Global leaf sulphur stoichiometry and the relationships with nitrogen and phosphorus: phylogeny, growth form and environmental controls
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# Global leaf sulphur stoichiometry and the relationships with nitrogen and phosphorus: phylogeny, growth form and environmental controls In total, we collected 31939 records of data , and 2600 plant species belonging to 1186 genera, 210 families, 69 orders, 7 classes and 4 divisions. The overall plants were divided into two growth forms: woody and herb, five growth forms within woody plants: conifer tree, deciduous broad-leaf tree (DB), evergreen broad-leaf tree (EB), deciduous (D) shrub and evergreen (E) shrub. Herbs were subdivided into aquatic and terrestrial herbs by habitats, and into graminoids and forbs by leaf types. The collected environment variables (MAT, MAP, BIO2, BIO5, BIO6, BIO13, BIO14 and BIO15) were used to analyze the response of the leaf elements (leaf S, leaf N and leaf P) to them. ## Description of the Data and file structure We have thirteen sheets in this dataset file. Sheet 1, named "Overall_data", we have a 31940*36 matrix. Sheet 2, named "Metadata" contains a detailed description of the abbreviations that appear in the dataset. Sheet 3, we recorded the source of the dataset. Sheet 4, named "Fig5_data", contains SiteID, OrderID, FamilyID, SpeciesID and elemental concentrations (i.e., CON). All data in "Fig5_data" is derived from "Overall_data" (After remove all null values for each column). Sheet 5 contains the variance of each component (Site, Species, Family, Order and Residual, %) to leaf S, N and P at different levels. Sheet 6, named "Fig6_data", contains environmental variables (BIO15, BIO14, BIO13, BIO6, BIO5, BIO2, MAT and MAP ) and element variables (leaf S, N and P) at different levels. "Fig6_data" is obtained by extracting from "Overall_data" and then deleting the null value. Sheet 7, Sheet 8 and Sheet 9 named "pearson", "lm_result" and "env_importance" respectively, are all results obtained in the course of calculating. Sheet 10, named "BIO", contains 19 environment variables (BIO1-BIO19) obtained from the WorldClim ([https://worldclim.org/).](https://worldclim.org/\).) Sheet 11, Sheet 12 and Sheet 13 named "LeafS_species", "LeafN_species" and "LeafP_species" respectively, includes value of all S, N and P in the database and family information on the corresponding species, respectively. Since some samples did not have exact species information, their taxonomic information was incomplete and we filled by "NA". Some samples did not provide latitude and longitude information on the raw data, and we filled in with "NA". On samples that lacked latitude and longitude, environmental information could not be obtained based on latitude and longitude, and this part of the environmental data were filled with "NA". **The abbreviations for variables**: Variable Description AQ Aquatic plant C Conifer tree DS Deciduous shrub DB Deciduous broad-leaf tree EB Evergreen broad-leaf tree shrub Evergreen shrub TH Terrestrial herb MAT Mean average temperature (°C) MAP Mean average precipitation (mm) BIO2 Mean diurnal range (°C) BIO5 Max temperature of warmest month (°C) BIO6 Min temperature of coldest month (°C) BIO13 Precipitation of wettest month (mm) BIO14 Precipitation of driest month (mm) BIO15 Precipitation seasonality (coefficient of variation) (mm) Leaf S Total sulphur concentrations in leaves (mg g-1) Leaf N Total nitrogen concentrations in leaves (mg g-1) Leaf P Total phosphorus concentrations in leaves (mg g-1) NS Ratio of leaf sulfur concentrations to leaf nitrogen concentrations PS Ratio of leaf phosphorus concentrations to leaf sulfur concentrations NP Ratio of leaf nitrogen concentrations to leaf phosphorus concentrations ## Sharing/Access information Links to other publicly accessible locations of the data: N/A Was data derived from another source? Yes Data was derived from the following sources: \[1] Cui P, Shen Z, Fu P, Bai K, Jiang Y, Cao K. 2020 Comparison of foliar element contents of plants from natural forests with different substrates in southern China. *Acta Ecol. Sin.* **40**, 9148-9163. \[2] Fernández‐Martíne M, Preece C, Corbera J, Cano O, Garcia‐Porta J, Sardans J, Janssens IA, Sabater F, Peñuelas J. 2021 Bryophyte C:N:P stoichiometry, biogeochemical niches and elementome plasticity driven by environment and coexistence. *Ecol. Lett.* **24**, 1375-1386. (doi:10.1111/ele.13752). \[3] Dalle Fratte M, Pierce S, Zanzottera M, Cerabolini BEL. 2021 The association of leaf sulfur content with the leaf economics spectrum and plant adaptive strategies. Funct. Plant Biol. 48, 924-935. (doi:10.1071/FP20396) \[4] Han WX, Fang JY, Reich PB, Woodward FI, Wang ZH. 2011 Biogeography and variability of eleven mineral elements in plant leaves across gradients of climate, soil and plant functional type in China. *Ecol. Lett.* **14**, 788–796. (doi:10.1111/j.1461-0248.2011.01641.x). \[5] Hou X. 1982 *Vegetation geography and chemical composition of dominant plants in China*. Beijing, Science Press. \[6] Kattge J, Bonisch G, Diaz S, Lavorel S, Prentice IC, Leadley P, Tautenhahn S, Werner GDA, Aakala T, Abedi M*, et al.* 2020 TRY plant trait database - enhanced coverage and open access. *Global Change Biol.* **26**, 119-188. (doi:10.1111/gcb.14904). \[7] Sardans J, Vallicrosa H, Zuccarini P, Farré-Armengol G, Fernández-Martínez M, Peguero G, Gargallo-Garriga A, Ciais P, Janssens IA, Obersteiner M*, et al.* 2021 Empirical support for the biogeochemical niche hypothesis in forest trees. *Nat. Ecol. Evol.* **5**, 184-194. (doi:10.1038/s41559-020-01348-1). \[8] Zhang J, Wang Y, Cai C. 2020 Multielemental Stoichiometry in Plant Organs: A Case Study With the Alpine Herb Gentiana rigescens Across Southwest China. *Front. Plant Sci.* **11**, 441. (doi:10.3389/fpls.2020.00441). \[9] Zhang SB, Zhang JL, Slik JWF, Cao KF. 2012 Leaf element concentrations of terrestrial plants across China are influenced by taxonomy and the environment. *Global Ecol. Biogeogr.* **21**, 809-818. (doi:10.1111/j.1466-8238.2011.00729.x). \[10] Zuo Z, Zhao H, Yang L, Lv T, Li X, Ma F, Wang Z, Yu D. 2022 Salinity induces allometric accumulation of sulfur in plants and decouples plant nitrogen‐sulfur correlation in alpine and arid wetlands. *Global Biogeochem. Cy.***36**, e2022GB007372. (doi:10.1029/2022GB007372).
全球叶片硫化学计量学及其与氮、磷的关联：系统发育、生长型与环境调控因子 本次研究共收集31939条数据记录，涵盖隶属于4个门、7个纲、69个目、210个科、1186个属的2600种植物。所有植物被划分为两大类生长型：木本植物与草本植物；其中木本植物进一步细分为5类：针叶树、落叶阔叶树（DB）、常绿阔叶树（EB）、落叶灌木（DS）与常绿灌木（ES）。草本植物按生境分为水生草本与陆生草本，按叶型分为禾草类与非禾本草本。本次收集的环境变量包括年均温（MAT）、年均降水量（MAP）、BIO2、BIO5、BIO6、BIO13、BIO14与BIO15，用于分析叶片元素（叶片硫、叶片氮与叶片磷）对这些环境因子的响应。 ## 数据与文件结构说明 本数据集文件共包含13个工作表。工作表1命名为"Overall_data"，为31940行×36列的矩阵。工作表2"Metadata"详细说明了数据集中出现的所有缩写术语。工作表3记录了本数据集的来源信息。工作表4命名为"Fig5_data"，包含样地ID（SiteID）、目ID（OrderID）、科ID（FamilyID）、物种ID（SpeciesID）及元素浓度（即CON），该表所有数据均源自"Overall_data"，且已剔除各列中的全部空值。工作表5统计了不同层级下，各组分（样地、物种、科、目及残差）对叶片硫、氮、磷化学计量特征的方差贡献率（%）。工作表6命名为"Fig6_data"，包含不同层级的环境变量（BIO15、BIO14、BIO13、BIO6、BIO5、BIO2、MAT、MAP）与元素变量（叶片硫、氮、磷），该表通过从"Overall_data"中提取数据并剔除空值后得到。工作表7、8、9分别命名为"pearson""lm_result"与"env_importance"，均为分析计算过程中得到的结果。工作表10"BIO"包含从WorldClim（https://worldclim.org/）获取的19个环境变量（BIO1-BIO19）。工作表11、12、13分别命名为"LeafS_species""LeafN_species"与"LeafP_species"，分别包含数据库中所有物种的硫、氮、磷元素含量数据，以及对应物种的科属分类信息。由于部分样本未提供确切的物种信息，其分类学信息不完整，以"NA"填充；部分样本的原始数据未提供经纬度信息，同样以"NA"填充；对于缺失经纬度的样本，无法通过经纬度获取环境数据，该部分环境数据也以"NA"填充。 ## 变量缩写说明 - AQ：水生植物（Aquatic plant） - C：针叶树（Conifer tree） - DS：落叶灌木（Deciduous shrub） - DB：落叶阔叶树（Deciduous broad-leaf tree） - EB：常绿阔叶树（Evergreen broad-leaf tree） - ES：常绿灌木（Evergreen shrub） - TH：陆生草本（Terrestrial herb） - MAT：年均温（Mean average temperature，单位：℃） - MAP：年均降水量（Mean average precipitation，单位：mm） - BIO2：昼夜温差均值（Mean diurnal range，单位：℃） - BIO5：最热月最高温（Max temperature of warmest month，单位：℃） - BIO6：最冷月最低温（Min temperature of coldest month，单位：℃） - BIO13：最湿月降水量（Precipitation of wettest month，单位：mm） - BIO14：最干月降水量（Precipitation of driest month，单位：mm） - BIO15：降水季节性（变异系数，单位：mm） - Leaf S：叶片总硫浓度（Total sulphur concentrations in leaves，单位：mg g⁻¹） - Leaf N：叶片总氮浓度（Total nitrogen concentrations in leaves，单位：mg g⁻¹） - Leaf P：叶片总磷浓度（Total phosphorus concentrations in leaves，单位：mg g⁻¹） - NS：叶硫氮比（Ratio of leaf sulfur concentrations to leaf nitrogen concentrations） - PS：叶磷硫比（Ratio of leaf phosphorus concentrations to leaf sulfur concentrations） - NP：叶氮磷比（Ratio of leaf nitrogen concentrations to leaf phosphorus concentrations） ## 共享/获取信息 本数据集的其他公开获取链接：无。 数据是否源自其他来源？是。 本数据集的数据源自以下文献： [1] Cui P, Shen Z, Fu P, Bai K, Jiang Y, Cao K. 2020. 中国南方不同基质天然林植物叶片元素含量比较. 生态学报, 40: 9148-9163. [2] Fernández-Martínez M, Preece C, Corbera J, Cano O, Garcia-Porta J, Sardans J, Janssens IA, Sabater F, Peñuelas J. 2021. 环境与共存驱动的苔藓植物C:N:P化学计量学、生物地球化学生态位及元素组可塑性. 生态学快报, 24: 1375-1386. (doi:10.1111/ele.13752) [3] Dalle Fratte M, Pierce S, Zanzottera M, Cerabolini BEL. 2021. 叶片硫含量与叶片经济谱及植物适应策略的关联. 功能植物生物学, 48: 924-935. (doi:10.1071/FP20396) [4] Han WX, Fang JY, Reich PB, Woodward FI, Wang ZH. 2011. 中国区域不同气候、土壤与植物功能类型梯度下植物叶片11种矿质元素的生物地理学特征与变异. 生态学快报, 14: 788-796. (doi:10.1111/j.1461-0248.2011.01641.x) [5] Hou X. 1982. 中国植被地理与优势植物化学成分. 北京：科学出版社. [6] Kattge J, Bonisch G, Diaz S, Lavorel S, Prentice IC, Leadley P, Tautenhahn S, Werner GDA, Aakala T, Abedi M, et al. 2020. TRY植物性状数据库：覆盖范围扩展与开放获取. 全球变化生物学, 26: 119-188. (doi:10.1111/gcb.14904) [7] Sardans J, Vallicrosa H, Zuccarini P, Farré-Armengol G, Fernández-Martínez M, Peguero G, Gargallo-Garriga A, Ciais P, Janssens IA, Obersteiner M, et al. 2021. 林木生物地球化学生态位假说的实证支持. 自然·生态与进化, 5: 184-194. (doi:10.1038/s41559-020-01348-1) [8] Zhang J, Wang Y, Cai C. 2020. 中国西南高山草本植物Gentiana rigescens器官的多元素化学计量学研究. 植物科学前沿, 11: 441. (doi:10.3389/fpls.2020.00441) [9] Zhang SB, Zhang JL, Slik JWF, Cao KF. 2012. 中国陆生植物叶片元素含量受分类学与环境的影响. 全球生态学与生物地理学, 21: 809-818. (doi:10.1111/j.1466-8238.2011.00729.x) [10] Zuo Z, Zhao H, Yang L, Lv T, Li X, Ma F, Wang Z, Yu D. 2022. 盐胁迫诱导植物体内硫的异速积累并解除高山与干旱湿地植物的氮硫关联. 全球生物地球化学循环, 36: e2022GB007372. (doi:10.1029/2022GB007372)
