65cf1057-2785-46bb-85c1-51752047b791 CNR, National Research Council, Institute of Atmospheric Sciences and Climate (Rome) Via Fosso del Cavaliere, 100 Rome 00133 Italy s.argentini@isac.cnr.it http://www.isac.cnr.it web site 2026-04-02T00:00:00 ISO 19115:2003/19139 1.0 WGS 1984 Neural network model output of marine phytoplankton primary production (Global Ocean) 2018-01-29 2018-02-12 2018-05-09 2018-10-10 65cf1057-2785-46bb-85c1-51752047b791 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. University of Rome Tor Vergata Via Cracovia n.50 Rome 00133 Italy rettore@uniroma2.it https://web.uniroma2.it/home/newlang/english web site National Institute of Oceanography and Applied Geophysics - OGS, Division of Oceanography Borgo Grotta Gigante 42/c Sgonico (Trieste) 34010 Italy nodc@ogs.it http://www.ogs.it web site Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2008-06-01 geonetwork.thesaurus.external.theme.httpinspireeceuropaeutheme-theme World SeaVoX salt and fresh water body gazetteer 2024-01-15 SeaVoX salt and fresh water body gazetteer Rate measurements (including production, excretion and grazing) SeaDataNet Agreed Parameter Groups 2023-07-04 SeaDataNet Agreed Parameter Groups SeaDataNet device categories 2024-01-16 SeaDataNet device categories SeaVoX Device Catalogue 2024-01-29 SeaVoX Device Catalogue Primary production in the water column SeaDataNet Parameter Discovery Vocabulary 2023-12-12 SeaDataNet Parameter Discovery Vocabulary CRUISE SUMMARY REPORT INVENTORY (CSR) 2023-10-02 SeaVoX Platform Categories 2024-01-16 SeaVoX Platform Categories ICES Platform Codes 2024-01-16 ICES Platform Codes EUROPEAN DIRECTORY OF MARINE ENVIRONMENTAL RESEARCH PROJECTS (EDMERP) 2020-06-05 Text or Plaintext MEDIN data format categories 2024-01-29 MEDIN data format categories World Register of Marine Species (WORMS) 2024-02-07 SeaDataNet Measurement Periodicity Categories 2024-01-29 SeaDataNet Measurement Periodicity Categories Kilometres BODC-approved data storage units (Spatial Unit) 2023-10-12 BODC-approved data storage units (Spatial Unit) Metres BODC-approved data storage units (Vertical Unit) 2023-10-12 BODC-approved data storage units (Vertical Unit) no limitations to public access Conditions for access and use apply ODC-By 4 Oceans 2017-01-01 2017-12-31 -180 180 -89 89 0 0 Data and model description file (Phyro_prod_model_data_readme.docx) monthly phytoplankton production map plot file (pp_2017.pdf) IDL code to read and visualize monthly maps (pp_scardi_read.pro) Text or Plaintext 1 https://cloud.emodnet-ingestion.eu/index.php/s/879r5ByvTbb6VQ0 WWW:DOWNLOAD-1.0-http--download https://www.seadatanet.org/ WWW:LINK-1.0-http--link http://www.emodnet-biology.eu/ WWW:LINK-1.0-http--link https://www.seadatanet.org/ WWW:LINK-1.0-http--link http://www.emodnet-biology.eu/ WWW:LINK-1.0-http--link COMMISSION REGULATION (EC) No 1205/2008 of 3 December 2008 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards metadata 2010-12-08 See the referenced specification false Corrigendum to INSPIRE Metadata Regulation published in the Official Journal of the European Union, L 328, page 83 2010-12-08 See the referenced specification false Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification false 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