<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20200507</CreaDate>
<CreaTime>15152800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs/>
<searchKeys>
<keyword>Above ground</keyword>
<keyword>herbaceous</keyword>
<keyword>biomass</keyword>
<keyword>NLC 2014</keyword>
<keyword>land cover</keyword>
<keyword>CarbonSinksAtlasV3</keyword>
</searchKeys>
<idPurp>The above ground herbaceous biomass is a very small fraction of the total terrestrial organic carbon stocks and it was calculated with the same model as in the 2014 NTCSA dataset. The equation incorporates Rain Use Efficiency, amount of rain required to enable production per year and tree cover fraction. A mean herbaceous layer is modelled based on mean long term rainfall. The above ground herbaceous biomass was based on harvest factors obtained from the 2002 Agricultural Census. A proportional approach per land use, based on 2014 National Land Cover (NLC) data was used for the soil organinc carbon (SOC) analysis.</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
<idCitation>
<resTitle>Map</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">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</Data>
</Thumbnail>
</Binary>
</metadata>
