Impact of ocean acidification on phytoplankton growth and aggregation

Since the industrial revolution, the ocean has absorbed around one third of the anthropogenic CO2, which induced a profound alteration of the carbonate system commonly known as ocean acidification. Since the preindustrial times, the average ocean surface water pH has fallen by 0.1 units, from approximately 8.2 to 8.1 and a further decrease of 0.4 pH units is expected for the end of the century. Despite their microscopic size, marine diatoms are bio-geo-chemically a very important group, responsible for the export of massive amount of carbon to deep waters and sediments. The knowledge of the potential effects of ocean acidification on the phytoplankton growth and on biological pump is still at its infancy. This study wants to investigate the effect of ocean acidification on the growth of the diatom Skeletonema marinoi and on its aggregation, using a mechanistic approach. The experiment consisted of two treatments (Present and Future) representing different pCO2 conditions and two sequential experimental phases. During the cell growth phase a culture of S. marinoi was inoculated into transparent bags and the effect of ocean acidification was studied on various growth parameters, including DOC and TEP production. The aggregation phase consisted in the incubation of the cultures into rolling tanks where the sinking of particles through the water column was simulated and aggregation promoted. Since few studies investigated the effect of pH on the growth of S. marinoi and none used pH ranges that are compatible with the OA scenarios, there were no baselines. I have shown here, that OA does not affect the cell growth of S. marinoi, suggesting that the physiology of this species is robust in respect to the changes in the carbonate chemistry expected for the end of the century. Furthermore, according to my results, OA does not affect the aggregation of S. marinoi in a consistent manner, suggesting that this process has a high natural variability but is not influenced by OA in a predictable way. The effect of OA was tested over a variety of factors including the number of aggregates produced, their size and sinking velocity, the algal, bacterial and TEP content. Many of these variables showed significant treatment effects but none of these were consistent between the two experiments.

Influence of microstructure variability on short crack growth behavior

Fatigue life in metals is predicted utilizing regression analysis of large sets of experimental data, thus representing the material’s macroscopic response. Furthermore, a high variability in the short crack growth (SCG) rate has been observed in polycrystalline materials, in which the evolution and distributionof local plasticity is strongly influenced by the microstructure features. The present work serves to (a) identify the relationship between the crack driving force based on the local microstructure in the proximity of the crack-tip and (b) defines the correlation between scatter observed in the SCG rates to variability in the microstructure. A crystal plasticity model based on the fast Fourier transform formulation of the elasto-viscoplastic problem (CP-EVP-FFT) is used, since the ability to account for the both elastic and plastic regime is critical in fatigue. Fatigue is governed by slip irreversibility, resulting in crack growth, which starts to occur during local elasto-plastic transition. To investigate the effects of microstructure variability on the SCG rate, sets of different microstructure realizations are constructed, in which cracks of different length are introduced to mimic quasi-static SCG in engineering alloys. From these results, the behavior of the characteristic variables of different length scale are analyzed: (i) Von Mises stress fields (ii) resolved shear stress/strain in the pertinent slip systems, and (iii) slip accumulation/irreversibilities. Through fatigue indicator parameters (FIP), scatter within the SCG rates is related to variability in the microstructural features; the results demonstrate that this relationship between microstructure variability and uncertainty in fatigue behavior is critical for accurate fatigue life prediction.

Modelling growth dynamics and toxin production in Ostreopsis cf. ovata

The benthic dinoflagellate O. ovata represents a serious threat for human health and for the ecology of its blooming areas: thanks to its toxicity this microalga has been responsible for several cases of human intoxication and mass mortalities of benthic invertebrates. Although the large number of studies on this dinoflagellate, the mechanisms underpinning O. ovata growth and toxin production are still far to be fully understood. In this work we have enriched the dataset on this species by carrying out a new experiment on an Adriatic O. cf. ovata strain. Data from this experiment (named Beta) and from another comparable experiment previously conducted on the same strain (named Alpha), revealed some interesting aspects of this dinoflagellate: it is able to grow also in a condition of strong intracellular nutrient deficiency (C:P molar ratio > 400; C:N > 25), reaching extremely low values of chlorophyll-a to carbon ratio (0.0004). Was also found a significant inverse relationships (r > -0.7) between cellular toxin to carbon and cellular nutrient to carbon ratios of experiment Alpha. In the light of these result, we hypothesized that in O. cf. ovata nutrient-stress conditions (intended as intracellular nutrient deficiency) can cause: i) an increase in toxin production; ii) a strong decrease in chlorophyll-a synthesis; iii) a lowering of metabolism associated with the formation of a sort of resting stage. We then used a modelling approach to test and critically evaluate these hypotheses in a mechanistic way: newly developed formulation describing toxin production and fate, and ad hoc changes in the already existent formulations describing chlorophyll synthesis, rest respiration, and mortality, have been incorporated in a simplified version of the European Regional Seas Ecosystem Model (ERSEM), together with a new ad hoc parameterization. The adapted model was able to accurately reproduce many of the trends observed in the Alpha experiment, allowing us to support our hypotheses. Instead the simulations of the experiment Beta were not fully satisfying in quantitative terms. We explained this gap with the presumed different physiological behaviors between the algae of the two experiments, due to the different pre-experimental periods of acclimation: the model was not able to reproduce acclimation processes in its simulations of the experiment Beta. Thus we attempt to simulate the acclimation of the algae to nutrient-stress conditions by manual intervention on some parameters of nutrient-stress thresholds, but we received conflicting results. Further studies are required to shed light on this interesting aspect. In this work we also improve the range of applicability of a state of the art marine biogeochemical model (ERSEM) by implementing in it an ecological relevant process such as the production of toxic compounds.