Photosynthetic rates derived from satellite‐based chlorophyll concentration

TLDR

We assembled a dataset of 14 C‑based productivity measurements to identify the key variables needed for accurate assessment of daily depth‑integrated phytoplankton carbon fixation from sea surface pigment concentrations. From this dataset, we developed a light‑dependent, depth‑resolved model (VGPM) that separates environmental factors influencing the vertical distribution of primary production from those controlling the optimal assimilation efficiency of the productivity profile. We created a temperature‑dependent PBopt model and combined it with monthly climatological images of chlorophyll‑satellite concentration, sea surface temperature, and cloud‑corrected surface irradiance to compute a global annual phytoplankton carbon fixation rate of 43.5 Pg C yr⁻¹. The VGPM explained 79 % of the variability in the vertical distribution of primary production and 86 % of the variability in total production, demonstrating that accurate PP estimates hinge on capturing PBopt variability; the resulting global annual PP distribution differed markedly from previous models, highlighting the need to focus PBopt development on temporal and spatial variability.

Abstract

We assembled a dataset of 14 C‐based productivity measurements to understand the critical variables required for accurate assessment of daily depth‐integrated phytoplankton carbon fixation ( PP ( PP eu ) u ) from measurements of sea surface pigment concentrations ( C sat )( C sat ). From this dataset, we developed a light‐dependent, depth‐resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production ( P z ) z ) and those that control the optimal assimilation efficiency of the productivity profile ( P ( P B opt ). The VGPM accounted for 79% of the observed variability in P z and 86% of the variability in PP eu by using measured values of P B opt . Our results indicate that the accuracy of productivity algorithms in estimating PP eu is dependent primarily upon the ability to accurately represent variability in P b opt . We developed a temperature‐dependent P b opt model that was used in conjunction with monthly climatological images of C sat sea surface temperature, and cloud‐corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation ( PP annu ) rate of 43.5 Pg C yr ‒1 . The geographical distribution of PP annu was distinctly different than results from previous models. Our results illustrate the importance of focusing P b opt model development on temporal and spatial, rather than the vertical, variability.