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    <identifier>10.11922/sciencedb.j00001.00397</identifier>
    <datestamp>2022-07-11T17:24:17Z</datestamp>
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  <dc:date>2022-07-11</dc:date>
  <dc:title>A dataset of soil moisture in Xishuangbanna tropical seasonal rain forest (2009 &amp;ndash; 2017)</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.j00001.00397</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>&amp;nbsp;As the carrier of material circulation and energy flow, soil moisture plays an important role in terrestrial forest ecosystems. Observation of soil moisture is helpful to reveal the hydrological characteristics, water conservation capacity and ecosystem service function of forest ecosystems. Tropical rain forest is one of the ecosystems with the most abundant biodiversity. There are large areas of tropical rain forest in Xishuangbanna, and tropical seasonal rain forest is the most representative vegetation type of rain forest in Xishuangbanna. Continuous, long-term and high-quality ecological monitoring is one of the main tasks of China Ecosystem Research Network (CERN). Soil moisture content is an important indicator of long-term positioning observation of water environment of CERN terrestrial ecosystems. This dataset collected soil moisture content data from January 2009 to December 2017 at the Xishuangbanna Station for Tropical Rainforest Ecosystem Studies of the Chinese Academy Sciences (also known as National Forest Ecosystem Research Station at Xishuangbanna, BNF for short), with a total of 2,879 entries; the determination method is fixed-point continuous observation by instrument of Time Domain Reflectometry (TDR); the observation depths are 0&amp;ndash;10 cm, 10&amp;ndash;20 cm, 20&amp;ndash;30 cm, 30&amp;ndash;40 cm, 40&amp;ndash;50 cm, 50&amp;ndash;70 cm, 70&amp;ndash;90 cm and 90&amp;ndash;110 cm; the observation frequency is 3 times per month, respective&amp;nbsp;at the beginning, middle and end of each month; observation strictly according to the CERN observation and quality control protocols. The dataset provides sharing service on line and it can be basic data support for tropical forest hydrological research under the global climate change and different vegetation environments.</dc:description>
  <dc:subject>tropical seasonal rain forest; soil moisture content; Time Domain Reflectometry; BNF</dc:subject>
  <dc:creator>Luo Yan</dc:creator>
  <dc:creator>Li Yuwu</dc:creator>
  <dc:creator>Qin Hailang</dc:creator>
  <dc:creator>Deng Xiaobao</dc:creator>
  <dc:creator>Chen Hui</dc:creator>
  <dc:creator>Sha Liqing</dc:creator>
  <dc:creator>Cao Min</dc:creator>
  <dc:creator>Lin Luxiang</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.11922/11-6035.csd.2022.0022.zh</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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