Growth physiology and fate of diatoms in the ocean: a review

Selection of microalgae for lipid production under high levels carbon dioxide.

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition.

/pdf/spatial-patterns-and-links-between-microbial-community-1meipsc4uv.pdf

Spatial patterns and links between microbial community composition and function in cyanobacterial mats

Microalgae-based biofuel has received increasing attention as one of the alternative energy sources because of its many advantages. Cultivation of microalgae is a crucial step for successful applications in the biofuel industry. Growth kinetic models are needed to provide an understanding of microalgal growth so that cultivation conditions can be optimized. This review study aims to provide an overview of the existing growth kinetic models for microalgae cultivation and identify knowledge gaps. The existing models were compiled and organized into three groups: those considering a single substrate factor, a light factor, or multiple factors including both substrate and environment. Three major knowledge gaps were identified in this review. For models considering multiple factors, the trade-off between the complexity of the model structure and the usability of the model must be managed. There is a need for appropriate incorporation of light and temperature in the growth model. This can be accomplished through developing an appropriate expression for temporally varying culture temperature and improving light expressions by considering the light attenuation and variation in sunlight intensity. Lastly, developing a generalized growth model for incorporation of species diversity is necessary for more realistic modeling of actual systems.

Growth kinetic models for microalgae cultivation: A review

. Past model studies have projected a global decrease in marine net primary production (NPP) over the 21st century, but these studies focused on the multi-model mean rather than on the large inter-model differences. Here, we analyze model-simulated changes in NPP for the 21st century under IPCC's high-emission scenario RCP8.5. We use a suite of nine coupled carbon–climate Earth system models with embedded marine ecosystem models and focus on the spread between the different models and the underlying reasons. Globally, NPP decreases in five out of the nine models over the course of the 21st century, while three show no significant trend and one even simulates an increase. The largest model spread occurs in the low latitudes (between 30° S and 30° N), with individual models simulating relative changes between −25 and +40 %. Of the seven models diagnosing a net decrease in NPP in the low latitudes, only three simulate this to be a consequence of the classical interpretation, i.e., a stronger nutrient limitation due to increased stratification leading to reduced phytoplankton growth. In the other four, warming-induced increases in phytoplankton growth outbalance the stronger nutrient limitation. However, temperature-driven increases in grazing and other loss processes cause a net decrease in phytoplankton biomass and reduce NPP despite higher growth rates. One model projects a strong increase in NPP in the low latitudes, caused by an intensification of the microbial loop, while NPP in the remaining model changes by less than 0.5 %. While models consistently project increases NPP in the Southern Ocean, the regional inter-model range is also very substantial. In most models, this increase in NPP is driven by temperature, but it is also modulated by changes in light, macronutrients and iron as well as grazing. Overall, current projections of future changes in global marine NPP are subject to large uncertainties and necessitate a dedicated and sustained effort to improve the models and the concepts and data that guide their development.

/pdf/drivers-and-uncertainties-of-future-global-marine-primary-oonrtngfd1.pdf

Drivers and uncertainties of future global marine primary production in marine ecosystem models

The CO2 exchange response of plants to multiple environmental variables is often difficult to frame for purposes of comparison. In this paper, a nonlinear model relating CO2 exchange to light and temperature is derived from experimental curves determined in other investigations. Parameter values, determined from a least-squares fit of the model to CO2 exchange data, are useful for comparing responses to light and temperature in terms of seasonal phenology, population heterogeneity, or species variation. The model was fitted to CO2 exchange data of a group of 40 Alnus rubra Bong. (red alder) seedlings for steady-state combinations of light and temperature. The average deviation of the data from the model was ±6.7%. This steady-state expression satisfactorily predicted CO2 exchange for dynamic conditions of light and temperature occurring in a diurnal cycle.

Carbon dioxide exchange of Alnus rubra

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Carbon dioxide exchange of Alnus rubra