Preprints
https://doi.org/10.5194/bg-2022-11
https://doi.org/10.5194/bg-2022-11
17 Jan 2022
 | 17 Jan 2022
Status: this preprint was under review for the journal BG but the revision was not accepted.

Pronounced seasonal and spatial variability in determinants of phytoplankton biomass dynamics along a near–offshore gradient in the southern North Sea

Viviana Otero, Steven Pint, Klaas Deneudt, Maarten De Rijcke, Jonas Mortelmans, Lennert Schepers, Patricia Cabrera, Koen Sabbe, Wim Vyverman, Michiel Vandegehuchte, and Gert Everaert

Abstract. Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient–phytoplankton–zooplankton model to quantify the relative importance of bottom-up and top-down determinants on phytoplankton biomass dynamics in the Belgian Part of the North Sea. Using four years (2014–2017) of monthly observations at nine locations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a and zooplankton biomass, we disentangled the monthly, seasonal and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near–offshore gradient, the analysis was performed for three spatial regions, i.e. nearshore region (< 10 km to the coastline), midshore region (10–30 km), and offshore region (> 30 km). We found that from year 2014 to 2017, phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m−3. Phytoplankton biomass dynamics follow a general seasonal cycle as in other temperate regional seas, with a distinct spring bloom (5.3–23.1 mg Chla m−3) and a modest autumn bloom (2.9–5.4 mg Chla m−3). This seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e. explained 38 %–65 % of the variation in the offshore region, 45 %–71 % in the midshore region, and 56 %–77 % in the nearshore region. In the near- and midshore regions, nutrients are most limiting the phytoplankton production in the month following the spring bloom (44 %–55 %). Nutrients are a determinant throughout the year in the offshore region (27 %–62 %). During winter, sea surface temperature is a determinant in all regions (15 %–17 %). The findings of this study contribute to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. The parameterized causal relationships allow estimating how the base of the southern North Sea food web will change under future climate change and/or blue economy activities that affect one or more determinants of the phytoplankton biomass dynamics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Viviana Otero, Steven Pint, Klaas Deneudt, Maarten De Rijcke, Jonas Mortelmans, Lennert Schepers, Patricia Cabrera, Koen Sabbe, Wim Vyverman, Michiel Vandegehuchte, and Gert Everaert

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-11', Anonymous Referee #1, 19 Apr 2022
    • AC1: 'Reply on RC1 and RC2', Steven Pint, 08 Jul 2022
      • EC1: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022
      • EC3: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022
  • RC2: 'Comment on bg-2022-11', Anonymous Referee #2, 21 May 2022
    • AC1: 'Reply on RC1 and RC2', Steven Pint, 08 Jul 2022
      • EC2: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-11', Anonymous Referee #1, 19 Apr 2022
    • AC1: 'Reply on RC1 and RC2', Steven Pint, 08 Jul 2022
      • EC1: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022
      • EC3: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022
  • RC2: 'Comment on bg-2022-11', Anonymous Referee #2, 21 May 2022
    • AC1: 'Reply on RC1 and RC2', Steven Pint, 08 Jul 2022
      • EC2: 'Reply on AC1', Gert Van Hoey, 18 Aug 2022
Viviana Otero, Steven Pint, Klaas Deneudt, Maarten De Rijcke, Jonas Mortelmans, Lennert Schepers, Patricia Cabrera, Koen Sabbe, Wim Vyverman, Michiel Vandegehuchte, and Gert Everaert
Viviana Otero, Steven Pint, Klaas Deneudt, Maarten De Rijcke, Jonas Mortelmans, Lennert Schepers, Patricia Cabrera, Koen Sabbe, Wim Vyverman, Michiel Vandegehuchte, and Gert Everaert

Viewed

Total article views: 1,264 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
955 266 43 1,264 29 37
  • HTML: 955
  • PDF: 266
  • XML: 43
  • Total: 1,264
  • BibTeX: 29
  • EndNote: 37
Views and downloads (calculated since 17 Jan 2022)
Cumulative views and downloads (calculated since 17 Jan 2022)

Viewed (geographical distribution)

Total article views: 1,230 (including HTML, PDF, and XML) Thereof 1,230 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 11 Jun 2024
Download
Short summary
A mechanistic ecological model analysed which factors drive marine phytoplankton biomass dynamics in the southern part of the North Sea and how their relationship to primary production varies on a spatiotemporal scale. We found a spatiotemporal dependence, meaning that the effects of changing abiotic conditions on phytoplankton biomass dynamics are difficult to generalise. The tailor-made ecological model will enables to predict phytoplankton biomass dynamics under future climate scenarios.
Altmetrics