Decadal patterns and trends in benthic-pelagic exchange processes

Abstract

In marine environments, the exchange of particles and solutes between the seafloor and overlying water column, known as benthic-pelagic (B/P) coupling is an important component in many biological and biogeochemical cycles. Key processes and drivers involved in this exchange display strongly seasonal variability, especially in temperate coastal environments. The magnitude and timings of these seasonal patterns however are not identical year-on-year, and the influence of this inter-annual variability on the rate and direction of B/P exchange, as well as the influence of longer term, multi-year trends, are less well understood. In this current study, multi-year temporal patterns of benthic-pelagic solute and particle exchange were investigated on the examples of particulate organic carbon and dissolved inorganic nitrogen time series data, to assess connections between inter- and multi-annual processes and characterize their nature and what drives them. To this end, a decadal (2009–2018) time-series dataset that combines biological, physical, meteorological and chemical measurements from the Western Channel Observatory, Plymouth, UK was analysed in combination with supplementary data from several environmental monitoring agencies. Time-series decomposition using seasonal decomposition with locally estimated scatterplot smoothing revealed that the main causes of inter-annual variability were extreme outlier events, some of which were influential enough to cause multi-annual trends. Stochastic meteorological and biological extremes, such as exceptional storms and phytoplankton blooms explained a large proportion of outlier events in the time series. Global-scale climatic fluctuations, such as North Atlantic Oscillation (NAO) and Southern Oscillation Index were reflected in benthic-pelagic exchange trends when they co-occurred in an additive manner (e.g. positive NAO and El Niño). The importance of multi-parameter long-term observatories, such as the Western Channel Observatory, is highlighted, and the use of transdisciplinary time-series datasets to identify individual events which have large ecosystem-level impacts is demonstrated. In order to identify and monitor long-term effects, such as climate trends or decadal global ocean cycles, multi-decadal sustained observations are of vital importance.