Extending quota models to nitrogen-limited growth of phytoplankton populations

Malerba, Martino Edoardo (2015) Extending quota models to nitrogen-limited growth of phytoplankton populations. PhD thesis, James Cook University.

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View at Publisher Website: https://doi.org/10.25903/nwpn-v637


Almost all life on earth is directly or indirectly dependent on phytoplankton primary productivity. In many aquatic systems, phytoplankton primary production is limited by the availability of nitrogen in the environment. Therefore, studying the dynamics of nitrogen uptake and assimilation by phytoplankton cells is critically important for understanding many ecosystem services and global biogeochemical cycles. Mathematical models are particularly powerful tools for analyzing dynamic processes in many areas of ecology, but so far their employment with phytoplankton time-series has been limited. Specifically, published phytoplankton models are unable to explicitly account for the role of different nitrogen forms on cell division and can only be calibrated with time-consuming and impractical monitoring of specific variables. Overall, this thesis aimed to expand previous models by incorporating important processes regulating nitrogen utilization in phytoplankton cells, and by improving their calibration with proxy data routinely monitored in experimental studies.

Nitrate and ammonium are the two most important sources of inorganic nitrogen driving phytoplankton primary productivity. The performance of phytoplankton species changes when reared with either of these two forms of nitrogen individually, as well as when they are both present, or when cells have experienced previous periods of nitrogen starvation. However, current functional responses are unable to capture transient and interactive dynamics of nitrate and ammonium uptake, nor can they capture how these two forms of nitrogen differently influence cell division. Hence, in chapter 2, I designed and empirically tested a new process-based model that includes uptake of both nitrate and ammonium, as well as the effects of starvation length and inhibition of nitrate uptake by ammonium on phytoplankton cell division. Results for the green alga Chlorella sp. showed that a single parameterization of the model performed well across data from laboratory cultures started at 12 different initial conditions. This new model allowed for the first time the quantification of nitrate-ammonium utilization traits of a phytoplankton species. This contributes to a more comprehensive understanding of the factors underpinning the high variation in nitrate-ammonium assimilation observed in natural and engineered systems.

Characterizing resource utilization traits of a species is particularly important for identifying processes promoting biodiversity and ecosystem functioning in nature. Most trait-based studies define species by their mean trait values and assume intraspecific trait variability to be negligible compared to interspecific differences. However, phenotypic plasticity may be an important source of variation in phytoplankton species, which are well known for their ability to rapidly adjust their cell size according to biotic and abiotic conditions. In chapter 3, I used the model designed in chapter 2 to evaluate the effects of cell size plasticity on the nitrogen utilization traits of the green alga Desmodesmus armatus, reared under different nitrogen sources (nitrate, ammonium, or both) and nitrogen histories (N-replete and N-deplete). Results showed that nitrate-ammonium utilization traits depended substantially on mean cell size and nitrogen history and that representing phytoplankton species by their mean trait values (as per traditional approaches) could underestimate the actual performance of a species by as much as one order of magnitude. These results highlight the ecological importance of intraspecific variability in determining the ability of a species to adjust to new environmental conditions.

Biologically, it is well-known that the internal concentration of the most limiting nutrient (cell "quota") is what determines the growth rate of a cell. Given the critical importance of nitrogen for phytoplankton cell division, monitoring nitrogen quota is important to understand aquatic primary productivity, phytoplankton ecology, eutrophication and algal blooms. However, current methods to directly monitor nitrogen quota remain inaccurate, expensive, destructive, and time-consuming. Thus, in chapter 4, I tested the hypothesis that optical changes in single cells, which can be rapidly and accurately monitored with a standard flow cytometer, can provide reliable proxies for per-cell internal nitrogen. Results from four freshwater phytoplankton species showed that cellular nitrogen quota could be estimated accurately (R² = 0.9) from cell optical properties and medium nitrogen, and that the relationship did not change among different species or different initial conditions. In particular, red chlorophyll autofluorescence (from here on simply "red fluorescence") was the most important variable explaining 77% of the total variability in total cell nitrogen. These results indicate that optical flow cytometric variables are a reliable and non-destructive method to estimate nitrogen quota in phytoplankton cells.

Finding an efficient proxy to evaluate cell nitrogen quota is particularly valuable for extending the applicability of phytoplankton models. The internal nitrogen status of a cell is critical to analyze the dynamics of nitrogen-limited phytoplankton populations, but accounting for this process in phytoplankton models requires monitoring per-cell nitrogen quota, which is time-consuming, inaccurate, and destructive. Instead, the method I proposed in chapter 4 to quantify nitrogen quota using the optical properties of individual cells is rapid, precise, accurate, and non-destructive. Hence, in chapter 5, I evaluated a new way to model phytoplankton populations, consisting in explicitly including cell optical properties as a proxy for nitrogen quota within phytoplankton Quota models. Results showed that accounting for cell optical properties could improve the performance of phytoplankton population models while still accounting for the biologically important process of cell nitrogen storage. More broadly, these findings highlight the importance of identifying proxy variables for the internal condition of an organism when using population models to analyze species dynamics.

The overarching aim of my thesis was to improve current phytoplankton models for the analysis of phytoplankton nitrogen utilization. This was achieved by presenting and calibrating a new mathematical framework describing the dynamics of nitrate-ammonium utilization in phytoplankton populations (chapter 2), by evaluating the effect of mean cell size and previous nitrogen history in determining the nitrogen utilization of a cell (chapter 3), and by documenting the importance of cell optical properties for explaining the dynamics of phytoplankton populations (chapters 4 and 5). These findings improve our ability to identify, analyze, and understand the relationships between nitrogen concentrations in the environment and phytoplankton populations. More broadly, this thesis offers new mathematical tools to better investigate the processes regulating phytoplankton primary productivity in nature and engineered systems.

Item ID: 46585
Item Type: Thesis (PhD)
Keywords: allometric scaling, ammonium inhibition, aquaculture, biomass generation, bioproducts, cell nutrient status, chlorophyta, commercial production, dynamic models, ecological modelling, flow cytometry, fluorescence, Markov Chain Monte Carlo (MCMC), microalgae, nitrogen limitation, nitrogen starvation, nitrogen status, optical properties, phytoplankton dynamics, phytoplankton, quota model, quota, state-space models, stochastic simulations
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Publications arising from this thesis are available from the Related URLs field. The publications are:

Chapter 2:Malerba, Martino E., Connolly, Sean R., and Heimann, Kirsten (2015) An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake. Ecological Modelling, 317. pp. 30-40.

Chapter 4: Malerba, Martino E., Connolly, Sean R., and Heimann, Kirsten (2016) Standard flow cytometry as a rapid and non-destructive proxy for cell nitrogen quota. Journal of Applied Phycology, 28 (2). pp. 1085-1095.

Chapter 5: Malerba, Martino E., Heimann, Kirsten, and Connolly, Sean R. (2016) Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen. Journal of Theoretical Biology, 404. pp. 1-9.

Date Deposited: 06 Dec 2016 22:50
FoR Codes: 06 BIOLOGICAL SCIENCES > 0607 Plant Biology > 060701 Phycology (incl Marine Grasses) @ 33%
06 BIOLOGICAL SCIENCES > 0602 Ecology > 060204 Freshwater Ecology @ 33%
06 BIOLOGICAL SCIENCES > 0602 Ecology > 060207 Population Ecology @ 34%
SEO Codes: 96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960807 Fresh, Ground and Surface Water Flora, Fauna and Biodiversity @ 40%
97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 40%
82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8299 Other Plant Production and Plant Primary Products > 829999 Plant Production and Plant Primary Products not elsewhere classified @ 20%
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