Timing and placing samplings to optimally calibrate a reactive transport model: exploring the potential for <i>Escherichia coli</i> 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 the maximum of information. Using a criterion related to the Fisher information matrix, it is possible to design a sampling scheme that will enable the most precise model parameter estimates. This approach was applied to a reactive transport model (based on SLIM) of Escherichia coli 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 will 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

Design of a sampling strategy to optimally calibrate a reactive transport model: Exploring the potential for <i>Escherichia coli</i> 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

Cortical cells reveal APP as a regulator of KCC2 in gabaergic neurotransmission

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Limnological variability and pelagic fish abundance (Stolothrissa tanganicae and Lates stappersii) in Lake Tanganyika

The abundance of two main pelagic fish species in Lake Tanganyika (Stolothrissa tanganicae and Lates stappersii) has always been observed to fluctuate considerably at different time scales. The inverse correlation between the abundance of these species has often been interpreted as the consequence of predator-prey relations (avoidance behaviour by the prey). However, currently the two species often appear spatially segregated in the lake, S. tanganicae dominating in the north while L. stappersii is generally abundant in the south where it feeds mostly on shrimps. A fluctuating abundance of the species is nevertheless observed. As these fish species have a major importance for the fisheries, we investigated the limnological variability in relation to the short-term variability of fish catches. The abundance of S. tanganicae was positively correlated to plankton biomass (r = 0.65), while water transparency (r = 0.56), depth of mixed layer (r = -0.70) and oxygenated water appeared important drivers for the abundance of L. stappersii. Alternating "mixing" and "stable" states of the epilimnion related to seasonal and internal waves variability are probably determinant for the short-term variability in abundance of S. tanganicae and L. stappersii. In the framework of this study, remote sensing has shown a potentially interesting application for fisheries research at Lake Tanganyika. We observed a close correspondence between phytoplankton blooms at the time of trade winds changes and increased catches of S. tanganicae in the south. The anti-correlated abundance of S. tanganicae and L. stappersii probably mainly reflects the underlying fluctuating limnological environment. Fisheries studies need to integrate limnological and planktonic monitoring to better understand large and complex ecosystems such as Lake Tanganyika