Data

Pre-European estimate of mean annual store of soil organic carbon (COrg0.Base) (kgC ha-1)

Also known as: substrate_corg0, Pre-European estimate of mean annual store of soil organic carbon (COrg0.Base) (kgC ha-1)
Atlas of Living Australia
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://spatial.ala.org.au/layers&rft.title=Pre-European estimate of mean annual store of soil organic carbon (COrg0.Base) (kgC ha-1)&rft.identifier=ala.org.au/uid_837&rft.publisher=Atlas of Living Australia&rft.description=This is the basic measure of the store of soil organic matter on the landscape. Like plant and litter carbon stores, the soil carbon stores are strongly controlled by Net Primary Production (NPP), and hence by rainfall and saturation deficit. All these C stores are also modulated by temperature because low temperatures slow the decay of plant material and high temperatures promote rapid decay. Typically, most soil carbon occurs in the upper soil layer. Derived from the BiosEquil model by Raupach et al. (2001a; 2001b). Soil nutrient outputs of the BiosEquil model Nutrient status is one of the key limiting factors determining the productivity of Australian vegetation systems, but is only broadly represented by gross nutrient status an attribute compiled from the Atlas of Australian Soils (McKenzie et al. 2000). We therefore additionally compiled the 0.05°gridded pre-European (base) predictions of carbon, nitrogen and phosphorous distributions which are outputs of the BiosEquil model by Raupach et al. (2001a; 2001b). These data are available from the Australian Natural Resources Atlas at www.nlwra.gov.au/atlas. Inputs to the pre-European models included meteorological surfaces of daily gridded data at 0.05° spatial resolution (for Australia) (Jeffrey et al. 2001), soil characteristics for current conditions derived from the Atlas of Australian Soils (McKenzie et al. 2000), and vegetation characteristics (Leaf Area Index) (Lu et al. 2001). The 0.05° gridded data were resampled to 0.01° using the cubic algorithm with RESAMPLE in ARCINFO GRID. Zero values were assumed to represent NODATA values (e.g. lakes) and were iteratively filled using the DATA option of the FOCALMEAN command with a CIRCLE expand radius of 3 cells in ARCINFO GRID, as described above.&rft.creator=Anonymous&rft.date=2014&rft.coverage=northlimit=-9.0 southlimit=-43.8 westlimit=112.9 eastLimit=153.64 projection=WGS84&rft_rights=Permission required to re-distribute derivative works. Please contact Dr. Kristen Williams - kristen.williams@csiro.au&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Substrate&rft_subject=Chemistry&rft.type=dataset&rft.language=English Access the data

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Permission required to re-distribute derivative works. Please contact Dr. Kristen Williams - kristen.williams@csiro.au

Full description

This is the basic measure of the store of soil organic matter on the landscape. Like plant and litter carbon stores, the soil carbon stores are strongly controlled by Net Primary Production (NPP), and hence by rainfall and saturation deficit. All these C stores are also modulated by temperature because low temperatures slow the decay of plant material and high temperatures promote rapid decay. Typically, most soil carbon occurs in the upper soil layer. Derived from the BiosEquil model by Raupach et al. (2001a; 2001b).

Soil nutrient outputs of the BiosEquil model
Nutrient status is one of the key limiting factors determining the productivity of Australian vegetation systems, but is only broadly represented by gross nutrient status an attribute compiled from the Atlas of Australian Soils (McKenzie et al. 2000). We therefore additionally compiled the 0.05°gridded pre-European (base) predictions of carbon, nitrogen and phosphorous distributions which are outputs of the BiosEquil model by Raupach et al. (2001a; 2001b). These data are available from the Australian Natural Resources Atlas at www.nlwra.gov.au/atlas. Inputs to the pre-European models included meteorological surfaces of daily gridded data at 0.05° spatial resolution (for Australia) (Jeffrey et al. 2001), soil characteristics for current conditions derived from the Atlas of Australian Soils (McKenzie et al. 2000), and vegetation characteristics (Leaf Area Index) (Lu et al. 2001). The 0.05° gridded data were resampled to 0.01° using the cubic algorithm with RESAMPLE in ARCINFO GRID. Zero values were assumed to represent NODATA values (e.g. lakes) and were iteratively filled using the DATA option of the FOCALMEAN command with a CIRCLE expand radius of 3 cells in ARCINFO GRID, as described above.
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Spatial Coverage And Location

iso19139dcmiBox: northlimit=-9.0 southlimit=-43.8 westlimit=112.9 eastLimit=153.64 projection=WGS84

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Identifiers
  • Local : ala.org.au/uid_837