How to learn more about hydrological conditions and phytoplankton dynamics and diversity in the eastern English Channel and the Southern Bight of the North Sea: the Suivi Régional des Nutriments data set (1992–2021)

Abstract

This article describes a 30-year data series produced by the SRN (“Suivi Régional des Nutriments” in French; Regional Nutrients Monitoring Programme) network managed by Ifremer. Since 1992, the SRN network has been analysing phytoplankton species and measuring physicochemical (temperature, salinity, oxygen, suspended matter, nutrients) and biological (chlorophyll a, phytoplankton abundance) parameters at 10 different stations distributed along three different transects located in the eastern English Channel and the Southern Bight of the North Sea. This geographic coverage allows for the study of three distinct ecosystems, i.e. three transects (estuary, coastal region under freshwater influence, and coastal region), as well as the investigation of coastal to offshore water gradients. The SRN collects a maximum of 184 samples per year (3687 samples spread over 10 stations during the studied period) and detects up to 291 taxa, including harmful algal bloom species (HABs), with a bi-weekly to monthly sampling frequency (depending on the location and the season). The objectives of this monitoring programme are to assess the influence of continental inputs on the marine environment and their implications for possible eutrophication processes. It also aims to estimate the effectiveness of development and management policies in the marine coastal zone by providing information on trends and/or shifts in pressure, state, and impact variables. The regular acquisition of data allows the establishment of long-term monitoring of the evolution of coastal water quality as well as the observation of the consequences of large-scale alterations mainly driven by climate change and modifications that are more related to local/regional anthropogenic activities. This paper provides an overview of the main characteristics of SRN data (descriptive statistics and data series main patterns) as well as an analysis of temporal trends and shifts. We also propose to the data user a specific numerical tool available as an R package to optimize the data pre-processing and processing steps. Users will then have easy access to statistics, trends, and anomalies as proposed in this paper. The main results of several research projects based on SRN data and dealing with hydrology, phytoplankton blooms, HABs, phenology, and niches are also highlighted, providing the readers with examples of what can be done with such a data set. We hope that this synthesis will also save data users time by allowing them to jump right into a deeper analysis based on previous conclusions and perspectives or to investigate new scientific key challenges. These data should also be used at a wider geographical scale, combined with other data sources, to define more global patterns of environmental changes in a moving world subject to strong anthropogenic pressures. Data can also be used by the remote sensing (ocean colour observation) and modelling communities to calibrate or validate products in this complex and vital coastal region. The SRN data set is publicly available: https://doi.org/10.17882/50832 (SRN – Regional Observation and Monitoring program for Phytoplankton and Hydrology in the eastern English Channel, 2022).