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Search results for: "keyword:"soil organic carbon""

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Chemical properties of forest and pasture soils in Cajanuma at 3000 m asl
Dataset ID: 1869
Last updated: 2020-11-09
Dataset creators: Andre Velescu
Tobias Fabian
Wolfgang Wilcke
Contact: Andre Velescu
Temporal coverage: 2018-11-03 00:00:00 - 2019-11-08 00:00:00
Geographic coverage: Cajanuma
Abstract: The dataset includes chemical properties of the o...
Additional info: ---
Keywords: | electric conductivity | soil characteristics | Cajanuma | cation exchange capacity | soil pH | soil nutrients | soil organic carbon | total organic C | core plots | pH values | total phosphorus | soil horizons | exchangeable cations | total element concentrations | available nitrogen | available phosphorus |
Intellectual rights: FOR2730 data user agreement. (www.tropicalmountainforest.org/dataagreementp3.do)
1. Entity:
Entity name: caj_soil_profiles_metadata
Entity info: Cajanuma soil profiles metadata
Entity type:dataTable
Attributes:
Datetime of specific event (eventdatetime) (Unitless)
Site name (Site_name) (Unitless)
land use (Land_use) (Unitless)
ID of the plot (PlotID) (Unitless)
Section (Section) (Unitless)
Comment (Comment) (Unitless)
ID of the subplot (subplot_id) (Unitless)
UTM x-coordinate (UTMCoordX) [Meter]
UTM y-coordinate (UTMCoordY) [Meter]
Minimum geographic latitude (geocoordinate_latitude_min) [Degree]
Maximum geographic latitude (geocoordinate_latitude_max) [Degree]
Minimum geographic longitude (geocoordinate_longitude_min) [Degree]
Maximum geographic longitude (geocoordinate_longitude_max) [Degree]
Height above mean sea level (geocoordinate_amsl) [Meter]
Exposition (expo_angle) [Degree]
slope (Slope) [Degree]
Soil development depth (Zsmax) [Meter]
2. Entity:
Entity name: caj_ol_forest_chemical_properties
Entity info: Cajanuma forest soils - chemical properties of organic layer
Entity type:dataTable
Attributes:
Datetime of specific event (eventdatetime) (Unitless)
Site name (Site_name) (Unitless)
land use (Land_use) (Unitless)
ID of the plot (PlotID) (Unitless)
ID of the sample (SampleID) (Unitless)
Section (Section) (Unitless)
Soil horizon symbol after "world reference base" (Horizon_WRB) (Unitless)
Thickness of the horizon (Horizon_thickness) [Meter]
electrical conductivity of streamwater (ECw) [Microsiemens per centimeter]
pH of soil H2O (PHs_H2O) [Unitless]
pH of soil KCl (PHs_KCl) [Unitless]
Total carbon of soil (TCs) [Gram per kilogram]
Total nitrogen of soil (TNs) [Gram per kilogram]
Total Sulphur of soil (TSs) [Gram per kilogram]
Total phosphorus soil (TPs) [Gram per kilogram]
Total element Potassium of soil (TE_K) [Gram per kilogram]
Total Na (TE_Na) [Milligram per kilogram]
Total element Magnesium of soil (TE_Mg) [Gram per kilogram]
Total element Calcium of soil (TE_Ca) [Gram per kilogram]
Total element Aluminum of soil (TE_Al) [Gram per kilogram]
Total element Iron of soil (TE_Fe) [Gram per kilogram]
Total element Manganese of soil (TE_Mn) [Gram per kilogram]
Total Zn (TE_Zn) [Milligram per kilogram]
C/N ratio (CN_ratio) [Ratio]
Extractable ammonium in soil (NH4s) [Milligram of nitrogen per kilogram]
Extractable nitrate in soil (NO3s) [Milligram of nitrogen per kilogram]

Soil organic carbon stocks in the ECSF area (spatial prediction)
Dataset ID: 1477
Last updated: 2016-05-31
Dataset creators: Mareike Ließ
Contact: Mareike Ließ
Temporal coverage: 2011-03-01 00:00:00 - 2015-12-31 00:00:00
Geographic coverage: ECSF DEM 10m
Abstract:
Additional info: Please refer to "Ließ et al. (2016), Improving th...
Keywords: | ECSF | boosted regression trees | soil organic carbon | digital soil mapping |
Intellectual rights: Ließ et al. (2016), Improving the spatial prediction of soil organic carbon stocks in a complex tropical mountain landscape by methodological specifications in machine learning approaches. PLoS ONE, 11(4): e0153673. doi:10.1371/journal.pone.0153673
1. Entity:
Entity name: SOC stocks spatial density function values
Entity info: The columns of this data matrix refer to the UTM coordinates, the prediction median (SOC_BRTMED), interquartile range (SOC_BRTIQR), 25% (SOC_BRTQ25) and 75% (SOC_BRTQ75) quantiles of the position specific density functions of the prediction.
Entity type:otherEntity


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