Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas
The vertically generalized production model (VGPM) is one of the most important methods for estimating marine net primary productivity (PP) using remote sensing. However, different data sources and parameterization schemes of the input variables for the VGPM can introduce uncertainties to the model...
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MDPI AG
2024-11-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/12/2146 |
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| author | Xiaolong Zhao Jianan Sun Qingjun Fu Xiao Yan Lei Lin |
| author_facet | Xiaolong Zhao Jianan Sun Qingjun Fu Xiao Yan Lei Lin |
| author_sort | Xiaolong Zhao |
| collection | DOAJ |
| description | The vertically generalized production model (VGPM) is one of the most important methods for estimating marine net primary productivity (PP) using remote sensing. However, different data sources and parameterization schemes of the input variables for the VGPM can introduce uncertainties to the model results. This study compared the PP results from different data sources and parameterization schemes of three major input variables (i.e., chlorophyll-a concentration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>), euphotic depth (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Z</mi><mrow><mi>e</mi><mi>u</mi></mrow></msub></mrow></semantics></math></inline-formula>), and maximum photosynthetic rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula>)) and evaluated the sensitivity of VGPM in the Yellow and Bohai Seas on the inputs. The results showed that the sensitivity in the annual mean PP was approximately 40%. Seasonally, the sensitivity was lowest in the spring (35%), highest in the winter (70%), and approximately 60% in the summer and autumn. Spatially, the sensitivity in nearshore water (water depth < 40 m) was more than 60% and around two times higher than that in deep water areas. Nevertheless, all VGPM results showed a decline trend in the PP from 2003 to 2020 in the Yellow and Bohai Seas. The influence of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> was important for the magnitude of annual mean PP. The PP seasonal variation pattern was highly related to the parameterization scheme of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula>, whereas the spatial distribution was mostly sensitive to the data sources of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>. |
| format | Article |
| id | doaj-art-b6f82719e7d3497ebbd67cd2a6f3c8f7 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-b6f82719e7d3497ebbd67cd2a6f3c8f72024-12-27T14:33:05ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-11-011212214610.3390/jmse12122146Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf SeasXiaolong Zhao0Jianan Sun1Qingjun Fu2Xiao Yan3Lei Lin4North China Sea Marine Forecasting Center, Ministry of Natural Resources of the People’s Republic of China, Qingdao 266061, ChinaNingbo Yonghuanyuan Environmental Engineering and Technology Co., Ltd., Ningbo 315000, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Ocean Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaThe vertically generalized production model (VGPM) is one of the most important methods for estimating marine net primary productivity (PP) using remote sensing. However, different data sources and parameterization schemes of the input variables for the VGPM can introduce uncertainties to the model results. This study compared the PP results from different data sources and parameterization schemes of three major input variables (i.e., chlorophyll-a concentration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>), euphotic depth (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>Z</mi><mrow><mi>e</mi><mi>u</mi></mrow></msub></mrow></semantics></math></inline-formula>), and maximum photosynthetic rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula>)) and evaluated the sensitivity of VGPM in the Yellow and Bohai Seas on the inputs. The results showed that the sensitivity in the annual mean PP was approximately 40%. Seasonally, the sensitivity was lowest in the spring (35%), highest in the winter (70%), and approximately 60% in the summer and autumn. Spatially, the sensitivity in nearshore water (water depth < 40 m) was more than 60% and around two times higher than that in deep water areas. Nevertheless, all VGPM results showed a decline trend in the PP from 2003 to 2020 in the Yellow and Bohai Seas. The influence of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula> was important for the magnitude of annual mean PP. The PP seasonal variation pattern was highly related to the parameterization scheme of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>P</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow><mi>B</mi></msubsup></mrow></semantics></math></inline-formula>, whereas the spatial distribution was mostly sensitive to the data sources of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>C</mi><mrow><mi>o</mi><mi>p</mi><mi>t</mi></mrow></msub></mrow></semantics></math></inline-formula>.https://www.mdpi.com/2077-1312/12/12/2146shelf seamarine primary productivitysatellite remote sensingchlorophyll-a |
| spellingShingle | Xiaolong Zhao Jianan Sun Qingjun Fu Xiao Yan Lei Lin Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas Journal of Marine Science and Engineering shelf sea marine primary productivity satellite remote sensing chlorophyll-a |
| title | Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas |
| title_full | Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas |
| title_fullStr | Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas |
| title_full_unstemmed | Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas |
| title_short | Sensitivity Assessment on Satellite Remote Sensing Estimates of Primary Productivity in Shelf Seas |
| title_sort | sensitivity assessment on satellite remote sensing estimates of primary productivity in shelf seas |
| topic | shelf sea marine primary productivity satellite remote sensing chlorophyll-a |
| url | https://www.mdpi.com/2077-1312/12/12/2146 |
| work_keys_str_mv | AT xiaolongzhao sensitivityassessmentonsatelliteremotesensingestimatesofprimaryproductivityinshelfseas AT jianansun sensitivityassessmentonsatelliteremotesensingestimatesofprimaryproductivityinshelfseas AT qingjunfu sensitivityassessmentonsatelliteremotesensingestimatesofprimaryproductivityinshelfseas AT xiaoyan sensitivityassessmentonsatelliteremotesensingestimatesofprimaryproductivityinshelfseas AT leilin sensitivityassessmentonsatelliteremotesensingestimatesofprimaryproductivityinshelfseas |