Tuomas Kärnä

Infrastructure for collaborative science and societal applications in the Columbia River estuary

To meet societal needs, modern estuarine science needs to be interdisciplinary and collaborative, combine discovery with hypotheses testing, and be responsive to issues facing both regional and global stakeholders. Such an approach is best conducted with the benefit of data-rich environments, where information from sensors and models is openly accessible within convenient timeframes. Here, we introduce the operational infrastructure of one such data-rich environment, a collaboratory created to support (a) interdisciplinary research in the Columbia River estuary by the multi-institutional team of investigators of the Science and Technology Center for Coastal Margin Observation & Prediction and (b) the integration of scientific knowledge into regional decision making. Core components of the operational infrastructure are an observation network, a modeling system and a cyber-infrastructure, each of which is described. The observation network is anchored on an extensive array of long-term stations, many of them interdisciplinary, and is complemented by on-demand deployment of temporary stations and mobile platforms, often in coordinated field campaigns. The modeling system is based on finiteelement unstructured-grid codes and includes operational and process-oriented simulations of circulation, sediments and ecosystem processes. The flow of information is managed through a dedicated cyber-infrastructure, conversant with regional and national observing systems.

Design of a sampling strategy to optimally calibrate a reactive transport model: Exploring the potential for Escherichia coli in the Scheldt Estuary

For the calibration of any model, measurements are necessary. As measurements are expensive, it is of interest to determine beforehand which kind of samples will provide maximal information. Using a criterion related to the Fisher information matrix as a measure for information content, it is possible to design a sampling scheme that will enable the most precise parameter estimates. This approach was applied to a reactive transport model (based on the Second-generation Louvain-la-Neuve Ice-ocean Model, SLIM) of Escherichia coli concentrations in the Scheldt Estuary. As this estuary is highly influenced by the tide, it is expected that careful timing of the samples with respect to the tidal cycle can have an effect on the quality of the data. The timing and also the positioning of samples were optimised according to the proposed criterion. In the investigated case studies the precision of the estimated parameters could be improved by up to a factor of ten, confirming the usefulness of this approach to maximize the amount of information that can be retrieved from a fixed number of samples. Precise parameter values will result in more reliable model simulations, which can be used for interpretation, or can in turn serve to plan subsequent sampling campaigns to further constrain the model parameters.

Metagenomic evidence for reciprocal particle exchange between the mainstem estuary and lateral bay sediments of the lower Columbia River

Lateral bays of the lower Columbia River estuary are areas of enhanced water retention that influence net ecosystem metabolism through activities of their diverse microbial communities. Metagenomic characterization of sediment microbiota from three disparate sites in two brackish lateral bays (Baker and Youngs) produced ∼100 Gbp of DNA sequence data analyzed subsequently for predicted SSU rRNA and peptide-coding genes. The metagenomes were dominated by Bacteria. A large component of Eukaryota was present in Youngs Bay samples, i.e., the inner bay sediment was enriched with the invasive New Zealand mudsnail, Potamopyrgus antipodarum, known for high ammonia production. The metagenome was also highly enriched with an archaeal ammonia oxidizer closely related to Nitrosoarchaeum limnia. Combined analysis of sequences and continuous, high-resolution time series of biogeochemical data from fixed and mobile platforms revealed the importance of large-scale reciprocal particle exchanges between the mainstem estuarine water column and lateral bay sediments. Deposition of marine diatom particles in sediments near Youngs Bay mouth was associated with a dramatic enrichment of Bacteroidetes (58% of total Bacteria) and corresponding genes involved in phytoplankton polysaccharide degradation. The Baker Bay sediment metagenome contained abundant Archaea, including diverse methanogens, as well as functional genes for methylotrophy and taxonomic markers for syntrophic bacteria, suggesting that active methane cycling occurs at this location. Our previous work showed enrichments of similar anaerobic taxa in particulate matter of the mainstem estuarine water column. In total, our results identify the lateral bays as both sources and sinks of biogenic particles significantly impacting microbial community composition and biogeochemical activities in the estuary.

Gaussian fitting based FDA for chemometrics

In Functional Data Analysis (FDA) multivariate data are considered as sampled functions. We propose a non-supervised method for finding a good function basis that is built on the data set. The basis consists of a set of Gaussian kernels that are optimized for an accurate fitting. The proposed methodology is experimented with two spectrometric data sets. The obtained weights are further scaled using a Delta Test (DT) to improve the prediction performance. Least Squares Support Vector Machine (LS-SVM) model is used for estimation.

US Experience Will Advance Gulf Ecosystem Research

This paper addresses the vision and early steps of the cooperation between the Center for Coastal Margin Observation and Prediction (CMOP) in Oregon, United States and the emerging Gulf Ecosystems Research Center (GERC) at the American University of Sharjah, UAE. The cooperation focuses on a better understanding and ability to predict the Arabian Gulf as a complex ecosystem, and involves science, technology and training components. An ultimate goal is the development for the Gulf of a “collaboratory” inspired on the concepts of integration of observations, simulations and stakeholder needs developed by CMOP for the Columbia River coastal margin, in the Eastern North Pacific. An early phase of the cooperation addresses the development of a 3D numerical model for the Arabian Gulf water circulation. A very preliminary forecasting system has been developed at CMOP, and its skill will be systematically assessed and improved by GERC and CMOP over the next several years, with the progressive deployment of a targeted observation network. Preliminary products include the visualization of the salinity fields associated with various river plumes. The model used was SELFE (a Semi-implicit Eulerian–Lagrangian Finite-Element model for cross-scale ocean circulation), the same that is being used for the Gulf predictions. Exploratory simulations were made to assess the ability of simple grid refinement strategies and/or use of higher order numerical schemes in improving the representation of the complex dynamics of plumes, filaments (eddies) and upwelling in the continental shelf of the Eastern North Pacific, off the Columbia River. Results suggested the need for automated grid optimization strategies, which are currently in progress.