Data from: Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment
Data files
Aug 27, 2024 version files 346.18 KB
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Dataset_upload.csv
337.79 KB
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README.md
8.38 KB
Abstract
Quantifying leaf photosynthetic response to nitrogen (N) deposition under contrasting water conditions is important for reliably modeling terrestrial carbon and water cycles, a topic that has not been well understood.
Here, we analyzed 737 paired observations from 102 publications to assess the response of eleven leaf photosynthesis-related properties to N addition under different water conditions. Our research includes global experiments, with 19 conducted in the field and 83 in greenhouses. Treatments without water reduction were classified as 'no water change', while those with reduced water or precipitation causing physiological drought were categorized as 'drought'.
We found that, compared to the control group, N addition significantly increased leaf photosynthetic rate (Pn; 20.9%), leaf transpiration (E; 8.3%), and stomatal conductance (gs; 14.1%). However, the decrease in Pn (-11.6%), E (-24.7%), and gs (-23.9%) under the combination of N addition and drought indicated that N addition could not offset the negative effects of drought. Furthermore, N addition significantly enhanced water use efficiency (WUE) by 19.8% under no water change conditions and by 21.1% under drought conditions. Within plant functional groups, herbaceous species exhibited greater susceptibility to N addition than woody species, especially under drought conditions. The observed patterns of increase in Pn with longer experimental duration and WUE with higher N rate under drought conditions showed that plants would gradually adapt to long-term water stress in the context of N deposition. Furthermore, our results showed that drought could strengthen the correlations between leaf photosynthetic properties. Lastly, our study demonstrated that N addition and drought significantly impacted leaf nitrogen content and SPAD, respectively, and further affected gs, Pn, and WUE.
Synthesis: Our results emphasize the crucial role of water conditions in shaping the response of leaf photosynthesis to nitrogen (N) enrichment, and also acknowledge the significance of leaf functional traits in regulating the dynamics of leaf photosynthetic processes.
README: Data from: Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment
https://doi.org/10.5061/dryad.p5hqbzkz0
Description of the data and file structure
The data of 7 leaf photosynthetic properties were extracted, including
- leaf photosynthetic rate (Pn, µmol m−2 s−1),
- leaf transpiration (E, µmol m−2 s−1),
- stomatal conductance (gs, mol m−2 s−1),
- optimal photochemical efficiency of PSII (Fv/Fm),
- maximum rate of carboxylation by Rubisco (Vcmax, µmol m−2 s−1),
- maximum electron transparent rate (Jmax, µmol m−2 s−1),
- water use efficiency (WUE, calculated from gas exchange measurement of A and gs/E).
Additionally, SPAD was not the only indicator of leaf chlorophyll, it also included data on actual leaf chlorophyll content. Considering the majority of the observations were SPAD-based, we used SPAD to represent chlorophyll in our study.Moreover, 4 leaf photosynthesis-related traits and 1 root trait that may indirectly impact leaf photosynthesis were complementally chosen, including
8. leaf nitrogen content (LNC, g m-2),
9. Soil and Plant Analyzer Development (SPAD, a proxy for leaf chlorophyll content, no unit),
10. leaf area (LA, cm2),
11. superoxide dismutase (SOD, U h–1 mg–1 protein).
12. Root length (RL, cm)
Files and variables
File: Dataset_upload.csv
Description
The dataset for Water controls the divergent responses of terrestrial plant photosynthesis under nitrogen enrichment. The list of all references was exhibited in the Supporting Information (Reference S1).
Additionally, some unavailable values are replaced by "null" in this dataset. Data users can use the formulation: ln*RR*<-ln(Xtrt/Xck) to calculate the response ratio. And the values of each variable under control and treatment conditions must be carefully recorded to ensure accurate calculations. This formulation assumes that the variables under treatment (Xtrt) and control (Xck) conditions are measured consistently and their ratio can be appropriately log-transformed to derive the response ratio, ln*RR*. To ensure reproducibility and clarity, data users should notice the conditions under which measurements were taken. Furthermore, appropriate statistical methods should be applied to analyze the data, including checking for normality of distributions and homogeneity of variance before applying the log transformation. This approach will help accurately interpret the treatment's effects relative to the control. And X.cn ,X.tn,X.csd, and X.tsd could be calculated for the weight of each variable via two major methods (Tian et al., 2019; Wang et al., 2023).
Tian D, Reich PB, Chen HYH, Xiang Y, Luo Y, Shen Y, Meng C, Han W, Niu S. 2019. Global changes alter plant multi-element stoichiometric coupling. New Phytol 221(2): 807-817.
Wang Z, Xing A, Shen H. 2023. Effects of nitrogen addition on the combined global warming potential of three major soil greenhouse gases: A global meta-analysis. Environmental Pollution 334: 121848.
Variables
- number: The number of observation
- references: The abbreviation of the reference
- num_reference: The number of the reference
- study: The number of the experiment
- map1: An index for map building
- latitude: The latitude of the experiment
- longitude: The longitude of the experiment
- TN: Soil total nitrogen
- Greenhouse.field: Experimental setting place
- plant.year: The age of a woody plant
- Growth.form: Plant growth form
- D.form: The drought setting form
- water: The change of water condition. Specificall, it represents the relative change in water conditions under a specific treatment compared to the control group. Formulation= (
Watertrt- Waterck) /Waterck - N.rate: The rate of N addition
- Duration..yr.: The experiment duration
- SPAD.ck: SPAD in control treatment
- SPAD.csd: The standard error of SPAD in control treatment
- SPAD.cn: The replication of SPAD in control treatment
- SPAD.treat: SPAD in experimental treatment
- SPAD.tsd: The standard error of SPAD in experimental treatment
- SPAD.tn: The replication of SPAD in experimental treatment
- Pn.ck: Leaf photosynthetic rate in control treatment
- Pn.csd: The standard error of leaf photosynthetic rate in control treatment
- Pn.cn: The replication of leaf photosynthetic rate in control treatment
- Pn.treat: Leaf photosynthetic rate in experimental treatment
- Pn.tsd: The standard error of leaf photosynthetic rate in experimental treatment
- Pn.tn: The replication of leaf photosynthetic rate in experimental treatment
- SOD.ck: SOD in experimental treatment
- SOD.csd: The standard error of SOD in control treatment
- SOD.cn: The replication of SOD in control treatment
- SOD.treat: SOD in experimental treatment
- SOD.tsd: The standard error of SOD in experimental treatment
- SOD.tn: The replication of SOD in experimental treatment
- Jmax.ck: Jmax in control treatment
- Jmax.csd: The standard error of Jmax in control treatment
- Jmax.cn: The replication of Jmax in control treatment
- Jmax.treat: Jmax in experimental treatment
- Jmax.tsd: The standard error of Jmax in experimental treatment
- Jmax.tn: The replication of Jmax in experimental treatment
- Vcmax.ck: Vcmax in control treatment
- Vcmax.csd: The standard error of Vcmax in control treatment
- Vcmax.cn: The replication of Vcmax in control treatment
- Vcmax.treat: Vcmax in experimental treatment
- Vcmax.tsd: The standard error of Vcmax in experimental treatment
- Vcmax.tn: The replication of Vcmaxin experimental treatment
- gs.ck: Stomatal conductance in control treatment
- gs.csd: The standard error of stomatal conductance in control treatment
- gs.cn: The replication of stomatal conductance in control treatment
- gs.treat: Stomatal conductance in experimental treatment
- gs.tsd: The standard error of stomatal conductance in experimental treatment
- gs.tn: The replication of stomatal conductance in experimental treatment
- LA.ck: LA in control treatment
- LA.csd: The standard error of LA in control treatment
- LA.cn: The replication of LA in control treatment
- LA.treat: LA in experimental treatment
- LA.tsd: The standard error of LA in experimental treatment
- LA.tn: The replication of LA in experimental treatment
- E.ck: E in control treatment
- E.csd: The standard error of E in control treatment
- E.cn: The replication of E in control treatment
- E.treat: E in experimental treatment
- E.tsd: The standard error of E in experimental treatment
- E.tn: The replication of E in experimental treatment
- WUE.ck: WUE in control treatment
- WUE.csd: The standard error of WUE in control treatment
- WUE.cn: The replication of WUE in control treatment
- WUE.treat: WUE in experimental treatment
- WUE.tsd: The standard error of WUE in experimental treatment
- WUE.tn: The replication of WUE in experimental treatment
- LNC.ck: LNC in control treatment
- LNC.csd: The standard error of LNC in control treatment
- LNC.cn: The replication of LNC in control treatment
- LNC.treat: LNC in experimental treatment
- LNC.tsd: The standard error of LNC in experimental treatment
- LNC.tn: The replication of LNC in experimental treatment
- Fv.Fm.ck: Fv/Fm in control treatment
- Fv.Fm.csd: The standard error of Fv/Fm in control treatment
- Fv.Fm.cn: The replication of Fv/Fm in control treatment
- Fv.Fm.treat: Fv/Fm in experimental treatment
- Fv.Fm.tsd: The standard error of Fv/Fm in experimental treatment
- Fv.Fm.tn: The replication of Fv/Fm in experimental treatment
- RootLength.ck: Root length in control treatment
- RootLength.csd: The standard error of root length in control treatment
- RootLength.cn: The replication of root length in control treatment
- RootLength.treat: Root length in experimental treatment
- RootLength.tsd: The standard error of root length in experimental treatment
- RootLength.tn: The replication of root length in experimental treatment
Code/software
All meta-analyses were conducted in R software (version 4.0.5; R Core Team, 2023) and figures were generated using the ‘ggplot2’ package (Ginestet, 2011).
Note: The code was also uploaded to Zenodo through this repository. See Software related works.
Methods
We systematically searched the journal articles via Web of Science, Google Scholar, and China National Knowledge Infrastructure, using the following keywords: “drought” or “water stress” or “water deficit” or “reduced precipitation” or “reduced rainfall” and “nitrogen addition” or “N addition” and “leaf photosynthesis” or “plant photosynthesis”. The preliminary screened articles were then refined based on the following criteria:
1) Studies that did not investigate both the individual and combined effects of drought and N addition on leaf photosynthesis were excluded.
2) Experiments that manipulated only water or N availability or warming and eCO2 simultaneously were not considered.
3) Control and experimental plots should be established in the same location or soil condition to ensure consistency in microclimate and soil nutrient conditions.
4) The studies we selected contained at least one of the following target variables: leaf photosynthetic rate (Pn), stomatal conductance (gs), water use efficiency (WUE), or optimal photochemical efficiency of PSII (Fv/Fm).