Trichodesmium is a globally important marine diazotroph that accounts for approximately 60 − 80% of marine biological N2 fixation and as such plays a key role in marine N and C cycles. We undertook a comprehensive assessment of how the growth rate of Trichodesmium erythraeum IMS101 was directly affected by the combined interactions of temperature, pCO2 and light intensity. Our key findings were: low pCO2 affected the lower temperature tolerance limit (Tmin) but had no effect on the optimum temperature (Topt) at which growth was maximal or the maximum temperature tolerance limit (Tmax); low pCO2 had a greater effect on the thermal niche width than low-light; the effect of pCO2 on growth rate was more pronounced at suboptimal temperatures than at supraoptimal temperatures; temperature and light had a stronger effect on the photosynthetic efficiency (Fv/Fm) than did CO2; and at Topt, the maximum growth rate increased with increasing CO2, but the initial slope of the growth-irradiance curve was not affected by CO2. In the context of environmental change, our results suggest that the (i) nutrient replete growth rate of Trichodesmium IMS101 would have been severely limited by low pCO2 at the last glacial maximum (LGM), (ii) future increases in pCO2 will increase growth rates in areas where temperature ranges between Tmin to Topt, but will have negligible effect at temperatures between Topt and Tmax, (iii) areal increase of warm surface waters (> 18°C) has allowed the geographic range to increase significantly from the LGM to present and that the range will continue to expand to higher latitudes with continued warming, but (iv) continued global warming may exclude Trichodesmium spp. from some tropical regions by 2100 where temperature exceeds Topt.

is the ultimate source of reducing power for phytoplankton primary productivity (PhytoPP). Single turnover active chlorophyll fluorometry (STAF) provides a non-intrusive method that has the potential to measure PhytoPP on much wider spatiotemporal scales than is possible with more direct methods such as 14 C fixation or O 2 evolved through water oxidation. Application of a STAF-derived absorption coefficient for PSII light-harvesting (a LHII) provides a method for estimating PSII photochemical flux on a unit volume basis (JV PII). Within this study, we assess potential errors in the calculation of JV PII arising from sources other than photochemically active PSII complexes (baseline fluorescence) and the package effect. Although our data show that such errors can be significant, we identify fluorescencebased correction procedures that can be used to minimize their impact. For baseline fluorescence, the correction incorporates an assumed consensus PSII photochemical efficiency for dark-adapted material. The error generated by the package effect can be minimized through the ratio of variable fluorescence measured within narrow wavebands centered at 730 nm, where the re-absorption of PSII fluorescence emission is minimal, and at 680 nm, where re-absorption of PSII fluorescence emission is maximal. We conclude that, with incorporation of these corrective steps, STAF can provide a reliable estimate of JV PII and, if used in conjunction with simultaneous satellite measurements of ocean color, could take us significantly closer to achieving the objective of obtaining reliable autonomous estimates of PhytoPP.

We have assessed how varying CO2 (180, 380, and 720 μatm) and growth light intensity (40 and 400 μmol photons m−2 s−1) affected Trichodesmium erythraeum IMS101 growth and photophysiology over free iron (Fe′) concentrations between 20 and 9,600 pM. We found significant iron dependencies of growth rate and the initial slope and maximal relative PSII electron transport rates (rPm). Under iron-limiting concentrations, high-light increased growth rates and rPm; possibly indicating a lower allocation of resources to iron-containing photosynthetic proteins. Higher CO2 increased growth rates across all iron concentrations, enabled growth to occur at lower Fe′ concentrations, increased rPm and lowered the iron half saturation constants for growth (Km). We attribute these CO2 responses to the operation of the CCM and the ATP spent/saved for CO2 uptake and transport at low and high CO2, respectively. It seems reasonable to conclude that T. erythraeum IMS101 can exhibit a high degree of phenotypic plasticity in response to CO2, light intensity and iron-limitation. These results are important given predictions of increased dissolved CO2 and water column stratification (i.e., higher light exposures) over the coming decades.

Photosynthetic rates in the cyanobacterium Trichodesmium erythraeum appear to be a function of CO2, although numerical simulations of the carbon-concentrating mechanism show carboxylation to be mediated as a function of pH and HCO3–.

The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra‐ and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms. We found that many of the surveyed equations have comparable abilities to fit data and equally high requirements for data quality (number of test temperatures and range of response captured) but lead to different estimates of cardinal temperatures and of the biological rates at these temperatures. When these rate estimates are used for biogeographic predictions, differences between the estimates of even the best‐fitting models can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models.