植物生态学报 ›› 2025, Vol. 49 ›› Issue (典型生态系统数据集): 0-0.DOI: 10.17521/cjpe.2024.0330

• •    下一篇

2018-2023年黄土高原丘陵沟壑区川台地农田长期监测样地作物收获期性状和产量数据集

王志波1,2,刘文胜1,2,吴瑞俊1,王国梁1,2   

  1. 1. 西北农林科技大学水土保持科学与工程学院
    2. 中国科学院水利部水土保持研究所
  • 收稿日期:2024-09-29 修回日期:2024-12-17 出版日期:2025-06-20 发布日期:2025-03-26

Dataset of Crop Harvest Traits and Yields from Long-term Monitored Farmland Plots on Fluvial Terraces in the Hilly and Gully Region of the Loess Plateau from 2018 to 2020

Zhi-Bo WANG1,2,3,4,Wen-Sheng LIU1,2,3,4,Rui-Jun WU1,4,Guo-Liang WANG5,6   

  1. 1. College of Soil and Water Conservation Science and Engineering, Northwest A&F University
    2. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources
    3. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources
    4. College of Soil and Water Conservation Science and Engineering, Northwest A&F University
    5. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources; State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau, Northwest Sci-Tech University of Agriculture and Forestry
    6.
  • Received:2024-09-29 Revised:2024-12-17 Online:2025-06-20 Published:2025-03-26

摘要： 黄土高原丘陵沟壑区是黄土高原最具代表性的地貌单元之一，其复杂破碎的地形条件和脆弱的生态环境决定了该地区农业生产的特殊性。川台地作为该区域的重要农业耕作区，因其地势平坦、土壤肥沃是该区域典型的农田生态系统类型。作物性状和产量作为农田生态系统长期监测中的基础要素，可直接反映农田的生产力，也是衡量农田可持续性的重要指标。连续多年对川台地农田生态要素观测，对于深入理解农田生态系统的动态变化及其与环境因素的相互作用具有重要意义。陕西安塞农田生态系统国家野外科学观测研究站（简称安塞站）是研究干旱半干旱黄土高原丘陵区的核心研究平台，隶属于中国生态系统研究网络（CERN）和国家生态系统观测研究网络（CNERN），也是黄土高原丘陵沟壑区农田生态系统长期野外观测的重要平台。本数据集整合了安塞站川台地（2018–2023年）典型耕作制度下3个农田长期定位观测场的作物收获期性状和产量等观测数据，主要包括样地长期轮作体系、肥料投入、农药/除草剂/生长剂投入、收获期性状、收获期测产等数据。此数据集为研究和评估区域农田生态系统的生产力与稳定性、优化农业管理措施及制定相关农业政策提供科学数据支撑。

关键词: 作物收获期性状, 作物产量, 长期监测数据, 黄土丘陵沟壑区

Abstract: The hilly and gully region is one of the most representative geomorphological units of the Loess Plateau. The complex and fragmented terrain, along with its fragile ecological environment, determines the unique characteristics of agricultural production in this region. The Fluvial Terraces, as an important agricultural cultivation area in this region, is characterized by its flat terrain and fertile soil, making it a typical agricultural ecosystem type of the region. Crop traits and yield, as fundamental elements in long-term monitoring of agricultural ecosystems, can directly reflect the productivity of farmland and are important indicators for assessing agricultural sustainability. Continuous multi-year observations of agricultural ecosystem elements in the Fluvial Terraces are crucial for a comprehensive of the dynamic changes in agricultural ecosystems and their interactions with environmental factors. The Ansai Farmland Ecosystem National Field Scientific Observation and Research Station (referred to as the Ansai Station) is a core research platform dedicated to the arid and semi-arid hilly regions of the Loess Plateau. It is affiliated with the Chinese Ecosystem Research Network (CERN) and the National Ecosystem Observation and Research Network (CNERN). The Ansai Station serves as a crucial platform for long-term field observations of farmland ecosystems in the hilly and gully region of the Loess Plateau. This dataset integrates ecological observation data from three long-term monitoring fields on Fluvial terraces at Ansai Station (2018–2023) under typical cultivation systems, including long-term crop rotation systems, fertilizer inputs, applications of pesticides, herbicides, and growth regulators, harvest period traits, and yield measurements. This dataset provides valuable data support for evaluating the productivity and stability of regional farmland ecosystems, optimizing agricultural management practices, and formulating relevant agricultural policies.

Key words: Crop harvest traits, grain yield, Long-term monitoring data, Loess Plateau hilly and gully region

Copyright © 2022 版权所有 《植物生态学报》编辑部
地址: 北京香山南辛村20号, 邮编: 100093
Tel.: 010-62836134, 62836138;　Fax: 010-82599431;　E-mail: apes@ibcas.ac.cn, cjpe@ibcas.ac.cn
备案号: 京ICP备16067583号-19