Summary: A new mechanistic model of the photosynthesis–light response is developed based on photosynthetic electron transport via photosystem II (PSII) to specifically describe light‐harvesting characteristics and associated biophysical parameters of photosynthetic pigment molecules. This model parameterizes ‘core’ characteristics not only of the light response but also of difficult to measure physical parameters of photosynthetic pigment molecules in plants. Application of the model to two C₃ and two C₄ species grown under the same conditions demonstrated that the model reproduced extremely well (r² > 0.992) the light response trends of both electron transport and CO₂ uptake. In all cases, the effective absorption cross‐section of photosynthetic pigment molecules decreased with increasing light intensity, demonstrating novel operation of a key mechanism for plants to avoid high light damage. In parameterizing these previously difficult to measure characteristics of light harvesting in higher plants, the model provides a new means to understand the mechanistic processes underpinning variability of CO₂ uptake, for example, photosynthetic down‐regulation or reversible photoinhibition induced by high light and photoprotection. However, an important next step is validating this parameterization, possibly through application to less structurally complex organisms such as single‐celled algae.

The first results obtained by the DAMA/LIBRA–phase2 experiment are presented. The data have been collected over six independent annual cycles corresponding to a total exposure of 1.13 ton × year, deep underground at the Gran Sasso National Laboratory. The DAMA/LIBRA–phase2 apparatus, about 250 kg highly radio-pure NaI(Tl), profits from a second generation high quantum efficiency photomultipliers and of new electronics with respect to DAMA/LIBRA–phase1. The improved experimental configuration has also allowed to lower the software energy threshold. The DAMA/LIBRA–phase2 data confirm the evidence of a signal that meets all the requirements of the model independent Dark Matter annual modulation signature, at 9.5 $\sigma$ C.L. in the energy region (1–6) keV. In the energy region between 2 and 6 keV, where data are also available from DAMA/NaI and DAMA/LIBRA–phase1, the achieved C.L. for the full exposure (2.46 ton × year) is 12.9 $\sigma$ .

Background: Clarifying the relationship between photosynthesis and irradiance and accurately quantifying photosynthetic performance are of importance to calculate the productivity of phytoplankton, whether in aquatic ecosystems modelling or obtaining more economical production. Results: The photosynthetic performance of seven phytoplankton species was characterized by four typical photosynthesis–irradiance (P–I) response models. However, the differences were found between the returned values to photosynthetic characteristics by different P–I models. The saturation irradiance (I_sat) was distinctly underestimated by model 1, and the maximum net photosynthetic rate (P_nmax) was quite distinct from its measured values, due to the asymptotic function of the model. Models 2 and 3 lost some foundation to photosynthetic mechanisms, that the returned I_sat showed significant differences with the measured data. Model 4 for higher plants could reproduce the irradiance response trends of photosynthesis well for all phytoplankton species and obtained close values to the measured data, but the fitting curves exhibited some slight deviations under the low intensity of irradiance. Different phytoplankton species showed differences in photosynthetic productivity and characteristics. Platymonas subcordiformis showed larger intrinsic quantum yield (α) and lower I_sat and light compensation point (I_c) than Dunaliella salina or Isochrysis galbana. Microcystis sp., especially M. aeruginosa with the largest P_nmax and α among freshwater phytoplankton strains, exhibited more efficient light use efficiency than two species of green algae. Conclusions: The present work will be useful both to describe the behavior of different phytoplankton in a quantitative way as well as to evaluate the flexibility and reusability of P–I models. Meanwhile we believe this research could provide important insight into the structure changes of phytoplankton communities in the aquatic ecosystems.