Phytoplankton Photophysiology Utilities: A Python Toolbox for the Standardization of Processing Active Chlorophyll-a Fluorescence Data

Abstract

The uptake and application of single turnover chlorophyll fluorometers to the study of phytoplankton ecosystem status and microbial functions has grown considerably in the last two decades. However, standardization of measurement protocols, processing of fluorescence transients and quality control of derived photosynthetic parameters is still lacking and makes community goals of large global databases of high-quality data unrealistic. We introduce the Python package Phytoplankton Photophysiology Utilities (PPU), an adaptable and open-source interface between Fast Repetition Rate and Fluorescence Induction and Relaxation instruments and python. The PPU package includes a variety of functions for the loading, processing and quality control of single turnover fluorescence transients from many commercially available instruments. PPU provides the user with greater flexibility in the application of the Kolber-Prasil-Falkowski model; tools for plotting, quality control, correcting instrument biases and high-throughput processing with ease; and a greater appreciation for the uncertainties in derived photosynthetic parameters. Using data from three research cruises across different biogeochemical regimes, we provide example applications of PPU to fit raw active chlorophyll-a fluorescence data from three commercial instruments and demonstrate tools which help to reduce uncertainties in the final fitted parameters.

Photosynthetic processes in Antarctic sea ice during the spring melt

“…Parameters of photophysiology, including maximum quantum yield of photochemistry in Photosystem II (PSII) ( F v / F m ) and functional absorption cross section of PSII ( σ PSII ), were calculated from the FIRe output after fitting the dark‐acclimated data using phytoplankton photophysiology utilities (Ryan‐Keogh and Robinson 2021) with blank and spectral corrections ( see below for methods). The first flashlet was excluded, and a fixed connectivity parameter ( ⍴ ) of 0.3 was used (Babin 2008).…”

Single-Turnover Variable Chlorophyll Fluorescence as a Tool for Assessing Phytoplankton Photosynthesis and Primary Productivity: Opportunities, Caveats and Recommendations

“…While the exact approach may be instrument specific, an explicit consideration of data quality and confidence is nonetheless critical to support globally coherent and intercomparable observations. Single-turnover variable chlorophyll fluorescence instruments are now capable of acquiring data even in very low biomass regions, but the low signal typical for oligotrophic waters often requires considerable data averaging from repeated rounds of ST-ChlF transients to achieve fits of reasonable quality (e.g., Ryan-Keogh and Robinson, 2021). A minimum level of fit quality for the derivation of primary ST-ChlF parameters should preferably be assessed during real-time data acquisition.…”

“…Once a robust database framework is established, endusers must be able to access and re-process raw data in a consistent and traceable way, choosing from a range of existing (and evolving) model fits. Toward this end, our group is developing a series of Python-based Jupyter notebooks allowing users with various levels of experience and expertise to reanalyze ST-ChlF data collected with any instrument (Ryan-Keogh and Robinson, 2021). The software will continue to evolve, as new analysis approaches are developed, allowing direct comparison among different approaches to calculate J PII or fit light-response curves.…”