2017–2024 年高寒草甸植物生物量和土壤化学性状对氮添加和降水改变的响应观测数据集

Alpine meadow ecosystems play an irreplaceable role in maintaining the ecological barrier function of the Qinghai-Tibet Plateau and supporting regional sustainable development. Understanding the response mechanisms to increased atmospheric nitrogen deposition and altered precipitation patterns is essential for predicting the trajectory of ecological functions under global change. Following the protocols of globally standardized large-scale networked experiments, researchers established a full-factorial experimental platform with nitrogen addition (10 g·m–²·a–¹) and precipitation manipulation (±50% of ambient precipitation) at the Haibei Alpine Grassland Ecosystem National Field Observation and Research Station on the southern foothills of the Lenglongling Mountains in the eastern Qilian Mountains, Qinghai Province, China. Continuous measurements of plant biomass and soil properties were conducted during the peak growing season (late August). To advance the understanding of the response and adaptation of alpine meadow ecological functions to global change, the research team intends to publicly release an observational dataset spanning 2017–2024, focusing on plant biomass and soil chemical properties in response to nitrogen addition and precipitation manipulation. The dataset includes: (1) aboveground biomass of the plant community and functional groups (grasses, sedges, legumes, and forbs), litter biomass, and 0–10 cm belowground biomass; (2) 0–10 cm soil organic carbon content, total nitrogen, total phosphorus, and soil pH; (3) mean annual air temperature and total annual precipitation. The collection and analysis of plant and soil samples strictly followed relevant standards or commonly used methods, ensuring data accuracy and comparability. This dataset provides robust data support for modeling the carbon cycle and evaluating the carbon sink function of alpine meadow ecosystems under scenarios of coupled atmospheric nitrogen deposition and altered precipitation patterns.