Quantum Yields in Aquatic Photosynthesis

Photo-oxygenation for nitritation and the effect of dissolved oxygen concentrations on anaerobic ammonium oxidation

“…The average incidence light intensity applied at reactor surface in this research was 500 μmol photons/m 2 ·s, but as the reflection from the water surface was not measured, it is difficult to estimate the maximum achievable oxygen production based on theoretical quantum yields. Nevertheless, assuming the theoretical estimated quantum yield for algae growing on ammonium (instead of nitrate) at low light intensities as 0.125 mol O 2 /mol photons (Iluz and Dubinsky, 2013), then maximum oxygen generation would be 6.25 * 10 −5 mol O 2 /m 2 ·s or 7.20 gO 2 /m 2 ·h. This oxygen would be used for heterotrophic oxidation of organics, algae respiration, ammonium oxidation and nitrite oxidation, and the amounts can be calculated as follows.…”

Regionalization and Dynamic Parameterization of Quantum Yield of Photosynthesis to Improve the Ocean Primary Production Estimates From Remote Sensing

“…The highest variability for different depths and different regions was reported in Ostrowska et al (2012). In the upper water column, φ is ruled mainly by light levels, presenting low values at surface because of photoinhibition and higher proportion of photoprotective pigments, while higher values are found at greater depths with lower light levels, where φ may reach its theoretical maximum (Iluz and Dubinsky, 2013). Marra et al (2000) quantified the effect of photoprotective pigments in φ.…”

“…Inside the cell, photosynthesis takes place in the chloroplasts, and two photosystems are involved in this process. The light reactions in both photosystems place physiological limits on photosynthesis efficiency that confers φ to a maximum theoretical value of 0.125 mol C mol photons −1 (Iluz and Dubinsky, 2013). Actually, in nature, phytoplankton species are observed to work under much lower efficiency than this expected maximum (Morel, 1978;Marra et al, 1993;Carder et al, 1995;Sorensen and Siegel, 2001; among many others).…”

“…Therefore, PP sat−aphy−based already takes into account the vertical variation of φ caused by differences in PAR at depth when using Equation 3. However, so far no application of the PP sat−aphy−based model considers regional and seasonal variability in φ caused by factors other than light, where as indicated in Iluz and Dubinsky (2013) temporal and regional varying φ instead of a universal factor should be employed. To test and evaluate this strategy, we derive φ values in two long, in situ time-series, collected at fixed stations within the two North Subtropical Gyres.…”

Geoinformation modeling of potential productivity in agricultural landscapes for the formation of sustainable land use

“…In addition, the information, obtained in the process of biopotential modeling of agricultural landscapes in grain industry of the Simferopol region, is currently not fully used in land management and can presumably serve as basis for effective land management. Modern research in the field of food security and preservation of natural environment is aimed at taking into account the efficiency of growing crops in combined sowings in various climatic conditions [1][2]. Therefore, specialists in the fields of land management, landscape science, biology and agriculture pay more attention to issues of geoinformation modeling in agricultural landscapes.…”