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Ecol Evol ; 12(7): e9079, 2022 Jul.
Article in English | MEDLINE | ID: mdl-35845373

ABSTRACT

Although many studies have focused on the effects of elevated atmospheric CO2 on algal growth, few of them have demonstrated how CO2 interacts with carbon absorption capacity to determine the algal competition at the population level. We conducted a pairwise competition experiment of Phormidium sp., Scenedesmus quadricauda, Chlorella vulgaris and Synedra ulna. The results showed that when the CO2 concentration increased from 400 to 760 ppm, the competitiveness of S. quadricauda increased, the competitiveness of Phormidium sp. and C. vulgaris decreased, and the competitiveness of S. ulna was always the lowest. We constructed a model to explore whether interspecific differences in affinity and flux rate for CO2 and HCO3 - could explain changes in competitiveness between algae species along the gradient of atmospheric CO2 concentration. Affinity and flux rates are the capture capacity and transport capacity of substrate respectively, and are inversely proportional to each other. The simulation results showed that, when the atmospheric CO2 concentration was low, species with high affinity for both CO2 and HCO3 - (HCHH) had the highest competitiveness, followed by the species with high affinity for CO2 and low affinity for HCO3 - (HCLH), the species with low affinity for CO2 and high affinity for HCO3 - (LCHH) and the species with low affinity for both CO2 and HCO3 - (LCLH); when the CO2 concentration was high, the species were ranked according to the competitive ability: LCHH > LCLH > HCHH > HCLH. Thus, low resource concentration is beneficial to the growth and reproduction of algae with high affinity. With the increase in atmospheric CO2 concentration, the competitive advantage changed from HCHH species to LCHH species. These results indicate the important species types contributing to water bloom under the background of increasing global atmospheric CO2, highlighting the importance of carbon absorption characteristics in understanding, predicting and regulating population dynamics and community composition of algae.

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