Wang Qian, Nogueira Anselmo, Wan Ji-Zhong, Wang Chun-Jing, Li Lan-Ping
College of Agriculture and Animal Husbandry, Qinghai University, Xining City, Qinghai Province, China College of Agriculture and Animal Husbandry, Qinghai University Xining City, Qinghai Province China.
Centro de Ciências Naturais e Humanas, Universidade Federal do ABC, São Bernardo do Campo - SP, Brazil Centro de Ciências Naturais e Humanas, Universidade Federal do ABC São Bernardo do Campo - SP Brazil.
Biodivers Data J. 2023 Jul 26;11:e106254. doi: 10.3897/BDJ.11.e106254. eCollection 2023.
Here, we present data collected from the Qinghai-Tibet Plateau that describes the variation of leaf functional traits across 32 plant species and could be used to investigate plant community functioning and predict the impact of climate change on biogeochemical cycles. The sampling area is located in Huangshui River Valley, in the southeast of Qinghai Province, China (36° 19' to 36° 53' N, 100° 59' to 102° 48' E). The area contains an alpine meadow typical of the Qinghai-Tibet Plateau.
This dataset includes field survey data on the functional properties of compound leaves from herbaceous species in the Huangshui River Basin of Qinghai Province, China, at altitudes from 1800 m to 4000 m in the summer of 2021. Data were collected from 326 plots, including 646 data points of compound leaf plants, spanning 32 compound leaf plant species belonging to 14 genera and four families. The study species were chosen from 47 families, 165 genera and 336 species present in the plots and all compound leaf plants were chosen within each plot. We picked the parts containing leaves, petioles and rachis from the study plants and separated the leaves from the plants. The cut compound leaf part was a leaflet, while the petiole and rachis were linear elements. The dataset includes information about the leaflet trait variation (i.e. leaflet area, leaflet dry mass, specific leaflet area and leaflet nitrogen content per unit dry mass) and linear elements' biomass and nitrogen content per unit dry mass (i.e. both petiole and rachis) of 646 compound leaves. This dataset can be used to analyse the evolution of leaf traits and the basic functioning of ecosystems. Moreover, the dataset provides an important basis for studying the species distribution and protection of biodiversity of the Qinghai-Tibet Plateau and evaluating ecosystem services. These data also support the high-quality development of the Yellow River Basin and have empirical and practical value for alpine biodiversity protection and ecosystem management.
在此，我们展示了从青藏高原收集的数据，这些数据描述了32种植物叶片功能性状的变化，可用于研究植物群落功能并预测气候变化对生物地球化学循环的影响。采样区域位于中国青海省东南部的湟水河谷（北纬36°19′至36°53′，东经100°59′至102°48′）。该区域包含青藏高原典型的高山草甸。
本数据集包括2021年夏季在中国青海省湟水河流域海拔1800米至4000米处草本植物复叶功能特性的实地调查数据。数据收集自326个样地，包括646个复叶植物数据点，涵盖14个属、4个科的32种复叶植物。研究物种从样地中存在的47个科、165个属和336个物种中选取，每个样地内选取所有复叶植物。我们从研究植物中选取包含叶片、叶柄和叶轴的部分，并将叶片与植物分离。切割后的复叶部分为小叶，而叶柄和叶轴为线性部分。该数据集包括646片复叶的小叶性状变异信息（即小叶面积、小叶干质量、比小叶面积和单位干质量小叶氮含量）以及线性部分的生物量和单位干质量氮含量（即叶柄和叶轴）。该数据集可用于分析叶片性状的演变和生态系统的基本功能。此外，该数据集为研究青藏高原物种分布和生物多样性保护以及评估生态系统服务提供了重要依据。这些数据也支持黄河流域的高质量发展，对高山生物多样性保护和生态系统管理具有实证和实践价值。
