Abstract

Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Global warming is thought to affect phytoplankton production both directly, by impacting their photosynthetic metabolism, and indirectly by modifying the physical environment in which they grow. In this respect, the Bermuda Atlantic Time-series Study (BATS) in the Sargasso Sea (North Atlantic gyre) provides a unique opportunity to explore effects of warming on phytoplankton production across the vast oligotrophic ocean regions because it is one of the few multidecadal records of measured net primary productivity (NPP). We analysed the time series of phytoplankton primary productivity at BATS site using machine learning techniques (ML) to show that increased water temperature over a 27-year period (1990–2016), and the consequent weakening of vertical mixing in the upper ocean, induced a negative feedback on phytoplankton productivity by reducing the availability of essential resources, nitrogen and light. The unbalanced availability of these resources with warming, coupled with ecological changes at the community level, is expected to intensify the oligotrophic state of open-ocean regions that are far from land-based nutrient sources.

Highlights

  • Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs

  • Interest in the impact of global warming on phytoplankton has grown during the last decade[5], with observations of synchronous increases of surface ocean temperature and an apparent global decrease of phytoplankton biomass, primarily inferred from changes in chlorophyll a (Chl a) concentration[6,7]

  • The day of the year (Y-day) – i.e. an independent variable representing seasons in the mathematical equation from Genetic Programming (GP) – showed no effect on net primary productivity (NPP). This result could stem from the fact that the codification of the Y-day from 1 to 365 is not adequate, because it could fail to convey the cyclical character of the seasonal changes, unless it is transformed using periodic functions (e.g. Gregor et al.[38]). We addressed this point by running GP with transformed Y-day data, but this operation yielded lower predictive power: in this way Y-day had a forced proportionality with temperature, resulting in a weak correlation between measured and predicted NPP (MAE > 300%)

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Summary

Introduction

Phytoplankton play key roles in the oceans by regulating global biogeochemical cycles and production in marine food webs. Changes in phytoplankton biomass over time do not necessarily parallel changes in the rate of primary production, i.e. the primary productivity, which reflects the level of photosynthetic activity of planktonic microalgae and is strongly linked to the availability of primary resources, such as nutrients and light energy. From this conceptual basis, global warming is thought to reduce vertical mixing in the oceans and its transport of nutrients from deep waters to the photic zone. Further validations are possible with long-term data representative of changes over the photic-zone depth that extends well below the surface in oligotrophic oceans[16]

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