Dataset for "Growing-season precipitation is a key driver of plant leaf area to sapwood area ratio at the global scale"

A_L/A_S data were obtained from two distinct sources and: i) Field Measurements: We conducted A_L/A_S measurements across 201 species in China. Terminal branches, ranging from 6 to 8 mm in diameter and 60 to 100 cm in length, were sampled from five mature individuals per species in the early morning. These samples were promptly placed in black plastic bags with a moist towel to maintain freshness and prevent wilting, and then transported directly to the laboratory. Leaf area (A_L) was measured using a leaf area meter (Li-3000A; Li-Cor, USA). For the sapwood area (A_S), stem diameter (without bark) and pith diameter were measured. The sapwood area was then calculated by subtracting the pith area from the total stem area. A_L/A_S was calculated as the ratio of leaf area attached per unit of sapwood cross-sectional area; ii) Plant Traits Database and Published Literatures: 137 data observations regarding "leaf area to sapwood area ratio" and "Huber value" were extracted from TRY Plant Traits Database (https ://www.try-db.org/TryWeb/Home.php; Kattge et al., 2020). We conducted searches on Web of Science, Google Scholar, and China National Knowledge Infrastructure (http://www.cnki.net) using the keywords "leaf area to sapwood area ratio", "Huber value", and "hydraulic traits". Xylem-specific hydraulic conductivity (K_S; kg m^-1 s^-1 MPa^-1) indicates the water transport efficiency of xylem tissue. K_S affects plant transpiration, photosynthesis, growth, survival, and the geographic distribution of species (Gleason et al., 2016). K_S data were collected simultaneously to explore the covariance between A_L/A_S, K_S, and climate.

To minimize ontogenetic and methodological variation, data were included based on the following criteria: (a) Wild plants thriving within natural ecosystems, excluding those cultivated in greenhouses or common garden experiments; (b) Measurements were conducted on adult plants or saplings, excluding seedlings; (c) A_L/A_S was measured only on branches at the crown; (d) A_L/A_S was calculated as the mean value for each species at the same site when data were from multiple sources.

To elucidate the environmental factors influencing global variation in A_L/A_S, we investigated the impacts of 14 abiotic and biotic features on A_L/A_S, including mean annual precipitation (MAP), mean annual temperature (MAT), aridity index (AI), growing-season precipitation (P_gs), growing-season temperature (T_gs), precipitation of the driest month (P_dm), minimum temperature of the coldest month (T_cm), annual mean daily irradiance (MAR), soil pH, soil cation exchange capacity (CEC), soil organic carbon concentration (SOC), soil total nitrogen concentration (soil N), soil total phosphorus concentration (soil P), and tree density (TD). Climate data were sourced from original reports where available, and nearly half of MAP and MAT data were obtained via this approach; otherwise, variables such as mean annual and monthly precipitation, temperature, solar radiation, minimum temperature of the coldest month (T_cm), and precipitation of the driest month (P_dm) were extracted from WorldClim version 2 (http://world clim.org/version2; Fick & Hijmans, 2017). Annual and monthly PET (potential evapotranspiration) were obtained from the CGIAR-CSI consortium (http://www.cgiar-csi.org/data; Zomer et al., 2008). The aridity index (monthly or annual) represents the ratio of precipitation to PET. We defined the growing season as the consecutive months meeting the criteria: (a) monthly mean temperature ≥ 5°C and (b) monthly aridity index ≥0.05 (Wright et al., 2017). Soil factors including soil pH, SOC, CEC, and soil N were acquired from ISRIC (https://www.isric.org/explore/wosis/accessing-wosis-derived-datasets) and soil P was extracted from He et al. (2021). Tree density data was at the community level and obtained from a map of global tree density (Crowther et al., 2015). To assess the correlation between plant A_L/A_S and ecosystem production, we calculated the annual NPP using Landsat data (http://www.ntsg.umt.edu). We extracted one value of environmental factors and NPP data for each studied site.

Following the Whittaker biome diagram (Whittakker, 1975), the sites were categorized into distinct biomes, including tropical rainforest, tropical seasonal forest/savanna, temperate seasonal forest, woodland/shrubland, boreal forest, and desert (Figure S2). Plant species were classified into three PFTs based on data extracted from source publications and online flora (e.g., http://frps.eflora.cn/). These included conifers, evergreen broad-leaved species, and deciduous broad-leaved species.