• Arctic SDI catalogue
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Neural network model output of marine phytoplankton primary production (Global Ocean)

Global phytoplankton production monthly maps for 2017 are produced using an artificial neural network to perform a generalized nonlinear regression of PP on several predictive variables, including latitude, longitude, day length, MLD, SST, PBopt computed according to Behrenfeld and Falkowski (1997), PAR and CHL(0 m). More details about this model can be found in Scardi (2001).

Behrenfeld, M. J., Falkowski, P. G. (1997), Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology & Oceanography, 42(1), 1–20.

Scardi, M. (2001), Advances in neural network modeling of phytoplankton primary production, Ecological Modelling, 146, 33–45.

Simple

Date ( Creation )
2018-01-29
Date ( Revision )
2018-02-12
Date ( Publication )
2018-05-09
Date ( Publication )
2018-10-10
Identifier
65cf1057-2785-46bb-85c1-51752047b791
Originator of Dataset
  University of Rome Tor Vergata -
Via Cracovia n.50 , Rome , 00133 , Italy
https://web.uniroma2.it/home/newlang/english
Author
  National Institute of Oceanography and Applied Geophysics - OGS, Division of Oceanography -
Borgo Grotta Gigante 42/c , Sgonico (Trieste) , 34010 , Italy
http://www.ogs.it
GEMET - INSPIRE themes, version 1.0 ( Theme )
  • Oceanographic geographical features
SeaVoX salt and fresh water body gazetteer ( Place )
  • World
SeaDataNet Agreed Parameter Groups ( Theme )
  • Rate measurements (including production, excretion and grazing)
SeaDataNet Parameter Discovery Vocabulary ( Theme )
  • Primary production in the water column
MEDIN data format categories ( featureType )
  • Text or Plaintext
BODC-approved data storage units (Spatial Unit) ( featureType )
  • Kilometres
BODC-approved data storage units (Vertical Unit) ( featureType )
  • Metres
Keywords
Access constraints
Other restrictions
Other constraints
no limitations to public access
Use limitation
Conditions for access and use apply
Use constraints
Other restrictions
Other constraints
ODC-By
Metadata language
En
Character set
UTF8
Topic category
  • Oceans
Begin date
2017-01-01
End date
2017-12-31
N
S
E
W
thumbnail


Vertical extent

Minimum value
0
Maximum value
0
Supplemental Information
Data and model description file (Phyro_prod_model_data_readme.docx)
Supplemental Information
monthly phytoplankton production map plot file (pp_2017.pdf)
Supplemental Information
IDL code to read and visualize monthly maps (pp_scardi_read.pro)
Unique resource identifier
WGS 1984

Spatial representation info

No information provided.
Distribution format
  • Text or Plaintext ( 1 )

OnLine resource
https://cloud.emodnet-ingestion.eu/index.php/s/879r5ByvTbb6VQ0 ( WWW:DOWNLOAD-1.0-http--download )
OnLine resource
https://www.seadatanet.org/ ( WWW:LINK-1.0-http--link )
OnLine resource
http://www.emodnet-biology.eu/ ( WWW:LINK-1.0-http--link )
OnLine resource
https://www.seadatanet.org/ ( WWW:LINK-1.0-http--link )
OnLine resource
http://www.emodnet-biology.eu/ ( WWW:LINK-1.0-http--link )
Hierarchy level
Dataset

Conformance result

Date ( Publication )
2010-12-08
Explanation
See the referenced specification
Pass
No

Conformance result

Date ( Publication )
2010-12-08
Explanation
See the referenced specification
Pass
No

Conformance result

Date ( Publication )
2010-12-08
Explanation
See the referenced specification
Pass
No
Statement

Several data sets were used to develop and validate the model. The largest one is still available at http://www.science.oregonstate.edu/ocean.productivity/field.data.c14.readme.php. Since field data were insufficient to calibrate the model in several regions, PP estimates from other models (VGPM, HYR, and the MOD-27 formulation (Esaias, 1996)) were considered as measurements where there were none. Therefore, this model can be regarded as a metamodel.

As vertical profiles with very high (and possibly biased) P/B ratios were filtered out, the PP estimates obtained from this model tend to be slightly lower than those from several other models. Comparisons with other global models of phytoplankton primary production can be found in Carr et al. (2006), Friedrichs et al. (2009), Saba et al. (2010a, 2010b) and Lee et al. (2015).

Carr M.E., Friedrichs M.A.M., Schmeltz M., Maki Noguchi A., Antoine D., Arrigo K.R., Asanuma I., Aumont O., Barber R., Behrenfeld M., Bidigare R., Buitenhuis E.T., Campbell J., Ciotti A., Dierssen H., Dowell M., Dunne J., Esaias W., Gentili B., Gregg W., Groom S., Hoepffner N., Ishizaka J., Kameda T., Le Quéré C., Lohrenz S., Marra J., Mélin F., Moore K., Morel A., Reddy T.A., Ryan J., Scardi M., Smyth T., Turpie K., Tilstone G., Waters K. & Yamanaka Y., (2006). A comparison of global estimates of marine primary production from ocean color. Deep-Sea Research II, 53: 741–770.

Friedrichs M.A.M., Carr M.-E., Barber R.T., Scardi M., Antoine D., Armstrong R.A:, Asanuma I., Behrenfeld M.J., Buitenhuis E.T., Chai F., Christian J.R., Ciotti A.M., Doney S.C., Dowell M., Dunne J., Gentili B., Gregg W., Hoepffner N., Ishizaka J., Kameda T., Lima I., Marra J., Mélin F., Moore J.K., Morel A., O’Malley R.T., O’Reilly J., Saba V.S., Schmeltz M., Smyth T.J., Tjiputra J., Waters K., Westberry T.K., Winguth A. (2009). Assessing the Uncertainties of Model Estimates of Primary Productivity in the Tropical Pacific Ocean. Journal of Marine Systems, 76: 113-133.

Esaias, W. (1996). MODIS algorithm theoretical basis document for product MOD-27: ocean primary productivity. Available at http://modis.gsfc.nasa.gov/data/atbd/atbd-mod24.pdf.

Lee Y.J., Matrai P.A., Friedrichs M.A., Saba V.S., Antoine D., Ardyna M., Asanuma I., Babin M., Bélanger S., Benoît-Gagné M., Devred E., Fernández-Méndez M., Gentili B., Hirawake T., Kang S.H., Kameda T., Katlein C., Lee S.H., Lee Z., Mélin F., Scardi M., Smyth T.J., Tang S., Turpie K.R., Waters K.J., Westberry T.K. (2015). An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models. Journal of Geophysical Research: Oceans, 120(9): 6508–6541.

Saba, V. S., Friedrichs, M. A. M. , Carr, M.-E., Antoine, D., Armstrong, R. A., Asanuma, I., Aumont, O., Bates, N. R., Behrenfeld, M. J., Bennington, V., Bopp, L., Bruggeman, J., Buitenhuis, E. T., Church, M. J., Ciotti, A. M., Doney, S. C., Dowell, M., Dunne, J., Dutkiewicz, S., Gregg, W., Hoepffner, N., Hyde, K. J. W., Ishizaka, J., Kameda, T., Karl, D. M., Lima, I., Lomas, M. W., Marra, J., McKinley, G. A., Mélin, F., Moore, J. K., Morel, A., Salihoglu, B., Scardi, M., Smyth, T. J., Tang, S., Tjiputra, J., Uitz, J., Vichi, M., Waters, K., Westberry, T. K.,

Saba, V. S., Friedrichs, M. A. M., Antoine, D., Armstrong, R. A., Asanuma, I., Behrenfeld, M. J., Ciotti, A. M., Dowell, M., Hoepffner, N., Hyde, K. J. W., Ishizaka, J., Kameda, T., Marra, J., Mélin, F., Morel, A., O'Reilly, J., Scardi, M., Smith Jr., W. O., Smyth, T. J., Tang, S., Uitz, J., Waters, K., Westberry, T. K. (2010b). An evaluation of ocean color model estimates of marine primary productivity in coastal and pelagic regions across the globe. Biogeosciences Discussions, 7: 6749-6788|The model uses an artificial neural network to perform a generalized nonlinear regression of PP on several predictive variables, including latitude, longitude, day length, MLD, SST, PBopt computed according to Behrenfeld and Falkowski (1997), PAR and CHL(0 m). More details about this model can be found in Scardi (2001).

Several data sets were used to develop and validate the model. The largest one is still available at http://www.science.oregonstate.edu/ocean.productivity/field.data.c14.readme.php. Since field data were insufficient to calibrate the model in several regions, PP estimates from other models (VGPM, HYR, and the MOD-27 formulation (Esaias, 1996)) were considered as measurements where there were none. Therefore, this model can be regarded as a metamodel.

As vertical profiles with very high (and possibly biased) P/B ratios were filtered out, the PP estimates obtained from this model tend to be slightly lower than those from several other models. Comparisons with other global models of phytoplankton primary production can be found in Carr et al. (2006), Friedrichs et al. (2009), Saba et al. (2010a, 2010b) and Lee et al. (2015).

References

Behrenfeld, M. J., Falkowski, P. G. (1997), Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology & Oceanography, 42(1), 1–20.

Carr M.E., Friedrichs M.A.M., Schmeltz M., Maki Noguchi A., Antoine D., Arrigo K.R., Asanuma I., Aumont O., Barber R., Behrenfeld M., Bidigare R., Buitenhuis E.T., Campbell J., Ciotti A., Dierssen H., Dowell M., Dunne J., Esaias W., Gentili B., Gregg W., Groom S., Hoepffner N., Ishizaka J., Kameda T., Le Quéré C., Lohrenz S., Marra J., Mélin F., Moore K., Morel A., Reddy T.A., Ryan J., Scardi M., Smyth T., Turpie K., Tilstone G., Waters K. & Yamanaka Y., (2006). A comparison of global estimates of marine primary production from ocean color. Deep-Sea Research II, 53: 741–770.

Friedrichs M.A.M., Carr M.-E., Barber R.T., Scardi M., Antoine D., Armstrong R.A:, Asanuma I., Behrenfeld M.J., Buitenhuis E.T., Chai F., Christian J.R., Ciotti A.M., Doney S.C., Dowell M., Dunne J., Gentili B., Gregg W., Hoepffner N., Ishizaka J., Kameda T., Lima I., Marra J., Mélin F., Moore J.K., Morel A., O’Malley R.T., O’Reilly J., Saba V.S., Schmeltz M., Smyth T.J., Tjiputra J., Waters K., Westberry T.K., Winguth A. (2009). Assessing the Uncertainties of Model Estimates of Primary Productivity in the Tropical Pacific Ocean. Journal of Marine Systems, 76: 113-133.

Esaias, W. (1996). MODIS algorithm theoretical basis document for product MOD-27: ocean primary productivity. Available at http://modis.gsfc.nasa.gov/data/atbd/atbd-mod24.pdf.

Lee Y.J., Matrai P.A., Friedrichs M.A., Saba V.S., Antoine D., Ardyna M., Asanuma I., Babin M., Bélanger S., Benoît-Gagné M., Devred E., Fernández-Méndez M., Gentili B., Hirawake T., Kang S.H., Kameda T., Katlein C., Lee S.H., Lee Z., Mélin F., Scardi M., Smyth T.J., Tang S., Turpie K.R., Waters K.J., Westberry T.K. (2015). An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models. Journal of Geophysical Research: Oceans, 120(9): 6508–6541.

Saba, V. S., Friedrichs, M. A. M. , Carr, M.-E., Antoine, D., Armstrong, R. A., Asanuma, I., Aumont, O., Bates, N. R., Behrenfeld, M. J., Bennington, V., Bopp, L., Bruggeman, J., Buitenhuis, E. T., Church, M. J., Ciotti, A. M., Doney, S. C., Dowell, M., Dunne, J., Dutkiewicz, S., Gregg, W., Hoepffner, N., Hyde, K. J. W., Ishizaka, J., Kameda, T., Karl, D. M., Lima, I., Lomas, M. W., Marra, J., McKinley, G. A., Mélin, F., Moore, J. K., Morel, A., Salihoglu, B., Scardi, M., Smyth, T. J., Tang, S., Tjiputra, J., Uitz, J., Vichi, M., Waters, K., Westberry, T. K., Yool, A. (2010a). Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT. Global Biogeochemical Cycles, 24, GB3020

Saba, V. S., Friedrichs, M. A. M., Antoine, D., Armstrong, R. A., Asanuma, I., Behrenfeld, M. J., Ciotti, A. M., Dowell, M., Hoepffner, N., Hyde, K. J. W., Ishizaka, J., Kameda, T., Marra, J., Mélin, F., Morel, A., O'Reilly, J., Scardi, M., Smith Jr., W. O., Smyth, T. J., Tang, S., Uitz, J., Wate

File identifier
65cf1057-2785-46bb-85c1-51752047b791 XML
Metadata language
en
Character set
UTF8
Hierarchy level
Dataset
Date stamp
2025-06-23T00:00:00
Metadata standard name
ISO 19115:2003/19139
Metadata standard version
1.0
Point of contact
  CNR, National Research Council, Institute of Atmospheric Sciences and Climate (Rome) - ( )
Via Fosso del Cavaliere, 100 , Rome , 00133 , Italy
http://www.isac.cnr.it
 
 

Overviews

Spatial extent

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S
E
W
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Keywords

GEMET - INSPIRE themes, version 1.0
Oceanographic geographical features
SeaDataNet Agreed Parameter Groups
Rate measurements (including production, excretion and grazing)
SeaDataNet Parameter Discovery Vocabulary
Primary production in the water column

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