2007–2017年青藏高原东南缘贡嘎山峨眉冷杉林土壤含水量数据集
收藏国家生态科学数据中心2024-03-04 收录
下载链接:
http://www.nesdc.org.cn/sdo/detail?id=64f864ef7e281736629e9414
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资源简介:
土壤水分作为陆地生态系统水循环的核心,是森林生态系统物质和能量循环的重要载体,在森林生态系统水文过程及养分循环等方面发挥了重要的作用。土壤含水量是陆地生态系统水环境长期定位观测的重要指标之一。按照CERN的统一规范,贡嘎山站在开展了土壤水分含量长期监测工作。本数据集收集整理了2007–2017年峨眉冷杉成熟林、峨眉冷杉演替中龄林、峨眉冷杉冬瓜杨演替林和3000米气象观测场的土壤含水量数据,这对了解气候变化下该区域森林土壤水分动态特征及其响应变化提供了数据支撑,对区域森林生态系统森林水量平衡、森林生产力形成及生态服务功能具有重要意义。数据集由1个数据文件组成,数据量1945条,包含了用中子仪法测定的峨眉冷杉成熟林、峨眉冷杉演替中龄林、峨眉冷杉冬瓜杨演替林和3000米气象观测场的土壤含水量数据。
Soil moisture, as the core of the water cycle in terrestrial ecosystems, serves as a critical carrier for material and energy cycling in forest ecosystems, and plays a vital role in hydrological processes and nutrient cycling of forest ecosystems. Soil water content is one of the key indicators for long-term in-situ observations of the water environment in terrestrial ecosystems. In accordance with the unified standards of the Chinese Ecosystem Research Network (CERN), the Gongga Mountain Station has carried out long-term monitoring of soil water content. This dataset compiles soil water content data collected from 2007 to 2017, covering four sampling sites: mature stands of *Abies fabri*, middle-aged successional stands of *Abies fabri*, successional stands of *Abies fabri* and *Populus davidiana*, and the 3000-meter meteorological observation station. This dataset provides essential data support for exploring the dynamic characteristics and responsive changes of forest soil moisture under climate change in this region, and holds great significance for studying regional forest ecosystem water balance, forest productivity formation and ecological service functions. The dataset consists of 1 data file with a total of 1945 records, containing soil water content data measured via the neutron probe method at the four aforementioned sampling sites.
创建时间:
2021-04-28
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集提供了2007–2017年青藏高原东南缘贡嘎山地区峨眉冷杉林土壤含水量的长期监测数据,覆盖成熟林、演替中龄林和冬瓜杨演替林等多种森林类型,采用中子仪法测定,共1945条数据。数据集旨在支持森林生态系统水循环、气候变化响应及生态服务功能研究,具有重要的科学价值和应用前景。
以上内容由遇见数据集搜集并总结生成



