Fast Repetition Rate Fluorometry (FRRF) Derived Phytoplankton Primary Productivity in the Bay of Bengal

Abstract

The approach of fast repetition rate fluorometry (FRRF) requires a conversion factor (Φ_{e : C}/n _PSII) to derive ecologically-relevant carbon uptake rates (PP _z,t). However, the required Φ_{e : C}/n _PSII is commonly measured by ¹⁴C assimilation and varies greatly across phytoplankton taxonomy and environmental conditions. Consequently, the use of FRRF to estimate gross primary productivity (GP _z,t), alone or in combination with other approaches, has been restricted by both inherent conversion and procedural inconsistencies. Within this study, based on a hypothesis that the non-photochemical quenching (NPQ_NSV) can be used as a proxy for the variability and magnitude of Φ_{e : C}/n _PSII, we thus proposed an independent field model coupling with the NPQ_NSV-based Φ_{e : C}/n _PSII for FRRF-derived carbon, without the need for additional Φ_{e : C}/n _PSII in the Bay of Bengal (BOB). Therewith, this robust algorithm was verified by the parallel measures of electron transport rates and ¹⁴C-uptake PP _z,t. NPQ_NSV is theoretically caused by the effects of excess irradiance pressure, however, it showed a light and depth-independent response on large spatial scales of the BOB. Trends observed for the maximum quantum efficiency (F_v/F_m), the quantum efficiency of energy conversion ( ${\text{F}}_{\text{q}}^{\text{'}}$ / ${\text{F}}_{\text{m}}^{\text{'}}$ ) and the efficiency of charge separation ( ${\text{F}}_{\text{q}}^{\text{'}}$ / ${\text{F}}_{\text{v}}^{\text{'}}$ ) were similar and representative, which displayed a relative maximum at the subsurface and were collectively limited by excess irradiance. In particular, most observed values of F_v/F_m in the BOB were only about half of the values expected for nutrient replete phytoplankton. FRRF-based estimates of electron transport at PSII (ETR_RCII) varied significantly, from 0.01 to 8.01 mol e^- mol RCII^-1 s^-1, and showed profound responses to depth and irradiance across the BOB, but fitting with the logistic model. N, P, and irradiance are key environmental drivers in explaining the broad-scale variability of photosynthetic parameters. Furthermore, taxonomic shifts and physiological changes may be better predictors of photosynthetic parameters, and facilitate the selection of better adapted species to optimize photosynthetic efficiency under any particular set of ambient light condition.

Keywords: Bay of Bengal; electron transport; photosynthetic parameters; phytoplankton; primary production.

Figure 1

Study area and sampling locations.

Figure 2

Spectral quality of the actinic flash and excitation power used for FRRF3 sensor.

Figure 3

The correlation between in situ NPQ and NPQ_NSV, as well as the responses of in situ NPQ to light and depth. (A) In situ NPQ derived from FRRF measurements plotted against NPQ_NSV calculated by fluorescence parameters of the same water (Spearman's rank correlation coefficient S = 0.95, n = 72). (B) Responses of NPQ to changes in light and depth over the course of the in situ experiment (S_PAR = 0.18, S_depth = 0.03). NPQ was derived from the in situ FRRF measurements and is unitless. The dashed line indicates the average value of NPQ.

Figure 4

Depth and light dependency of ChlF-derived F_v/F_m, ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{m}}^{\prime }$ and ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{v}}^{\prime }$ from FRRF measurements. (A) F_v/F_m, ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{m}}^{\prime }$ and ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{v}}^{\prime }$ vs. depth; (B) F_v/F_m, ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{m}}^{\prime }$ and ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{v}}^{\prime }$ vs. light. The red, olive and blue dashed lines represent the averaging of F_v/F_m, ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{m}}^{\prime }$ and ${\text{F}}_{\text{q}}^{\prime }$/${\text{F}}_{\text{v}}^{\prime }$, respectively.

Figure 5

Depth and light responses of rates of ETR_RCII and F_C. (A) ETR_RCII vs. depth (R² = 0.68) and PAR (R² = 0.87); (B) F_C vs. depth (R² = 0.96) and PAR (R² = 0.83). The black dashed lines, respectively, indicate their average values. The green dashed lines, respectively, represent the theoretical exponential model of Webb et al. (1974) for the P vs. E curves.

Figure 6

Spatial distributions of (a) phytoplankton abundance (×10⁴ cells m⁻³), (b) FRRF-GP_Zeu, and (c) ¹⁴C-PP_Zeu [mg C (mg chla)⁻¹ h⁻¹ m⁻²] within the upper Z_eu depth.

Figure 7

Scatter plots of FRRF-GP_Zeu and ¹⁴C-PP_Zeu [mg C (mg chla)⁻¹ h⁻¹ m⁻²] for pooled data of 16 stations in the BOB.

Figure 8

Vertical profiles for average values of phytoplankton abundance and PAR in the BOB.

Figure 9

A comparison among the water column integrated primary production from different FRRF approaches and synchronized ¹⁴C dataset.