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

Capturing the residence time boundary layer - Application to the Scheldt Estuary.

At high Peclet number, the residence time exhibits a boundary layer adjacent to incoming open boundaries. In a Eulerian model, not resolving this boundary layer can generate spurious oscillations that can propagate into the area of interest. However, resolving this boundary layer would require an unacceptably high spatial resolution. Therefore, alternative methods are needed in which no grid refinement is required to capture the key aspects of the physics of the residence time boundary layer. An extended finite element method representation and a boundary layer parameterisation are presented and tested herein. It is also explained how to preserve local consistency in reversed time simulations so as to avoid the generation of spurious residence time extrema. Finally, the boundary layer parameterisation is applied to the computation of the residence time in the Scheldt Estuary (Belgium/The Netherlands). This timescale is simulated by means of a depth-integrated, finite element, unstructured mesh model, with a high space-time resolution. It is seen that the residence time temporal variations are mainly affected by the semi-diurnal tides. However, the spring-neap variability also impacts the residence time, particularly in the sandbank and shallow areas. Seasonal variability is also observed, which is induced by the fluctuations over the year of the upstream flows. In general, the residence time is an increasing function of the distance to the mouth of the estuary. However, smaller-scale fluctuations are also present: they are caused by local bathymetric features and their impact on the hydrodynamics

The Pan-STARRS1 Surveys

Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveys including the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands ($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in the stacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3, 21.4) respectively. The upper bound on the systematic uncertainty in the photometric calibration across the sky is 7-12 millimag depending on the bandpass. The systematic uncertainty of the astrometric calibration using the Gaia frame comes from a comparison of the results with Gaia: the standard deviation of the mean and median residuals ($\Delta ra, \Delta dec$) are (2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRS system and the design of the PS1 surveys are described and an overview of the resulting image and catalog data products and their basic characteristics are described together with a summary of important results. The images, reduced data products, and derived data products from the Pan-STARRS1 surveys are available to the community from the Mikulski Archive for Space Telescopes (MAST) at STScI

The Pan-STARRS1 Surveys

Pan-STARRS1 has carried out a set of distinct synoptic imaging sky surveys including the $3\pi$ Steradian Survey and the Medium Deep Survey in 5 bands ($grizy_{P1}$). The mean 5$\sigma$ point source limiting sensitivities in the stacked 3$\pi$ Steradian Survey in $grizy_{P1}$ are (23.3, 23.2, 23.1, 22.3, 21.4) respectively. The upper bound on the systematic uncertainty in the photometric calibration across the sky is 7-12 millimag depending on the bandpass. The systematic uncertainty of the astrometric calibration using the Gaia frame comes from a comparison of the results with Gaia: the standard deviation of the mean and median residuals ($\Delta ra, \Delta dec$) are (2.3, 1.7) milliarcsec, and (3.1, 4.8) milliarcsec respectively. The Pan-STARRS system and the design of the PS1 surveys are described and an overview of the resulting image and catalog data products and their basic characteristics are described together with a summary of important results. The images, reduced data products, and derived data products from the Pan-STARRS1 surveys are available to the community from the Mikulski Archive for Space Telescopes (MAST) at STScI