Phenology of Phytoplankton Size Classes in the Arabian Sea
Phytoplankton size classes (PSC) patterns are distinctive, tightly coupled to environmental controls of the upper ocean layer, with sensitiveness toward the seasonal cycle. This letter focuses on the phenology of PSC to investigate the spatiotemporal assemblage of each PSC influenced by the environm...
Gespeichert in:
| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 5 |
|---|---|
| container_issue | |
| container_start_page | 1 |
| container_title | IEEE geoscience and remote sensing letters |
| container_volume | 19 |
| creator | Shunmugapandi, Rebekah Gedam, Shirishkumar Inamdar, Arun B |
| description | Phytoplankton size classes (PSC) patterns are distinctive, tightly coupled to environmental controls of the upper ocean layer, with sensitiveness toward the seasonal cycle. This letter focuses on the phenology of PSC to investigate the spatiotemporal assemblage of each PSC influenced by the environmental drivers over the Arabian Sea (AS). We applied an abundance-based approach on 16-year time series gap-filled satellite-derived chl- a products to retrieve the PSC. Further, we estimated the PSC phenology indices for the AS as the timing of initiation, termination, duration, peak, and mean. The threshold criterion method is used to extract and map the PSC phenology indexes. The unique environmental adaptation of each PSC on both spatial and seasonal variability is highlighted and discussed based on the connection with the sea surface temperature (SST) and mixed layered depth (MLD). From the results, a new perspective is drawn on the PSC phenology patterns in the AS and how environmental controls influence each PSC. |
| doi_str_mv | 10.1109/LGRS.2021.3132660 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_LGRS_2021_3132660</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9635815</ieee_id><sourcerecordid>2616718126</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-d90a349997d8512e4ea7ab9dba0a7bb1342df353880c31a8c2f4bbf72c3518b03</originalsourceid><addsrcrecordid>eNo9kNFKwzAUhoMoOKcPIN4EvO7MSZom8W4MncLA4RS8C0mb2s7a1KS7mE9vy4ZX54fz_efAh9A1kBkAUXer5etmRgmFGQNGs4ycoAlwLhPCBZyOOeUJV_LjHF3EuCWEplKKCbpfV671jf_cY1_idbXvfdeY9qv3Ld7Uvw4vGhOji7hucV85PA_G1mbYOXOJzkrTRHd1nFP0_vjwtnhKVi_L58V8leRUsT4pFDEsVUqJQnKgLnVGGKsKa4gR1gJLaVEyzqQkOQMjc1qm1paC5oyDtIRN0e3hbhf8z87FXm_9LrTDS00zyARIoNlAwYHKg48xuFJ3of42Ya-B6FGRHhXpUZE-Kho6N4dO7Zz751XGuATO_gCaw2Ea</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2616718126</pqid></control><display><type>article</type><title>Phenology of Phytoplankton Size Classes in the Arabian Sea</title><source>IEEE Electronic Library (IEL)</source><creator>Shunmugapandi, Rebekah ; Gedam, Shirishkumar ; Inamdar, Arun B</creator><creatorcontrib>Shunmugapandi, Rebekah ; Gedam, Shirishkumar ; Inamdar, Arun B</creatorcontrib><description>Phytoplankton size classes (PSC) patterns are distinctive, tightly coupled to environmental controls of the upper ocean layer, with sensitiveness toward the seasonal cycle. This letter focuses on the phenology of PSC to investigate the spatiotemporal assemblage of each PSC influenced by the environmental drivers over the Arabian Sea (AS). We applied an abundance-based approach on 16-year time series gap-filled satellite-derived chl-<inline-formula> <tex-math notation="LaTeX">a </tex-math></inline-formula> products to retrieve the PSC. Further, we estimated the PSC phenology indices for the AS as the timing of initiation, termination, duration, peak, and mean. The threshold criterion method is used to extract and map the PSC phenology indexes. The unique environmental adaptation of each PSC on both spatial and seasonal variability is highlighted and discussed based on the connection with the sea surface temperature (SST) and mixed layered depth (MLD). From the results, a new perspective is drawn on the PSC phenology patterns in the AS and how environmental controls influence each PSC.</description><identifier>ISSN: 1545-598X</identifier><identifier>EISSN: 1558-0571</identifier><identifier>DOI: 10.1109/LGRS.2021.3132660</identifier><identifier>CODEN: IGRSBY</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Data models ; Environmental control ; Indexes ; Mixed layer depth (MLD) ; Ocean temperature ; Phenology ; Phytoplankton ; phytoplankton size classes (PSC) ; Plankton ; Satellites ; Sea surface ; Sea surface temperature ; sea surface temperature (SST) ; Seasonal variability ; Seasonal variation ; Seasonal variations ; spatio-temporal assemblage ; Surface temperature ; Time series analysis ; Timing ; Upper ocean</subject><ispartof>IEEE geoscience and remote sensing letters, 2022, Vol.19, p.1-5</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-d90a349997d8512e4ea7ab9dba0a7bb1342df353880c31a8c2f4bbf72c3518b03</citedby><cites>FETCH-LOGICAL-c293t-d90a349997d8512e4ea7ab9dba0a7bb1342df353880c31a8c2f4bbf72c3518b03</cites><orcidid>0000-0002-8521-7254</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9635815$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,4024,27923,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9635815$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shunmugapandi, Rebekah</creatorcontrib><creatorcontrib>Gedam, Shirishkumar</creatorcontrib><creatorcontrib>Inamdar, Arun B</creatorcontrib><title>Phenology of Phytoplankton Size Classes in the Arabian Sea</title><title>IEEE geoscience and remote sensing letters</title><addtitle>LGRS</addtitle><description>Phytoplankton size classes (PSC) patterns are distinctive, tightly coupled to environmental controls of the upper ocean layer, with sensitiveness toward the seasonal cycle. This letter focuses on the phenology of PSC to investigate the spatiotemporal assemblage of each PSC influenced by the environmental drivers over the Arabian Sea (AS). We applied an abundance-based approach on 16-year time series gap-filled satellite-derived chl-<inline-formula> <tex-math notation="LaTeX">a </tex-math></inline-formula> products to retrieve the PSC. Further, we estimated the PSC phenology indices for the AS as the timing of initiation, termination, duration, peak, and mean. The threshold criterion method is used to extract and map the PSC phenology indexes. The unique environmental adaptation of each PSC on both spatial and seasonal variability is highlighted and discussed based on the connection with the sea surface temperature (SST) and mixed layered depth (MLD). From the results, a new perspective is drawn on the PSC phenology patterns in the AS and how environmental controls influence each PSC.</description><subject>Data models</subject><subject>Environmental control</subject><subject>Indexes</subject><subject>Mixed layer depth (MLD)</subject><subject>Ocean temperature</subject><subject>Phenology</subject><subject>Phytoplankton</subject><subject>phytoplankton size classes (PSC)</subject><subject>Plankton</subject><subject>Satellites</subject><subject>Sea surface</subject><subject>Sea surface temperature</subject><subject>sea surface temperature (SST)</subject><subject>Seasonal variability</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>spatio-temporal assemblage</subject><subject>Surface temperature</subject><subject>Time series analysis</subject><subject>Timing</subject><subject>Upper ocean</subject><issn>1545-598X</issn><issn>1558-0571</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kNFKwzAUhoMoOKcPIN4EvO7MSZom8W4MncLA4RS8C0mb2s7a1KS7mE9vy4ZX54fz_efAh9A1kBkAUXer5etmRgmFGQNGs4ycoAlwLhPCBZyOOeUJV_LjHF3EuCWEplKKCbpfV671jf_cY1_idbXvfdeY9qv3Ld7Uvw4vGhOji7hucV85PA_G1mbYOXOJzkrTRHd1nFP0_vjwtnhKVi_L58V8leRUsT4pFDEsVUqJQnKgLnVGGKsKa4gR1gJLaVEyzqQkOQMjc1qm1paC5oyDtIRN0e3hbhf8z87FXm_9LrTDS00zyARIoNlAwYHKg48xuFJ3of42Ya-B6FGRHhXpUZE-Kho6N4dO7Zz751XGuATO_gCaw2Ea</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Shunmugapandi, Rebekah</creator><creator>Gedam, Shirishkumar</creator><creator>Inamdar, Arun B</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-8521-7254</orcidid></search><sort><creationdate>2022</creationdate><title>Phenology of Phytoplankton Size Classes in the Arabian Sea</title><author>Shunmugapandi, Rebekah ; Gedam, Shirishkumar ; Inamdar, Arun B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-d90a349997d8512e4ea7ab9dba0a7bb1342df353880c31a8c2f4bbf72c3518b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Data models</topic><topic>Environmental control</topic><topic>Indexes</topic><topic>Mixed layer depth (MLD)</topic><topic>Ocean temperature</topic><topic>Phenology</topic><topic>Phytoplankton</topic><topic>phytoplankton size classes (PSC)</topic><topic>Plankton</topic><topic>Satellites</topic><topic>Sea surface</topic><topic>Sea surface temperature</topic><topic>sea surface temperature (SST)</topic><topic>Seasonal variability</topic><topic>Seasonal variation</topic><topic>Seasonal variations</topic><topic>spatio-temporal assemblage</topic><topic>Surface temperature</topic><topic>Time series analysis</topic><topic>Timing</topic><topic>Upper ocean</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shunmugapandi, Rebekah</creatorcontrib><creatorcontrib>Gedam, Shirishkumar</creatorcontrib><creatorcontrib>Inamdar, Arun B</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>ProQuest Computer Science Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE geoscience and remote sensing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shunmugapandi, Rebekah</au><au>Gedam, Shirishkumar</au><au>Inamdar, Arun B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Phenology of Phytoplankton Size Classes in the Arabian Sea</atitle><jtitle>IEEE geoscience and remote sensing letters</jtitle><stitle>LGRS</stitle><date>2022</date><risdate>2022</risdate><volume>19</volume><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>1545-598X</issn><eissn>1558-0571</eissn><coden>IGRSBY</coden><abstract>Phytoplankton size classes (PSC) patterns are distinctive, tightly coupled to environmental controls of the upper ocean layer, with sensitiveness toward the seasonal cycle. This letter focuses on the phenology of PSC to investigate the spatiotemporal assemblage of each PSC influenced by the environmental drivers over the Arabian Sea (AS). We applied an abundance-based approach on 16-year time series gap-filled satellite-derived chl-<inline-formula> <tex-math notation="LaTeX">a </tex-math></inline-formula> products to retrieve the PSC. Further, we estimated the PSC phenology indices for the AS as the timing of initiation, termination, duration, peak, and mean. The threshold criterion method is used to extract and map the PSC phenology indexes. The unique environmental adaptation of each PSC on both spatial and seasonal variability is highlighted and discussed based on the connection with the sea surface temperature (SST) and mixed layered depth (MLD). From the results, a new perspective is drawn on the PSC phenology patterns in the AS and how environmental controls influence each PSC.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/LGRS.2021.3132660</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0002-8521-7254</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1545-598X |
| ispartof | IEEE geoscience and remote sensing letters, 2022, Vol.19, p.1-5 |
| issn | 1545-598X 1558-0571 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_LGRS_2021_3132660 |
| source | IEEE Electronic Library (IEL) |
| subjects | Data models Environmental control Indexes Mixed layer depth (MLD) Ocean temperature Phenology Phytoplankton phytoplankton size classes (PSC) Plankton Satellites Sea surface Sea surface temperature sea surface temperature (SST) Seasonal variability Seasonal variation Seasonal variations spatio-temporal assemblage Surface temperature Time series analysis Timing Upper ocean |
| title | Phenology of Phytoplankton Size Classes in the Arabian Sea |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T06%3A50%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Phenology%20of%20Phytoplankton%20Size%20Classes%20in%20the%20Arabian%20Sea&rft.jtitle=IEEE%20geoscience%20and%20remote%20sensing%20letters&rft.au=Shunmugapandi,%20Rebekah&rft.date=2022&rft.volume=19&rft.spage=1&rft.epage=5&rft.pages=1-5&rft.issn=1545-598X&rft.eissn=1558-0571&rft.coden=IGRSBY&rft_id=info:doi/10.1109/LGRS.2021.3132660&rft_dat=%3Cproquest_RIE%3E2616718126%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2616718126&rft_id=info:pmid/&rft_ieee_id=9635815&rfr_iscdi=true |