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.2024.0346

• •    下一篇

2005-2015年鹤山站马占相思林长期监测样地的物种组成和群落特征数据集

饶兴权1,蔡锡安1,林永标1,刘素萍2   

  1. 1. 中国科学院华南植物园
    2. 中国科学院华南植物园;鹤山森林生态系统国家野外科学观测研究站
  • 收稿日期:2024-10-06 修回日期:2024-12-19 出版日期:2025-06-20 发布日期:2025-03-26

A dataset of species composition and community characteristics of long-term monitoring plot in Acacia mangium plantation in Heshan Station from 2005 to 2010.

兴权 饶1, 2,Yongbiao Lin1, 3   

  1. 1. 中国科学院华南植物园
    2.
    3. South China Botanical Garden, Chinese Academy of Sciences;Heshan National Field Research Station of Forest Ecosystem
  • Received:2024-10-06 Revised:2024-12-19 Online:2025-06-20 Published:2025-03-26

摘要: 随着社会的快速发展,人工林的规模处于不断扩大的趋势,如何有效地开展人工林经营管理及生态系统功能评价是一个长期的研究课题。中国科学院鹤山丘陵综合开放试验站(简称“鹤山站”)建于1984年,以“人工森林生态系统”为研究对象,遵循CERN长期观测规范,开展华南地区主要人工森林植被类型的群落动态观测,积累了长期数据。本数据集包含2005-2015年鹤山站马占相思林长期监测样地的物种组成和群落特征数据,以及数据集构建过程的信息。期望可为人工林经营管理及生态系统功能评价提供数据支撑。

关键词: 鹤山站, 马占相思林, 物种组成, 群落特征

Abstract: With the rapid development of society, the scale of plantation is continuously expanding. How to effectively carry out the management of plantation and evaluate the functions of the ecosystem is a long-term research topic. Heshan Hilly Comprehensive Open Experimental Station of the Chinese Academy of Sciences (hereafter referred to as Heshan Station) was established in 1984, focusing on "plantation ecosystems" as the research object, adhering to the long-term observation standards of CERN, and conducting long-term community dynamics observation of the main plantation types in the South China region, accumulating long-term data. This dataset includes the species composition and community characteristics data of the long-term monitoring plot of Acacia mangium plantation at Heshan Station from 2005 to 2015, as well as detailed information on the construction process of the dataset., It is expected to provide important data support for plantation management and ecosystem function evaluation.

Key words: Heshan Station, Acacia mangium plantation, species composition, community characteristics