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Peat moisture dataset of Sumatra peatlands.
Taufik, Muh; Widyastuti, Marliana Tri; Santikayasa, I Putu; Arif, Chusnul; Minasny, Budiman.
Afiliação
  • Taufik M; Department of Geophysics and Meteorology, IPB University, Jalan Meranti Wing 19 Lvl 4 Darmaga Campus, Bogor 16680, Indonesia.
  • Widyastuti MT; School of Life and Environmental Science, Sydney Institute of Agriculture, The University of Sydney, Sydney, New South Wales 2006, Australia.
  • Santikayasa IP; Department of Geophysics and Meteorology, IPB University, Jalan Meranti Wing 19 Lvl 4 Darmaga Campus, Bogor 16680, Indonesia.
  • Arif C; Department of Civil and Environmental Engineering, IPB University, Darmaga Campus, Bogor 16680, Indonesia.
  • Minasny B; School of Life and Environmental Science, Sydney Institute of Agriculture, The University of Sydney, Sydney, New South Wales 2006, Australia.
Data Brief ; 46: 108889, 2023 Feb.
Article em En | MEDLINE | ID: mdl-36817731
Peatland is a unique ecosystem that is key in regulating global carbon cycle, climate, hydrology, and biodiversity. Peat moisture content is a key variable in ecohydrological and biogeochemical cycles known to control peatland's greenhouse gas emissions and fire vulnerability. Peat moisture is also an indicator of the success of peat restoration projects. Here we present datasets of peat moisture dynamic and retention capacity of degraded tropical peatlands. The data were collected from automatic daily monitoring and field campaigns. The peat moisture content data consists of daily data from 21 stations across three peatland provinces in Sumatra Island, Indonesia, from 2018 to 2019. In addition, peat water retention data were collected from field campaigns in Riau province. This dataset represents human modified peatlands which can be used as a benchmark for hydrological and biogeochemical models.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article