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Eutrophication coupled to climate change disturbs the balance between competition and coexistence in microbial communities including the partitioning of organic and inorganic nutrients between phytoplankton and bacteria. Competition for inorganic nutrients has been regarded as one of the drivers affecting the productivity of the eutrophied coastal Baltic Sea. Yet, it is unknown at the molecular expression level how resources are competed for, by phytoplankton and bacteria, and what impact this competition has on the community composition. Here we use metatranscriptomics and amplicon sequencing and compare known metabolic pathways of both phytoplankton and bacteria co-occurring during a summer bloom in the archipelago of Åland in the Baltic Sea to examine phytoplankton bacteria resource partitioning. The expression of selected pathways of carbon (C), nitrogen (N), and phosphorus (P) metabolism varied over time, independently, for both phytoplankton and bacteria, indicating partitioning of the available organic and inorganic resources. This occurs regardless of eukaryotic plankton growth phase (exponential or stationary), based on expression data, and microbial community composition. Further, the availability of different nutrient resources affected the functional response by the bacteria, observed as minor compositional changes, at class level, in an otherwise taxonomically stable bacterial community. Resource partitioning and functional flexibility seem necessary in order to maintain phytoplankton-bacteria interactions at stable environmental conditions. More detailed knowledge of which organisms utilize certain nutrient species are important for more accurate projections of the fate of coastal waters.

Thiamin (vitamin B1) is primarily produced by bacteria and phytoplankton in aquatic food webs and transferred by ingestion to higher trophic levels. However, much remains unknown regarding production, content and transfer of this water-soluble, essential micronutrient. Hence, the thiamin content of six phytoplankton species from different taxa was investigated, along with the effect of thiamin amendment on thiamin content. Furthermore, thiamin transfer to copepods was estimated in feeding experiments. Prey type, not phytoplankton thiamin content per se, was the most important factor for the transfer of thiamin, as it was lowest from filamentous Cyanophyceae and highest from more easily ingested prey like Dunaliella tertiolecta and Rhodomonas salina. Cyanophyceae had the highest thiamin content of the investigated species, eightfold higher than the lowest. Phytoplankton varied in thiamin content related to the supply of thiamin, where thiamin addition enabled higher thiamin content in some species, while copepod thiamin content was less variable. In all, thiamin transfer is not only dependent on the prey thiamin content, but also the edibility and/or digestibility is of importance. Thiamin is essential for all organisms, and this study constitutes an important building block to understanding the dynamics and transfer of thiamin in the aquatic food web.

There are many ways in which scientists can engage in entrepreneurial activities. The context of this paper is a Swedish research group in marine ecology which became increasingly involved in entrepreneurial activities. The paper focus on the what, why and how of entrepreneurship as part of an academic role. The study was conducted as an interactive research process, involving activities as well as interviewing participants in the project. Theories of identity work, role identity and passion were used to analyse this context. Two distinct but simultaneous processes were identified: first, when scientists engage in commercial entrepreneurial activities and react by reaffirming their roles as academics and, second, when scientists engage in entrepreneurial activities in a broad sense, fulfilling environmental and social goals (this is compatible with their scientific passion connected to their academic role identity). The paper shows that scientists can be entrepreneurial while working with social and environmental responsibility with no conflict between their entrepreneurial activity and their role as an academic.

In Bayesian statistics, a general and widely used approach to extract information from (complex) posterior distributions relies on Markov chain Monte Carlo (MCMC) methods. Although MCMC samplers provide powerful tools for Bayesian inference in various applications, they are often computationally intensive due to their iterative nature. In this thesis, we develop a much faster alternative for approximate Bayesian inference called ‘‘Laplace-P-splines’’ (LPS) that combines Laplace approximations to selected posterior distributions and P-splines for flexible modeling of smooth model terms. The first part of the thesis starts with the implementation of LPS in the framework of survival analysis. First, the synergy between Laplace’s method and P-splines is exploited in the Cox proportional hazards model where the log baseline hazard is specified as a linear combination of cubic B-splines. The LPS approach is then extended to the promotion time cure model that intrinsically accounts for long-term survivors who will never experience the event of interest whatever the duration of the follow-up. The second part of the thesis expands the LPS methodology to (generalized) additive models. Efficient methods for exploring the posterior penalty space are proposed based on analytical formulas for the gradient and Hessian of the joint posterior of the penalty vector. Finally, the third part is devoted to a software package written in the R language that gathers several routines to implement the proposed methodology in latent Gaussian models., (SC - Sciences) -- UCL, 2020

In recent years, prediction models have become increasingly popular tools to estimate the risk of a person developing a specific event of interest at a particular time, given his/her characteristics. Accuracy of these predictive models is critical as it determines the quality of their predictions that form the scientific evidence for informing treatment or other clinical decisions for individual patients. Therefore, nowadays, it is widely accepted that assessing the predictive accuracy of predictive models is a critical step before make use of them for a clinical practice. The ability of the models to distinguish between two classes (e.g., case and control subjects) is one of the most important criteria to evaluate predictive accuracy. To this end, the receiver operating characteristic (ROC) curve and the associated summary indices are the most widely used tools to evaluate the classification accuracy of the model. There exist various methods to estimate the time-dependent ROC curve and the associated summary indices. However, there is a lack of literature that addresses issues such as the presence of cure fraction, interval censoring, and smoothing the ROC curve. This thesis fills these gaps by introducing some new estimation and inference methods for time-dependent ROC curves and associated summ...., (SC - Sciences) -- UCL, 2020

In survival analysis with competing risks, the treatment effect is typically expressed using cause-specific or subdistribution hazard ratios, both relying on proportional hazards assumptions. This paper proposes a nonparametric approach to analyze competing risks data based on generalized pairwise comparisons (GPC). GPC estimate the net benefit, defined as the probability that a patient from the treatment group has a better outcome than a patient from the control group minus the probability of the opposite situation, by comparing all pairs of patients taking one patient from each group. GPC allow using clinically relevant thresholds and simultaneously analyzing multiple prioritized endpoints. We show that under proportional subdistribution hazards, the net benefit for competing risks settings can be expressed as a decreasing function of the subdistribution hazard ratio, taking a value 0 when the latter equals 1. We propose four net benefit estimators dealing differently with censoring. Among them, the Péron estimator uses the Aalen–Johansen estimator of the cumulative incidence functions to classify the pairs for which the patient with the best outcome could not be determined due to censoring. We use simulations to study the bias of these estimators and the size and power of the tests based on the net benefit. The Péron estimator was approximately unbiased when the sample size was large and the censoring distribution’s support sufficiently wide. With one endpoint, our approach showed a comparable power to a proportional subdistribution hazards model even under proportional subdistribution hazards. An application of the methodology in oncology is provided.

There is increasing concern that accelerating environmental change attributed to human-induced warming of the planet may substantially alter the patterns, distribution and intensity of Harmful Algal Blooms (HABs). Changes in temperature, ocean acidification, precipitation, nutrient stress or availability, and the physical structure of the water column all influence the productivity, composition, and global range of phytoplankton assemblages, but large uncertainty remains about how integration of these climate drivers might shape future HABs. Presented here are the collective deliberations from a symposium on HABs and climate change where the research challenges to understanding potential linkages between HABs and climate were considered, along with new research directions to better define these linkages. In addition to the likely effects of physical (temperature, salinity, stratification, light, changing storm intensity), chemical (nutrients, ocean acidification), and biological (grazer) drivers on microalgae (senso lato), symposium participants explored more broadly the subjects of cyanobacterial HABs, benthic HABs, HAB effects on fisheries, HAB modelling challenges, and the contributions that molecular approaches can bring to HAB studies. There was consensus that alongside traditional research, HAB scientists must set new courses of research and practices to deliver the conceptual and quantitative advances required to forecast future HAB trends. These different practices encompass laboratory and field studies, long-term observational programs, retrospectives, as well as the study of socioeconomic drivers and linkages with aquaculture and fisheries. In anticipation of growing HAB problems, research on potential mitigation strategies should be a priority. It is recommended that a substantial portion of HAB research among laboratories be directed collectively at a small sub-set of HAB species and questions in order to fast-track advances in our understanding. Climate

Algal lipids have been observed to increase during autumn conditions (low light, low mean temperature, and diurnal shift in temperature), in large-scale outdoor photobioreactors. In this paper, we tested the effect of diurnal shifts in temperature (DS) and nitrogen (N) limitation on algal BODIPY lipid fluorescence cell?1 (BPF). We show that DS increased BPF in algal biomass up to 28% more compared with N limitation, the standard stressor to boost neutral lipids (NL) in commercial production. Biomass yield was constant, regardless the DS range (6°C-12°C). A combination of both stressors had an additive effect on algal BPF. A polyculture from an outdoor photobioreactor was cultivated under controlled conditions at different regimes of light, temperature, and N limitation. DSs were mimicking autumn conditions with a difference of 6°C, 10°C, and 12°C between day and night. Biomass and BPF were monitored over one to two weeks, and NLs were stained with a fluorescent marker (BODIPY) and detected with flow cytometry. Results indicate that, during autumn conditions, daily heating and cooling processes in contrast to N limitation do not challenge the trade-off between biomass production and BPF. During seasons when day temperature is still relatively high, DSs are rapid BPF boosting stressors, while N limitation could be applied to boost BPF further during other seasons.

The fresh-water cyanobacterium Microcystis is known to form blooms world-wide, and is often responsible for the production of microcystins found in lake water. Microcystins are non-ribosomal peptides with toxic effects, e.g. on vertebrates, but their function remains largely unresolved. Moreover, not all strains produce microcystins, and many different microcystin variants have been described. Here we explored the diversity of microcystin variants within Microcystis botrys, a common bloom-former in Sweden. We isolated a total of 130 strains through the duration of a bloom in eutrophic Lake Vomb, and analyzed their microcystin profiles with tandem mass spectrometry (LC-MS/MS). We found that microcystin producing (28.5%) and non-producing (71.5%) M. botrys strains, co-existed throughout the bloom. However, microcystin producing strains were more prevalent towards the end of the sampling period. Overall, 26 unique M. botrys chemotypes were identified, and while some chemotypes re-occurred, others were found only once. The M. botrys chemotypes showed considerable variation both in terms of number of microcystin variants, as well as in what combinations the variants occurred. To our knowledge, this is the first report on microcystin chemotype variation and dynamics in M. botrys. In addition, our study verifies the co-existence of microcystin and non-microcystin producing strains, and we propose that environmental conditions may be implicated in determining their composition.

Two annual Baltic Sea phytoplankton blooms occur in spring and summer. The bloom intensity is determined by nutrient concentrations in the water, while the period depends on weather conditions. During the course of the bloom, dead cells sink to the sediment where their degradation consumes oxygen to create hypoxic zones (< 2 mg/L dissolved oxygen). These zones prevent the establishment of benthic communities and may result in fish mortality. The aim of the study was to determine how the spring and autumn sediment chemistry and microbial community composition changed due to degradation of diatom or cyanobacterial biomass, respectively. Results from incubation of sediment cores showed some typical anaerobic microbial processes after biomass addition such as a decrease in NO2− + NO3− in the sediment surface (0–1 cm) and iron in the underlying layer (1–2 cm). In addition, an increase in NO2− + NO3− was observed in the overlying benthic water in all amended and control incubations. The combination of NO2− + NO3− diffusion plus nitrification could not account for this increase. Based on 16S rRNA gene sequences, the addition of cyanobacterial biomass during autumn caused a large increase in ferrous iron-oxidizing archaea while diatom biomass amendment during spring caused minor changes in the microbial community. Considering that OTUs sharing lineages with acidophilic microorganisms had a high relative abundance during autumn, it was suggested that specific niches developed in sediment microenvironments. These findings highlight the importance of nitrogen cycling and early microbial community changes in the sediment due to sinking phytoplankton before potential hypoxia occurs.