TY - JOUR

T1 - Wind speed and mesoscale features drive net autotrophy in the South Atlantic Ocean

AU - Ford, Daniel

AU - Tilstone, Gavin H.

AU - Shutler, Jamie D.

AU - Kitidis, Vassilis

AU - Lobanova, Polina

AU - Schwarz, Jill

AU - Poulton, Alex J.

AU - Serret, Pablo

AU - Lamont, Tarron

AU - Chuqui, Mateus

AU - Barlow, Ray

AU - Lozano, Jose

AU - Kampel, Milton

AU - Brandini, Frederico

N1 - Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/7/1

Y1 - 2021/7/1

N2 - A comprehensive in situ dataset of chlorophyll a (Chl a; N = 18,001), net primary production (NPP; N = 165) and net community production (NCP; N = 95), were used to evaluate the performance of Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-A) algorithms for these parameters, in the South Atlantic Ocean, to facilitate the accurate generation of satellite NCP time series. For Chl a, five algorithms were tested using MODIS-A data, and OC3-CI performed best, which was subsequently used to compute NPP. Of three NPP algorithms tested, a Wavelength Resolved Model (WRM) was the most accurate, and was therefore used to estimate NCP with an empirical relationship between NCP with NPP and sea surface temperature (SST). A perturbation analysis was deployed to quantify the range of uncertainties introduced in satellite NCP from input parameters. The largest reductions in the uncertainty of satellite NCP came from MODIS-A derived NPP using the WRM (40%) and MODIS-A Chl a using OC3-CI (22%). The most accurate NCP algorithm, was used to generate a 16 year time series (2002 to 2018) from MODIS-A to assess climate and environmental drivers of NCP across the South Atlantic basin. Positive correlations between wind speed anomalies and NCP anomalies were observed in the central South Atlantic Gyre (SATL), and the Benguela Upwelling (BENG), indicating that autotrophic conditions may be fuelled by local wind-induced nutrient inputs to the mixed layer. Sea Level Height Anomalies (SLHA), used as an indicator of mesoscale eddies, were negatively correlated with NCP anomalies offshore of the BENG upwelling fronts into the SATL, suggesting autotrophic conditions are driven by mesoscale features. The Agulhas bank and Brazil-Malvinas confluence regions also had a strong negative correlation between SLHA and NCP anomalies, similarly indicating that NCP is forced by mesoscale eddy generation in this region. Positive correlations between SST anomalies and the Multivariate ENSO Index (MEI) in the SATL, indicated the influence of El Niño events on the South Atlantic Ocean, however the plankton community response was less clear.

AB - A comprehensive in situ dataset of chlorophyll a (Chl a; N = 18,001), net primary production (NPP; N = 165) and net community production (NCP; N = 95), were used to evaluate the performance of Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-A) algorithms for these parameters, in the South Atlantic Ocean, to facilitate the accurate generation of satellite NCP time series. For Chl a, five algorithms were tested using MODIS-A data, and OC3-CI performed best, which was subsequently used to compute NPP. Of three NPP algorithms tested, a Wavelength Resolved Model (WRM) was the most accurate, and was therefore used to estimate NCP with an empirical relationship between NCP with NPP and sea surface temperature (SST). A perturbation analysis was deployed to quantify the range of uncertainties introduced in satellite NCP from input parameters. The largest reductions in the uncertainty of satellite NCP came from MODIS-A derived NPP using the WRM (40%) and MODIS-A Chl a using OC3-CI (22%). The most accurate NCP algorithm, was used to generate a 16 year time series (2002 to 2018) from MODIS-A to assess climate and environmental drivers of NCP across the South Atlantic basin. Positive correlations between wind speed anomalies and NCP anomalies were observed in the central South Atlantic Gyre (SATL), and the Benguela Upwelling (BENG), indicating that autotrophic conditions may be fuelled by local wind-induced nutrient inputs to the mixed layer. Sea Level Height Anomalies (SLHA), used as an indicator of mesoscale eddies, were negatively correlated with NCP anomalies offshore of the BENG upwelling fronts into the SATL, suggesting autotrophic conditions are driven by mesoscale features. The Agulhas bank and Brazil-Malvinas confluence regions also had a strong negative correlation between SLHA and NCP anomalies, similarly indicating that NCP is forced by mesoscale eddy generation in this region. Positive correlations between SST anomalies and the Multivariate ENSO Index (MEI) in the SATL, indicated the influence of El Niño events on the South Atlantic Ocean, however the plankton community response was less clear.

KW - Environmental drivers

KW - in situ uncertainty

KW - MODIS-A

KW - Ocean colour

KW - Ocean metabolism

KW - South Atlantic Ocean

KW - CHLOROPHYLL-A

KW - COLOR MODEL

KW - COASTAL

KW - CONTINENTAL-SHELF

KW - SEAWIFS DATA

KW - IN-SITU DATA

KW - SIZE STRUCTURE

KW - PRIMARY PRODUCTIVITY

KW - MARINE-PHYTOPLANKTON

KW - COMMUNITY PRODUCTION

UR - http://www.scopus.com/inward/record.url?scp=85105696020&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/beb5aa1f-9234-33da-969d-9534c2800c5e/

U2 - 10.1016/j.rse.2021.112435

DO - 10.1016/j.rse.2021.112435

M3 - Article

AN - SCOPUS:85105696020

VL - 260

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

M1 - 112435

ER -