@article{cc64b0aa0a9b4e70ac9ac3225d532e28,
title = "A dataset of global ocean alkaline phosphatase activity",
abstract = "Utilisation of dissolved organic phosphorus (DOP) by marine microbes as an alternative phosphorus (P) source when phosphate is scarce can help sustain non-Redfieldian carbon:nitrogen:phosphorus ratios and efficient ocean carbon export. However, global spatial patterns and rates of microbial DOP utilisation are poorly investigated. Alkaline phosphatase (AP) is an important enzyme group that facilitates the remineralisation of DOP to phosphate and thus its activity is a good proxy for DOP-utilisation, particularly in P-stressed regions. We present a Global Alkaline Phosphatase Activity Dataset (GAPAD) with 4083 measurements collected from 79 published manuscripts and one database. Measurements are organised into four groups based on substrate and further subdivided into seven size fractions based on filtration pore size. The dataset is globally distributed and covers major oceanic regions, with most measurements collected in the upper 20 m of low-latitude oceanic regions during summer since 1997. This dataset can help support future studies assessing global ocean P supply from DOP utilisation and provide a useful data reference for both field investigations and modelling activities.",
author = "Bei Su and Xianrui Song and Solange Duhamel and Claire Mahaffey and Clare Davis and Ingrid Ivan{\v c}i{\'c} and Jihua Liu",
note = "Funding Information: We gratefully acknowledge the very helpful comments from our two anonymous reviewers. We want to thank all the researchers for sharing the data with us and making the compilation of this dataset possible, as well as all the staff of the Biological & Chemical Oceanography Data Management Office (BCO-DMO) and the British Oceanographic Data Centre (BODC) for enabling the access of the data.We would like to thank Dr. Dan Wang, Dr. Gwo-Ching Gong, Prof. Jeng Chang and Prof. Olivier Wurl for their assistance in compiling this dataset. We also acknowledge Dr. Markus Pahlow for his help in improving the writing language of the original manuscript. This research is jointly funded by the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. SML2020SP008), the National Key Research and Development Program of China (No. 2020YFA0608304) and the “Fundamental Research Fund of Shandong University” granted to Bei Su. Funding Information: We gratefully acknowledge the very helpful comments from our two anonymous reviewers. We want to thank all the researchers for sharing the data with us and making the compilation of this dataset possible, as well as all the staff of the Biological & Chemical Oceanography Data Management Office (BCO-DMO) and the British Oceanographic Data Centre (BODC) for enabling the access of the data.We would like to thank Dr. Dan Wang, Dr. Gwo-Ching Gong, Prof. Jeng Chang and Prof. Olivier Wurl for their assistance in compiling this dataset. We also acknowledge Dr. Markus Pahlow for his help in improving the writing language of the original manuscript. This research is jointly funded by the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. SML2020SP008), the National Key Research and Development Program of China (No. 2020YFA0608304) and the “Fundamental Research Fund of Shandong University” granted to Bei Su. Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
month = dec,
doi = "10.1038/s41597-023-02081-7",
language = "English (US)",
volume = "10",
journal = "Scientific Data",
issn = "2052-4463",
publisher = "Nature Publishing Group",
number = "1",
}