Pan-European infrastructure for ocean & marine data management

P01 Vocabulary - Facet Search on Semantic Components

P01 Vocabulary - Facet Search on Semantic Components

The P01 Parameter Usage Vocabulary is based on a semantic model. This model uses a defined set of controlled vocabularies (the semantic components). The Facet Search below facilitates you to search for specific existing P01 terms using components for drilling down.

Are you missing specific P01 terms in the vocabulary, then you can compose and submit new terms for review and uptake using the P01 Vocabulary Builder tool.

Conceptid (61)Preflabel
CORPMOD1Concentration of organic phosphorus {organic_P CAS 7723-14-0} per unit volume of the water body [dissolved plus reactive particulate phase] by model prediction
CORPSPM1Concentration of organic phosphorus {organic_P CAS 7723-14-0} per unit volume of the sediment pore water [dissolved plus reactive particulate phase] by model prediction
CPHLMMMOConcentration monthly mean of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the water body by model prediction
CPHLMOD1Concentration of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the water body by model prediction
CPHLWSM1Concentration of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the wet sediment by model prediction
CRBMOD01Concentration of carbonate {CO32- CAS 3812-32-6} per unit volume of the water body by model prediction
CRBMOD0SConcentration of carbonate {CO32- CAS 3812-32-6} per unit volume of the sediment pore water by model prediction
CTOCMOD1Concentration of total carbon {total_C CAS 7440-44-0} per unit volume of the water body [dissolved plus reactive particulate phase] by model prediction
CTOCWSM1Concentration of total carbon {total_C CAS 7440-44-0} per unit volume of the wet sediment by model prediction
CTONMOD1Concentration of total nitrogen {total_N} per unit volume of the water body [dissolved plus reactive particulate phase] by model prediction
CTONWSM1Concentration of total nitrogen {total_N} per unit volume of the wet sediment by model prediction
CTOPMOD1Concentration of total phosphorus {total_P CAS 7723-14-0} per unit volume of the water body [dissolved plus reactive particulate phase] by model prediction
CTOPWSM1Concentration of total phosphorus {total_P CAS 7723-14-0} per unit volume of the wet sediment by model prediction
DOXYSPM1Concentration of oxygen {O2 CAS 7782-44-7} per unit volume of the sediment pore water [dissolved plus reactive particulate phase] by model prediction
NBRSMBM1Biomass as nitrogen of benthic microalgae [Subcomponent: intracellular reserve pool] per unit volume of the wet sediment by model prediction
NBRSMLP1Biomass as nitrogen of phytoplankton [Size: large Subcomponent: intracellular reserve pool] per unit volume of the wet sediment by model prediction
NBRSMSP1Biomass as nitrogen of phytoplankton [Size: small Subcomponent: intracellular reserve pool] per unit volume of the wet sediment by model prediction
NBRSMTR1Biomass as nitrogen of Trichodesmium (ITIS: 918: WoRMS 177604) [Subcomponent: intracellular reserve pool] per unit volume of the wet sediment by model prediction
NBRWMBM1Biomass as nitrogen of benthic microalgae [Subcomponent: intracellular reserve pool] per unit volume of the water body by model prediction
NBRWMLP1Biomass as nitrogen of phytoplankton [Size: large Subcomponent: intracellular reserve pool] per unit volume of the water body by model prediction
NBRWMSP1Biomass as nitrogen of phytoplankton [Size: small Subcomponent: intracellular reserve pool] per unit volume of the water body by model prediction
NBRWMTR1Biomass as nitrogen of Trichodesmium (ITIS: 918: WoRMS 177604) [Subcomponent: intracellular reserve pool] per unit volume of the water body by model prediction
NBSMMZ01Biomass as nitrogen of metazoan zooplankton per unit volume of the wet sediment by model prediction
NBSMPZ01Biomass as nitrogen of protozoan zooplankton per unit volume of the wet sediment by model prediction
NBSSMBM1Biomass as nitrogen of benthic microalgae [Subcomponent: structural cellular components] per unit volume of the wet sediment by model prediction