Quantifying photosynthetic performance of phytoplankton based on photosynthesis–irradiance response models

• Published in: Environmental sciences Europe Vol. 32; no. 1
• Main Authors: Yang, Xiaolong, Liu, Lihua, Yin, Zhikai, Wang, Xingyu, Wang, Shoubing, Ye, Zipiao
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2020; Springer Nature B.V
• Subjects: Algae; Aquatic ecosystems; Aquatic plants; Asymptotic methods; China; Curve fitting; Dunaliella salina; Earth and Environmental Science; Economic models; Ecotoxicology; Environment; Environmental changes; Irradiance; Microcystis; Photosynthesis; Phytoplankton; Plankton; Pollution; Progress in Environmental Sciences and Technology in the Yangtze River Basin; Phytoplankton; Irradiance; Photosynthesis–irradiance response model; Photosynthetic performance
• ISSN: 2190-4707; 2190-4715
• DOI: 10.1186/s12302-020-00306-9

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.