Data from: Interspecific differences in nitrogen form acquisition strategies contribute to species dominance
Dryad was alerted to concerns regarding the original May 22, 2025 version files, and the appearance therein of several instances in which data were duplicated across entries; the dataset supports this published paper [1]. Following liaison between the author, Ecology, and Dryad, a revised and corrected dataset has now been published (Oct 23, 2026 version files).
[1]: Guan, Ming, Xiao-Cui Pan, Jian-Kun Sun, Ji-Xin Chen, Xiao-Lin Wei, Bernhard Schmid, Michel Loreau, and Yu-Long Feng. 2025. “ Interspecific Differences in Nitrogen Form Acquisition Strategies Contribute to Species Dominance.” Ecology 106(6): e70137. https://doi.org/10.1002/ecy.70137
Data files
May 22, 2025 version files 733.96 KB
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ANOVAs_and_independent_sample_t-tests.R
48.40 KB
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ANOVAs.zip
3.93 KB
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data.xlsx
639.97 KB
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Hierarchical_partitioning_analysis.R
6.26 KB
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HPM.zip
8.30 KB
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Linear_mixed-effects_model_analysis.R
2.74 KB
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Linear_regression_analyses.R
8.51 KB
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LMMs.zip
3.92 KB
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LRA.zip
2.20 KB
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README.md
9.72 KB
Oct 23, 2026 version files 754.78 KB
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ANOVAs_and_independent_sample_t-tests.R
48.39 KB
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ANOVAs.zip
4 KB
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change_log.xlsx
11.94 KB
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data.xlsx
643.49 KB
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Hierarchical_partitioning_analysis.R
4.48 KB
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HPM.zip
7.13 KB
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Linear_mixed-effects_model_analysis.R
2.16 KB
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Linear_regression_analyses.R
9.91 KB
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LMMs.zip
3.98 KB
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LRA.zip
3.66 KB
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README.md
15.64 KB
Abstract
Plant’s ability to use prevalent or less prevalent soil nitrogen (N) forms may affect their dominance within vegetation types, and these partitioning-driven changes in dominance may facilitate species co-existence. However, the mechanisms underlying these processes remain unclear, particularly given the strong influence of altitude on soil N forms, which in turn affects plant N acquisition strategy. In this study, we first determined the effects of preference and plasticity in N form uptake on partitioning of soil N forms and species dominance, and then assessed the relative importance of these two N form use strategies for 19 dominant and non-dominant species in three vegetation types along an altitudinal gradient on Changbai Mountain, northeast China. To achieve this, we measured dominance, the contents of different N forms in rhizosphere soils, their proportional contributions to leaf N, and N form uptake preference and plasticity for these 19 species. Our results show significant interspecific differences in the proportional contributions of different soil N forms to leaf N within all three vegetation types, providing a novel mechanism underlying niche differentiation among plants. Species dominance was positively associated with the proportional contributions of soil dissolved organic N (the most prevalent N form) and the main inorganic N form to leaf N, while negatively with that of the subordinate inorganic N. These associations were not altered by the altitude-driven changes in the absolute and proportional contents of different soil N forms, suggesting a potentially widespread phenomenon. Both preference and plasticity in N form uptake contributed to the proportional contributions of different N forms to leaf N, and therefore to species dominance and co-existence within vegetation types. Furthermore, N form preference was more critical for non-dominant relative to dominant species and at high relative to low altitude, while N form uptake plasticity was more important for dominant species and at low altitude. Our study provides robust evidence for the interspecific niche differentiation in N form uptake, contributing to species dominance and co-existence within vegetation types, and reveals the mechanisms (plasticity and preference) underlying the association between species dominance and the uptakes of different N forms.
- File name: README.md
- Authors: Ming Guan, Yu-Long Feng
- Other contributors: Xiao-Cui Pan, Jian-kun Sun, Ji-Xin Chen, Xiao-Lin Wei, Bernhard Schmid, Michel Loreau
- Original README created: 2024-08-10
- Updated for Dryad revision: 2026-08-31
- Expanded in response to Dryad curation: 2026-10-22
Dataset Attribution and Usage
- Dataset Title: Data from: Interspecific differences in nitrogen form acquisition strategies contribute to species dominance
- Persistent Identifier (Dryad DOI): https://doi.org/10.5061/dryad.bk3j9kdhw
- Dataset Contributors (Creators):
Ming Guan; Xiao-Cui Pan; Jian-kun Sun; Ji-Xin Chen; Xiao-Lin Wei; Bernhard Schmid; Michel Loreau; Yu-Long Feng - Suggested Citations:
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Dataset citation:
Guan M, Pan XC, Sun JK, Chen JX, Wei XL, Schmid B, Loreau M, Feng YL. 2025. Data from: Interspecific differences in nitrogen form acquisition strategies contribute to species dominance. Dryad, Dataset, https://doi.org/10.5061/dryad.bk3j9kdhw
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Corresponding publication:
Guan M, Pan XC, Sun JK, Chen JX, Wei XL, Schmid B, Loreau M, Feng YL. 2025. Interspecific differences in nitrogen form acquisition strategies contribute to species dominance. Ecology 106(6): e70137. https://doi.org/10.1002/ecy.70137.
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Contact Information
- Name: Ming Guan
- Affiliations: Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou, Zhejiang Province 318000, China
- ORCID ID: https://orcid.org/0009-0006-9734-2219
- Email: guanmingtzc@163.com
- Alternate Email: guanming8812345@sina.com
- Alternative Contact Name: Yu-Long Feng
- Affiliations: Liaoning Key Laboratory for Biological Invasions and Global Changes, College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, Liaoning Province 110866, China
- ORCID ID: https://orcid.org/0000-0003-0243-2280
- Email: fyl@syau.edu.cn
Funding sources
National Key R&D Program of China (2023YFC2604500)
National Natural Science Foundation of China (32001238, 32171666 and 32271741)
Zhejiang Provincial Natural Science Foundation of China (LQ20C030004)
Version history
Version 2
This version corrects errors identified in the dataset originally published on 22 May 2025. Following verification against the original experimental records, two sample records for soil nitrogen-form contents were corrected. In addition, five sample records containing incorrectly duplicated estimates of the proportional contributions of different soil nitrogen forms to leaf nitrogen (f-values: fDON, fNH4, and fNO3) were identified and corrected after recalculation with MixSIAR.
Derived variables and related analysis inputs were recalculated using the corrected data, and the relevant statistical analyses were repeated. The corrections resulted in some numerical changes and a small number of changes in pairwise statistical comparisons, but did not alter the main patterns, effect directions, or main conclusions of the associated article.
The previous version of the dataset remains available through Dryad's version history.
- Methods of data collection/generation: see the associated article and its supporting information for details.
- Details of the statistical analyses are provided in the corresponding R scripts described below.
Data and File Overview
The current version contains the corrected master dataset, a change log documenting the directly corrected values, analysis-specific input files, and the R scripts used for the updated analyses.
Summary Metrics
- Accompanying data and analysis files: 10
- Top-level file formats: .xlsx, .zip, .R
- The zip archives contain .csv input files.
Table of Contents
- data.xlsx
- change_log.xlsx
- ANOVAs_and_independent_sample_t-tests.R
- Linear_mixed-effects_model_analysis.R
- Linear_regression_analyses.R
- Hierarchical_partitioning_analysis.R
- ANOVAs.zip
- LMMs.zip
- LRA.zip
- HPM.zip
Setup
- Recommended software/tools:
- R (recommended): version 4.2.2 (or compatible)
- Spreadsheet: Microsoft Excel (or equivalent) for .xlsx files
- Archive extraction: software supporting .zip files
Relationship between data files
data.xlsxis the corrected master dataset. The CSV input files contained inANOVAs.zip,LMMs.zip,LRA.zip, andHPM.zipare analysis-specific extracts or summaries derived from the corrected dataset.- To run the corresponding analyses:
- Extract the required archive(s) (
ANOVAs.zip,LMMs.zip,LRA.zip,HPM.zip) to local folders. - Open R and run the corresponding script:
ANOVAs_and_independent_sample_t-tests.Ruses the input file inANOVAs.zip.Linear_mixed-effects_model_analysis.Ruses the input file inLMMs.zip.Linear_regression_analyses.Ruses the input files inLRA.zip.Hierarchical_partitioning_analysis.Ruses the input files inHPM.zip.
- Extract the required archive(s) (
- Traceability:
change_log.xlsxdocuments the values directly corrected between Version 1 and Version 2.
File/Folder Details
Details for: data.xlsx
- Description: Corrected master dataset used for the statistical analyses and for generating the figures and tables associated with the article.
- Format(s): .xlsx
- Contents: 11 worksheets.
The worksheets are:
Article information: article title, authors, and journal.Column name: names and definitions of the variables in the master dataset.Data: corrected master data table containing 60 sample records and 26 variables.Fig. 2: data used for Figure 2 (proportional contributions of DON, NH4+, and NO3- to leaf N for dominant and non-dominant species in the three vegetation types).Fig. 3: data used for Figure 3 (relationships between proportional contributions of the three N forms to leaf N and species importance value).Fig. 4: data used for Figure 4 (preferences for different N forms for dominant and non-dominant species in the three vegetation types).Fig. 5: data used for Figure 5 (percentage similarity between plant N-form uptake and rhizosphere-soil N-form availability).Fig. 6: data used for Figure 6 (hierarchical-partitioning results for the explanatory contributions of PS and N-form preferences to variation in species importance value).Fig. S1: data used for Figure S1 (pool sizes of dissolved N forms in rhizosphere soils).Fig. S2: data used for Figure S2 (relationships between N-form preferences and species importance value).Fig. S3: data used for Figure S3 (relationships between percentage similarity and species importance value).
Variables in the Data worksheet:
VT: Vegetation types.plot_ID: ID of plot.Species: Plant species.Family: Family.Abbreviation: Abbreviation of plant species.MT: Mycorrhizal type.SD: Species dominance.PFG: Plant functional group.PLF: Plant life form.IV: Importance value.DON: Content of dissolved organic nitrogen (DON).NH4: Content of ammonium (NH4+).NO3: Content of nitrate (NO3-).SDON: Proportional contribution of DON in total dissolved nitrogen (TDN).SNH4: Proportional contribution of NH4+ in TDN.SNO3: Proportional contribution of NO3- in TDN.fDON: Proportional contribution (uptake) of DON to leaf N.fNH4: Proportional contribution (uptake) of NH4+ to leaf N.fNO3: Proportional contribution (uptake) of NO3- to leaf N.PS: Percentage similarity between plant uptake pattern of different N forms and their availability pattern in rhizosphere soil.pDON: Preference for DON.pNH4: Preference for NH4+.pNO3: Preference for NO3-.QT_pDON: pDON after quantile transformation.QT_pNH4: pNH4 after quantile transformation.QT_pNO3: pNO3 after quantile transformation.
Please see the Column name worksheet in data.xlsx for the variable definitions.
Details for: change_log.xlsx
- Description: Provides an itemized record of the values directly corrected between Version 1 and Version 2.
- Format(s): .xlsx
- Contents: 2 worksheets.
The worksheets are:
Column name: definitions of the columns used in the change log.Change_Log: itemized Version 1 and Version 2 values for the directly corrected entries.
For each corrected value, the file records:
- vegetation type;
- plot identifier;
- species;
- variable corrected;
- value in Version 1; and
- corrected value in Version 2.
Details for: ANOVAs.zip
- Description: Analysis-specific input data for one-way analyses of variance, post-hoc comparisons, independent-sample t-tests, and non-parametric alternatives used where appropriate.
- Format(s): .zip containing .csv files.
- Contents:
ANOVAs/Data-ANOVAs.csv: 60 sample records and 23 variables.
- Main analyses supported:
- Figure 2: proportional contributions of DON, NH4+, and NO3- to leaf N.
- Figure 4: preferences for different N forms.
- Figure 5: percentage similarity between plant N-form uptake and rhizosphere-soil N-form availability.
- Figure S1: pool sizes of DON, NH4+, and NO3- in rhizosphere soils.
- Corresponding R script:
ANOVAs_and_independent_sample_t-tests.R. - Note: Variable definitions are provided in the
Column nameworksheet ofdata.xlsxand in comments within the R script.
Details for: LMMs.zip
- Description: Analysis-specific input data for the linear mixed-effects model analyses reported in Tables S3-S5.
- Format(s): .zip containing .csv files.
- Contents:
LMMs/Data-LMMs.csv: 60 sample records and 23 variables.
- Main analyses supported:
- Table S3: effects of vegetation type, species dominance, and their interaction on fDON, fNH4, and fNO3.
- Table S4: effects of vegetation type, species dominance, and their interaction on preferences for DON, NH4+, and NO3-.
- Table S5: effects of vegetation type, species dominance, and their interaction on percentage similarity (PS).
- Corresponding R script:
Linear_mixed-effects_model_analysis.R. - Note: The models use vegetation type, species dominance, and their interaction as fixed effects, with species and plot as random effects, as specified in the R script.
Details for: LRA.zip
- Description: Analysis-specific input data for the linear regression analyses used for Figures 3, S2, and S3.
- Format(s): .zip containing .csv files.
- Contents:
LRA/Data-LRA.csv: 60 sample records and 17 variables. This file is used for the regressions of N-form proportional contributions and N-form preferences against species importance value.LRA/Data-LRA1.csv: 19 species-level records and 4 variables (VT,IV,Mean, andSE). This file is used for the analysis of percentage similarity against species importance value.
- Main analyses supported:
- Figure 3: relationships between fDON, fNH4, and fNO3 and species importance value.
- Figure S2: relationships between N-form preferences and species importance value.
- Figure S3: relationship between percentage similarity and species importance value.
- Corresponding R script:
Linear_regression_analyses.R.
Details for: HPM.zip
- Description: Analysis-specific input matrices for the hierarchical partitioning analyses used for Figure 6.
- Format(s): .zip containing .csv files.
- Contents: 18 CSV files organized by vegetation type and species-dominance subset.
For each of the three vegetation types (KPBL, EB, and AT), the archive contains paired response and predictor files for:
- all species;
- dominant species; and
- non-dominant species.
The nine response files are:
IV-KPBL.csvIV-KPBL-dominant.csvIV-KPBL-non-dominant.csvIV-EB.csvIV-EB-dominant.csvIV-EB-non-dominant.csvIV-AT.csvIV-AT-dominant.csvIV-AT-non-dominant.csv
Each response file contains species importance value (IV).
The nine corresponding predictor files are:
variables-KPBL.csvvariables-KPBL-dominant.csvvariables-KPBL-non-dominant.csvvariables-EB.csvvariables-EB-dominant.csvvariables-EB-non-dominant.csvvariables-AT.csvvariables-AT-dominant.csvvariables-AT-non-dominant.csv
Each predictor file contains PS, pDON, pNH4, and pNO3.
- Main analysis supported: Figure 6, which reports the relative explanatory contributions of percentage similarity and N-form preferences to variation in species importance value for all species, dominant species, and non-dominant species within each vegetation type.
- Corresponding R script:
Hierarchical_partitioning_analysis.R.
Details for: ANOVAs_and_independent_sample_t-tests.R
- Description: R script used to calculate descriptive statistics and conduct the group-comparison analyses associated with Figures 2, 4, 5, and S1.
- Format(s): .R
- Input:
ANOVAs/Data-ANOVAs.csvfromANOVAs.zip. - Analyses include:
- means and standard errors;
- tests of homogeneity of variance;
- one-way ANOVAs and pairwise post-hoc comparisons;
- Kruskal-Wallis and Conover post-hoc tests where non-parametric alternatives are used; and
- independent-sample t-tests for comparisons between dominant and non-dominant species.
- Note: Required R packages and explanatory comments are provided within the script.
Details for: Linear_mixed-effects_model_analysis.R
- Description: R script used to conduct the linear mixed-effects model analyses reported in Tables S3-S5.
- Format(s): .R
- Input:
LMMs/Data-LMMs.csvfromLMMs.zip. - Analyses include:
- models for fDON, fNH4, and fNO3 (Table S3);
- models for quantile-transformed N-form preferences (Table S4); and
- a model for percentage similarity (Table S5).
- Model structure: vegetation type, species dominance, and their interaction are included as fixed effects; species and plot are included as random effects.
- Note: Required R packages and explanatory comments are provided within the script.
Details for: Linear_regression_analyses.R
- Description: R script used to conduct the linear regression analyses associated with Figures 3, S2, and S3.
- Format(s): .R
- Inputs:
LRA/Data-LRA.csvLRA/Data-LRA1.csv
- Analyses include:
- regressions of fDON, fNH4, and fNO3 against species importance value (Figure 3);
- regressions of pDON, pNH4, and pNO3 against species importance value (Figure S2); and
- regression of mean percentage similarity against species importance value (Figure S3).
- Note: Required R packages and explanatory comments are provided within the script.
Details for: Hierarchical_partitioning_analysis.R
- Description: R script used to conduct the hierarchical partitioning analyses associated with Figure 6.
- Format(s): .R
- Inputs: the 18 CSV files contained in
HPM.zip. - Analysis structure:
- separate analyses for KPBL, EB, and AT;
- separate analyses for all species, dominant species, and non-dominant species within each vegetation type;
- species importance value (
IV) is the response variable; and PS,pDON,pNH4, andpNO3are the explanatory variables.
- Note: Required R packages and explanatory comments are provided within the script.
Data Reuse
Users conducting new analyses or reusing these data should use the files in the current version of the dataset.
Earlier versions remain available through Dryad for transparency and version history.
END OF README
Study sites
This study was conducted on the north slope of Changbai Mountain, Jilin Province, northeast China (41°23′ – 42°36′ N; 126°55′ – 129°00′ E). This region has a typical continental temperate monsoon climate, with long cold winters and short warm summers. From the lower part of the mountain at 740 m to the summit at 2691 m, the mean annual temperature decreases from 2.8 to –7.3oC and the mean annual precipitation increases from 750 to 1340 mm (He et al., 2005).
Korean pine and broadleaved mixed forest (KPBL), Erman’s birch forest (EB), and alpine tundra (AT) were selected as study plant communities based on their prevalent forms of soil N. In KPBL, dissolved inorganic N (DIN) accounts for a large proportion of total dissolved soil N (TDN), and NO3- is the prevailing inorganic N form; in EB, DIN also accounts for a large proportion of soil TDN, but NH4+ is the predominant inorganic N form; in AT, however, DON is the principal soil N form (CERN; http://www.cerndata.ac.cn/). Similar altitudinal changes in N forms were also found in our study (Appendix S1: Figure S1). The main properties of the three vegetation types are summarized in Appendix S1: Table S1. The sample plots are located in a national nature reserve, and thus human interference is negligible.
Study species
In mid-July of 2018, three 30 × 30 m plots (> 20 m apart from one another) were randomly established in EB and AT, respectively. First, we investigated the background information such as altitude, slope degree and vegetation cover in each plot. Second, all woody plants [diameter at breast height (DBH) ≥ 1 cm] were identified. Third, we measured the number, DBH, basal area, crown width, and height of each individual of each tree species, and the number, height and cover of each individual of each shrub species in each plot. Finally, we calculated relative density (RDy) and relative frequency (RF) for the tree and shrub species, relative dominance (RDe) for the tree species, relative cover (RC) for the shrub species, and then the importance values (IV) for the tree and shrub species in each plot based on Zhang et al. (1995) and Asigbaase et al. (2019). The importance value was used to quantified species dominance in our study.
IV of tree = (RDy + RF + RDe) / 300……. ………………………………….……………(1)
IV of shrub = (RDy + RF + RC) / 300………………………………………………..……(2)
RDy = number of individuals of the species / total number of individuals of all species × 100……………………………..………………………………………………………………(3)
RF = frequency of the species / sum frequency of all species × 100……………………..(4)
RDe = basal area of the tree species / total basal area of all tree species × 100…………..(5)
RC = cover of the shrub species / total cover of all shrub species × 100……………..…..(6)
For KPBL, three 30 × 30 m plots were randomly established in a 25-ha KPBL permanent plot. In the permanent plot, only 17 woody plant species had more than 10 individuals per hectare, which accounted for more than 95% of the individuals of all woody plants (Hao et al., 2008). Our studied species were selected from these 17 species using the following criteria: individuals > 3 in each plot; and only one species was randomly selected when more than one from the same family had similar numbers of individuals in each plot. Ultimately, 10 species were selected, and their importance values were calculated using the methods described above. These species together accounted for more than 80% of the total aboveground biomass (Li et al., 1981).
In total, 19 woody plant species were studied, and only one occurred in more than one vegetation types, i.e., Rhododendron aureum in both EB and AT (Appendix S1: Table S2). The species were divided into dominant (≥ 3) and non-dominant (< 3) according to their importance values (Avolio et al., 2019). The numbers of the dominant and non-dominant species are 6 and 4, 3 and 3, and 2 and 1 in KPBL, EB, and AT, respectively (Appendix S1: Table S2).
Leaf and soil sampling, measurements and calculations
In August of 2018, 10 fully developed, intact and healthy leaves or bunches of current-year needles on the south side of the upper canopy were randomly collected from each of the three sampling individuals for each studied species in each plot. The leaves or needles were collected using tree pruners when the sampling individuals were short. For high trees, we climbed up to collect the leaves and needles. The leaves or needles from the same species in each of the three plots were mixed as one sample. This sampling procedure ensured a representative and homogeneous sample, reducing potential effects of intraspecific differences within-plot.
Rhizosphere soils were also collected from the sample individuals mentioned above. We first carefully removed the litter and humus layers from the soil surface at four sides (east, south, west and north) around each sample tree (≈ 1 m from the trunk). Then, fine roots (diameter < 2 mm) were dug out at each side, and rhizosphere soils were collected using a hand-shaking method (Guan et al., 2023). Soils from the same species in each plot were thoroughly mixed as one sample. The soils were immediately put into an ice box, transported to the laboratory of the Research Station of Changbai Mountain Forest Ecosystems, Chinese Academy of Sciences, passed through a 2 mm sieve, and stored at 4oC until measurements.
Leaf total N concentration and δ15N were measured using an element analyzer-stable isotopic mass spectrometer (Flash EA 1112 HT-Delta V Advantages, Thermo Fisher Scientific, USA). The contents of DIN (NH4+ and NO3-), DON, and TDN in rhizosphere soil of each sample species were measured using the standard method commonly used in literature (Guan et al., 2023; Zhang et al., 2018). Soil water content was measured using the oven-drying method. The δ15N values of soil NH4+, NO3-, and TDN (δ15NNH4+, δ15NNO3-, and δ15NTDN) were measured using the chemical method (Liu et al., 2014), azide method (Tu et al., 2016), and high-temperature catalytic oxidation techniques performed with a total organic carbon analyzer-stable isotope ratio mass spectrometer (Iso TOC cube-isoprime100, Elementar, Germany), respectively. The δ15N value of DON (δ15NDON) was calculated as the mass-weighted difference between δ15NTDN versus δ15NNH4+ and δ15NNO3-.
The measurement data mentioned above were used to estimate the proportional contributions of soil NO3-, NH4+, and DON to leaf N (fNO3-, fNH4+, and fDON; %) (Houlton et al., 2007; Stock et al., 2018). The effects of possible isotope fractionation during within-plant N allocation and/or N transport from mycorrhizal fungi to host plants were taken into account (Houlton et al., 2007; Zhu et al., 2019). Plant preferential uptake for soil NO3-, NH4,+ and DON (βNO3-, βNH4,+ and βDON) were estimated by comparing their proportional contribution to leaf N and their relative contents in soil (Guan et al., 2023; Zhang et al., 2018). To estimate plasticity in N form uptake, percentage similarity between plant uptake pattern of different N forms and their availability pattern in rhizosphere soil (percentage similarity) was determined for each species in each plot based on McKane et al. (2002) and Guan et al. (2023).
For detailed measurement and calculation methods please see Appendix S1: Section S1, and mean value of three plots was reported for each variable in the results section.
The data files are .csv files, so they can be opened in many programs. For example, Excel.
The data files are analyzed using code files.
The code files are .R files, so they can be opened in R.
Changes after May 22, 2025:
1. Corrected two sample records for soil nitrogen-form contents following verification against the original experimental records.
2. Corrected five sample records containing incorrectly duplicated estimates of the proportional contributions of different soil nitrogen forms to leaf nitrogen (f-values: fDON, fNH4, and fNO3) after recalculation with MixSIAR.
3. Recalculated the related derived variables, updated the corresponding analysis input files, and repeated the relevant statistical analyses.
4. Added change_log.xlsx to document the values directly corrected between Version 1 and Version 2.
- Guan, Ming; Pan, Xiao‐Cui; Sun, Jian‐Kun et al. (2025). Interspecific differences in nitrogen form acquisition strategies contribute to species dominance. Ecology. https://doi.org/10.1002/ecy.70137
