Re: Thanks, we agree with your suggestion, and this paragraph has been revised for better logical flow.
Before revised: Ecological stoichiometry, a discipline focused on the balance and interactions of key elements in ecosystems, has provided valuable insights into individual growth population dynamics, limiting factors, community succession, and vegetation stability (Güsewell, 2004). understanding individual growth (Güsewell, 2004). Soil C:N:P ratios vary significantly due to differences in vegetation type and soil organic matter content (Luo et al., 2020). Microbial communities respond to stoichiometric changes in four primary ways: First, adjusting biomass composition to match available resources, though these changes are generally modest and driven more by shifts in microbial community structure than by cellular storage. Second, mobilizing resources via enzyme production, which is often limited by C and N availability (Ashraf et al., 2021). Third, regulating element use efficiency allow for the release of excess nutrients. Fourthly, utilizing diastrophic bacteria and saprotrophic fungi to acquiring exogenous N and P (Mooshammer et al., 2014). Globally, current knowledge on soil and microbial biomass stoichiometry is primarily focused on bulk soil (Luo et al., 2020). However, rhizospheric nutrients and microbial communities are more susceptible to environmental fluctuations than those in bulk soil. Thus, a comprehensive understanding of rhizospheric characteristics and their interactive stoichiometric interactions is crucial for improving agroecosystem productivity and management. This insight is critical for developing strategies that enhance soil fertility, optimize nutrient use efficiency, and support sustainable agricultural practices worldwide.
After revised: Ecological stoichiometry, which examines the elemental balance and interactions within ecosystems, offers a powerful framework to explore the nutrient dynamics in the rhizosphere (Güsewell, 2004). The stoichiometric ratios of C:N:P in soils and microbial biomass are widely used as indicators of nutrient cycling and ecosystem functioning (Cleveland and Liptzin, 2007). Soil C:N:P ratios integrate long-term processes such as organic input, decomposition, mineral weathering, and nutrient retention, thereby reflecting the cumulative nutrient status of the soil matrix (Tipping et al., 2016). In contrast, microbial biomass C:N:P ratios are sensitive indicators of the physiological demands of soil microorganisms, responding more rapidly to environmental fluctuations (Gao et al., 2022; Wasner et al., 2024). While microbial C:N:P ratios tend to remain relatively constrained across ecosystems due to homeostatic regulation, soil stoichiometry varies more widely due to complex biotic and abiotic influences (Chen and Chen, 2021). Rhizospheric processes further shape both soil and microbial stoichiometry by modifying nutrient availability and altering microbial community structure and function (Bell et al., 2014a). Despite this, most studies have examined either bulk soil or rhizosphere soil independently, without fully characterizing the differences in stoichiometric patterns and their underlying drivers (Luo et al., 2020). A more integrative understanding of rhizospheric stoichiometry is essential for informing management practices aimed at enhancing soil fertility, improving nutrient use efficiency, and sustaining agroecosystem productivity under changing environmental conditions.
- L68, what’s “soil P ratio”?
Re: Thanks, we have revised to “soil P:N ratio”.
- L70-71, please add the references
Re: Additional supporting references have been added (Jones et al., 2018; Pei et al., 2024).
- L90, please highlight your work at the end of this paragraph and explain your hypothesis
Re: Revised to explicitly state the novelty of our global-scale rhizosphere meta-analysis and clearly articulated two hypotheses
Before revised: Although previous studies have extensively examined the C:N:P stoichiometry in soils, plants, and microbes across natural and managed ecosystems, agricultural rhizospheric soils are often underrepresented. To fill this gap, we compiled a comprehensive dataset comprising 882 unique cases from 113 peer-reviewed sources across global agroecosystems. The objectives of this study were to: (1) quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry across global agroecosystems; and (2) identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry.
After revised: Although the rhizosphere’s unique biogeochemical properties are increasingly recognized, its stoichiometric distinctions from bulk soil have not been systematically evaluated on a global scale. Moreover, the extent to which these patterns are governed by climate, soil properties, and management remains poorly resolved. To address this knowledge gap, we assembled a global dataset comprising 1,673 unique cases from 121 peer-reviewed studies encompassing diverse agroecosystems. Our study aimed to (1) quantify the patterns and coupling relationships of rhizospheric soil and microbial stoichiometry at a global scale and (2) identify the environmental and management-related drivers of these patterns. We hypothesized that that (1) rhizospheric soils would exhibit significantly higher C:N and C:P ratios but lower microbial biomass C:N ratios than bulk soils due to root-induced nutrient enrichment and microbial activation, and (2) these differences would be strongly modulated by aridity, soil organic carbon content, and ammonium nitrogen availability.
- L111, “822”? it is not consistent with “882” in abstract, I am not sure how many observations do you have.
Re: This was an error. After updating the literature, we confirmed the correct number to be 1,683 and have revised it accordingly throughout the Abstract and Methods sections.
- L122, how did you get the missing latitude and longitude data from google map, I mean sometimes, they provide the name, but maybe it is a huge area, like a province.
Re: Thank you for this insightful comment. We acknowledge that our initial explanation was not sufficiently detailed. We have now clarified this section in the revised manuscript. Specifically, for studies that did not report geographic coordinates, we adopted a three-step approach:
(1) We first searched for other publications by the authors to find related studies that might contain location information;
(2) If such information could not be retrieved, we contacted the corresponding author directly via email to request site coordinates;
(3) If neither of these approaches yielded the necessary data, we excluded the study from our analysis.
This clarification has been added to the Methods section, and we now acknowledge the associated uncertainties in the Discussion as a potential limitation of our dataset.
- L124-125, you have some Climatic data from the targeted literatures and some from Worldclimate, did you compare the data here?
Re: Thank you for your comment. Since the temperature and precipitation data used in our analysis are long-term averages, they are relatively stable over time. The corresponding indicators provided by WorldClim are widely recognized for their representativeness and have been cited in numerous high-impact international journals. Therefore, we directly used the climatic data obtained from WorldClim in our study.
In response to your suggestion, we further compared part of the climatic data extracted directly from the original publications with the corresponding values obtained from WorldClim. The results showed no significant differences between the two sources, which further supports the reliability of using WorldClim data in our analysis.- L135-145, please provide classification criteria, reference or something you consider
Re: Thanks, we have added some references and provide corresponding explanationsfor some classification.
- L147, please clarify what your random factors are.
Re: Thanks, we have clarified the random factors.
After revised: Linear mixed-effects models were used to evaluate the influence of environmental factors—climatic zone, AI, crop type, fertilization, tillage, crop growth stage, SOC, soil pH, NO3--N, and NH₄⁺-N—on rhizospheric differences in stoichiometric ratios.
- L167, why did you consider median value other than mean value?
Re: Thank you for your suggestion. Considering the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L176-178, some grammatical errors, please check.
Re: Sentences rephrased for clarity and checked during language polishing
- L193 “the selected environmental variables explained…”, please be specific, which variables?
Re: Thanks, we have clarified the variables (including AI, crop types, fertilization, SOC, pH, TP, AP, NO3—N, and NH4+-N).
- L202-203, something I can’t follow, seems to be a repeat description
Re: Thanks, we have revised this description, please check it.
- L211, grammatical errors, please check
Re: Sentence rewritten during editing.
- L213, you didn’t define “TN” before.
Re: Now defined as “total nitrogen (TN)” at its first occurrence.
- L249-250, I can’t follow “reflecting projected precipitation ….”
Re: Thank you for pointing out our mistake. This is an incomplete statement, as detailed below:
After revised: As aridity increases, soil C:P and N:P ratios tend to decline, while C:N ratios increase, suggesting that continued warming and reduced precipitation could decouple C-N-P cycling and limit plant productivity in arid agroecosystems.
- L251, why do you mention climate change? It is a logical jump here.
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L279-280, I didn’t see any necessary to say “Increased acidity can alter SOC quality and composition” here
Re: Thanks, we agree with your suggestion and have removed this sentence.
- L288, what’s “stoichiometric decomposition theory”? please explain it a little bit and add the reference.
Re: Thank you for your suggestion and we have explained it a little bit and add the reference.
- L303-304, remove “variable” and rephrase this sentence
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L306, “altered soil textures C, N, and P cycles”, rephrase this sentence
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- L309-310, There is an over-inference here, it is correlation, not causation
Re: Thank you for your suggestion. Taking into account the comment from another reviewer, we have removed this sentence from the revised manuscript.
- Fig.1, I didn’t see where is the letters and what’s the meaning of the “◆”?
Re: Thanks, we have revised the figure legends to clearly explain.
Citation: https://doi.org/10.5194/egusphere-2025-1382-AC1
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AC1: 'Reply on RC1', Andong Cai, 28 Jun 2025
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RC2: 'Comment on egusphere-2025-1382', Anonymous Referee #2, 24 May 2025
The manuscript provides a meta-analysis comparing the soil and microbial biomass stochiometric relations between the rhizosphere and non-rhizosphere (bulk soil) from worldwide agroecosystems. This work fits within the scope of the Biogeoscience journal. However, it lacks multiple key elements to be accepted for publication.
The article pursues two objectives: 1) to quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry from agroecosystems and 2) to identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry. The introduction is repetitive in parts (e.g., lines 47-48, 63-65, 81-83) and overlooks the presentation of the agroecosystems management effect on soil and rhizosphere stochiometry. The authors omitted the potential influence of agroecosystem management and restricted their analysis to pedoclimatic effects, which may be misleading due to confounded effects. Several details in the methodology are missing, and sentences that do not follow a logical narrative (e.g., 93-98). The collection of studies does not follow minimum guidelines (e.g., PRISMA), which guarantees standards to perform the data collection and meta-analysis. The manuscript requires exhaustive inclusion and exclusion criteria for the references gathered during the bibliographic search. The conditions for the data extraction (e.g., soil depth(s), average over the season, or final point over the season) are not clear from the study. This is important when dealing with data dependencies (pseudoreplication) during data analysis. Moreover, the definition of control treatments is unclear, and there are no details about how the response ratio was calculated or transformed (to the percentage of change) for interpretation. The authors gave limited justification for discretizing abiotic factors to assess their effect (lines 133-145). The presentation of results is insufficient, lacking the description of the statistical model (e.g., weighting and random components), sensitivity and influence analyses, and heterogeneity indicators to study the effect of abiotic features and other factors properly. Moreover, there are insufficient details about the global distribution of the observations and their effect sizes, which will help assess the representativeness of the dataset. The assessment of other moderators, such as main agronomic practices (e.g., fertilization source or organic matter incorporation), should be incorporated, given their potential importance in regulating stoichiometric relations. The authors complemented their meta-analysis with a boosted regression tree, but insufficient details regarding the hyperparameter optimization and the response and predictor variables are provided. I recommend starting the results section by giving an overview of data regarding the geographic distribution in function of different stochiometric relations, pedoclimatic conditions, and management practices. Several grammatical, semantic, and punctuation errors need to be revised (e.g., lines 38, 51, 317). I encourage the authors to store the dataset and code in an open repository to increase the credibility of their meta-analysis. For these reasons, I recommend that the authors undertake an extensive major revision before the manuscript can be considered for publication.
Citation: https://doi.org/10.5194/egusphere-2025-1382-RC2 -
AC2: 'Reply on RC2', Andong Cai, 28 Jun 2025
Reviewer #2:
The manuscript provides a meta-analysis comparing the soil and microbial biomass stochiometric relations between the rhizosphere and non-rhizosphere (bulk soil) from worldwide agroecosystems. This work fits within the scope of the Biogeoscience journal. However, it lacks multiple key elements to be accepted for publication.
- The article pursues two objectives: 1) to quantify the characteristics and coupling relationships of rhizospheric soil and microbial biomass stoichiometry from agroecosystems and 2) to identify the environmental factors influencing rhizospheric soil and microbial biomass stoichiometry. The introduction is repetitive in parts (e.g., lines 47-48, 63-65, 81-83) and overlooks the presentation of the agroecosystems management effect on soil and rhizosphere stochiometry.
Re: Thank you for pointing this out. We have significantly revised the Introduction to remove redundant statements and improve clarity. Specifically: Lines 47-48, 63-65, and 81-83 were either deleted or rephrased to avoid repetition. We also incorporated the importance of agroecosystem management, as you suggested. Please check the part of Introduction.
- The authors omitted the potential influence of agroecosystem management and restricted their analysis to pedoclimatic effects, which may be misleading due to confounded effects.
Re: Thank you for pointing this out. We agree that agroecosystem management plays a vital role in shaping soil and rhizosphere stoichiometry. In the revised manuscript: (1) We expanded the Introduction and Discussion to explicitly highlight how practices such as fertilization, tillage, and organic matter addition can affect rhizosphere nutrient dynamics. (2) In addition, we have added analysis on management measures such as fertilization and tillage in the manuscript.
- Several details in the methodology are missing, and sentences that do not follow a logical narrative (e.g., 93-98).
Re: Thanks, we agree with your comment and have removed these sentences.
- The collection of studies does not follow minimum guidelines (e.g., PRISMA), which guarantees standards to perform the data collection and meta-analysis. The manuscript requires exhaustive inclusion and exclusion criteria for the references gathered during the bibliographic search
Re: We appreciate this critical point. Although PRISMA is typically used in clinical meta-analyses, we agree that a structured framework improves transparency. In the revised manuscript: We added a detailed workflow diagram following PRISMA guidelines (Fig. S1), including: literature search, screening, eligibility, inclusion criteria, and final study count. Additionally, we have made corresponding revisions in the Materials and Methods section to enhance the reliability of our data.
- The conditions for the data extraction (e.g., soil depth(s), average over the season, or final point over the season) are not clear from the study. This is important when dealing with data dependencies (pseudoreplication) during data analysis
Re: Thank you for this observation.
(1) Considering that our research focuses on agricultural crops and their root systems are mostly distributed in the topsoil layer of 0-20 cm, we mainly focused on the topsoil layer when collecting data. In the revised manuscript: We added clarification that only data from the topsoil layer were included.
(2) Given that microbial stoichiometric ratios can vary substantially across plant growth stages, we collected data not only at harvest but also during other key developmental stages to ensure a more comprehensive analysis. Based on your feedback, we have incorporated subgroup analyses based on growth stages (Fig. 4), which have further enhanced the accuracy and robustness of our findings.
- Moreover, the definition of control treatments is unclear, and there are no details about how the response ratio was calculated or transformed (to the percentage of change) for interpretation.
Re: We apologize for the oversight. In the revised Materials and Methods, we now clearly define control treatments as the bulk soil adjacent to rhizosphere zones, sampled from the same plots and under the same management conditions. Moreover, we also provided the detail equations about how the response ratio was calculated or transformed (2.3 Meta-analysis).
- The authors gave limited justification for discretizing abiotic factors to assess their effect (lines 133-145).
Re: We appreciate this point. We have now added a detailed rationale for discretization:
(1) For continuous variables (e.g., AI, SOC, NH4+-N, and pH) were initially assessed using line regression (Fig. 7 and S5), and subgroups were divided based on the frequency of data distribution.
(2) For categorical analysis (e.g., climate zones, crop types, fertilization, and tillage), we discretized variables into quantiles based on the previous study.
(3) We also added some reference that support such discretization strategies in ecological meta-analyses (e.g., Xu et al., 2021b; Zomer et al., 2022; Cai et al., 2023)
- The presentation of results is insufficient, lacking the description of the statistical model (e.g., weighting and random components), sensitivity and influence analyses, and heterogeneity indicators to study the effect of abiotic features and other factors properly.
Re: We thank the reviewer for highlighting this important issue. We have significantly expanded the statistical methods section:
(1) All models were run using the metafor package in R, employing a random-effects model with study identity as a random factor.
(2) Each effect size was weighted by the inverse of its variance.
(3) We now report heterogeneity statistics (Q, τ², I²) for each model.
(4) Funnel plots were employed to assess publication bias (Figs. S2).
- Moreover, there are insufficient details about the global distribution of the observations and their effect sizes, which will help assess the representativeness of the dataset.
Re: We have added a global map of the observation’s locations and their effect sizes (new Fig. 1). We also discussed the potential spatial biases and representativeness in the revised Discussion.
- The assessment of other moderators, such as main agronomic practices (e.g., fertilization source or organic matter incorporation), should be incorporated, given their potential importance in regulating stoichiometric relations.
Re: As mentioned above, we now include management-related moderators (fertilization type and tillage) in meta-regression models (Figs. 3 and 4).
- The authors complemented their meta-analysis with a boosted regression tree, but insufficient details regarding the hyperparameter optimization and the response and predictor variables are provided.
Re: We appreciate the reviewer's comment regarding the boosted regression tree (BRT) analysis details. In our study, the BRT was implemented using the 'dismo' package in R (v4.2.0) with the rhizospheric soil and microbial C:N ratio as the response variable and environmental factors (climate, soil properties, and management) as predictors. Key hyperparameters were optimized through 10-fold cross-validation: learning rate (0.005), tree complexity (3), bag fraction (0.75), and number of trees (1500 determined by early stopping). Model performance was evaluated via cross-validated deviance explained. These methodological details have been added to Section 2.4 of the revised manuscript.
- I recommend starting the results section by giving an overview of data regarding the geographic distribution in function of different stochiometric relations, pedoclimatic conditions, and management practices.
Re: As mentioned above, we added a global map of the observation’s locations and their effect sizes at the starting of the results section.
- Several grammatical, semantic, and punctuation errors need to be revised (e.g., lines 38, 51, 317).
Re: We acknowledge this and have carefully revised the manuscript for grammar, clarity, and scientific language. A native English-speaking editor with expertise in ecology performed full language editing.
- I encourage the authors to store the dataset and code in an open repository to increase the credibility of their meta-analysis.
Re: We fully support open science. We have added all the literature related to the dataset in the supplementary and the dataset and code will be made available on request.
EIC Comments:
1.) Lines 363-648 - Format for full citation references here do not conform to the requested journal type. This includes missing an ampersand (&) before the last author's name in citations with 7 or less authors, listing more than 7 authors (if more than 7, list #1 to #6, then " ... ", then last author's name), use of a comma before the year, missing parentheses around the year, use of comma after the journal name, italicization of the journal name and volume number, etc. Please see the instructions to authors, and revise these to match that format. See https://www.keaipublishing.com/en/journals/international-soil-and-water-conservation-research/guide-for-authors/Re: Thanks for your suggestions and we have revised it based on the request. Moreover, the English expression of the whole manuscript has been professionally edited for English usage, grammar, spelling, and punctuation by a native English speaker and a skilled professional editor. Therefore, we would appreciate it if any comments regarding language.
We deeply thank you again for your comprehensive and insightful review. Your feedback has helped us substantially improve the rigor, structure, and clarity of our manuscript. We hope that the revised version addresses all your concerns and meets the standard for publication. Thanks again for your kind evaluation and suggestions to improve our current manuscript, and we look forward to receiving your valuable reply.
Citation: https://doi.org/10.5194/egusphere-2025-1382-AC2
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AC2: 'Reply on RC2', Andong Cai, 28 Jun 2025
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Tianfu Han
Shengnan Tang
Waseem Hassan
Tianjing Ren
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