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    <identifier>10.57760/sciencedb.25375</identifier>
    <datestamp>2025-09-16T11:56:40Z</datestamp>
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  <dc:date>2025-09-16</dc:date>
  <dc:title>High-resolution maps of forest soil bulk density and pH across China at 90-m resolution</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.25375</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset maps two key forest soil properties: bulk density and pH, across China at a spatial resolution of 90 meters and five standardized depth layers (0&amp;ndash;5, 5&amp;ndash;15, 15&amp;ndash;30, 30&amp;ndash;60, and 60&amp;ndash;100 cm). The source data comprises 4,356 forest-specific soil profiles combined with 41 high-resolution environmental covariates, including climate, vegetation, and terrain variables. Quantile Regression Forests with forward selection and hyperparameter tuning were employed to generate the predictions. Model performance was evaluated via 10-fold cross-validation and independent validation, showing strong predictive accuracy (bulk density: 0.78&amp;ndash;0.89 in cross-validation, 0.60&amp;ndash;0.66 in independent validation; pH: 0.84&amp;ndash;0.87 in cross-validation, 0.71&amp;ndash;0.81 in independent validation). The spatial patterns reflect varying pedogenic controls by depth and property, with climate influencing bulk density and vegetation&amp;ndash;parent material interactions dominating pH. The dataset supports forest-specific modeling of soil carbon, acidification, and land surface processes.</dc:description>
  <dc:subject>Forest soil ; Bulk density; Soil pH ; digital soil mapping</dc:subject>
  <dc:creator>chen jizhen</dc:creator>
  <dc:creator>huang zhilin</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.5194/essd-2025-496</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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