Periphyton density influences organochlorine accumulation in rivers

To investigate the influence of eutrophication on organochlorine dynamics in lotic systems, we related polychlorinated biphenyl (PCB) concentrations in brown trout (Salmo trutta) to the periphyton density and total phosphorus concentrations (Tot-P) in 10 Swedish rivers. Tot-P concentrations in the water ranged from 37 +/- 4 to 156 +/- 51 mug L-1. Periphyton density in the rivers during the experiment ranged from 6 to 199 mg carbon (C) m(-2) and was not related to the Tot-P concentration. The concentrations of PCB 52, PCB 66/95, PCB 90/101, PCB 132/153/105, PCB 160/138/158, PCB 180, and PCB 194 in brown trout were positively related to both periphyton density and Tot-P concentration, with periphyton density having the highest degree of correlation, 40-58%, compared to 6-44% for Tot-P. All seven PCB concentrations in brown trout were significantly, positively related to the areal mass (ng m(-2)) of the PCB in periphyton (r(2) = 0.69-0.86). Contrary to what has been found for lakes, eutrophication and organochlorine accumulations are positively related in rivers. Thus, an increase in primary production should increase the exposure of the local biota but lead to a decrease of the downstream transport of these pollutants to coastal areas and oceans

COVID-19 lockdown reveals tourists as seabird guardians

The widespread lockdowns put in place to limit the spread of the new coronavirus disease (COVID-19) offers a rare opportunity in understanding how human presence influence ecosystems. Using data from long-term seabird monitoring, we reveal a previously concealed guarding effect by tourist groups on an iconic seabird colony in the Baltic Sea. The absence of tourists in 2020 lead to a sevenfold increase in presence of white-tailed eagles Haliaeetus albicilla, a sevenfold increase in their disturbance of breeding common murres Uria aalge and causing 26% lower murre productivity than the long-term average. Eagles did not prey on murres, but their frequent disturbances delayed egg laying and facilitated egg predation from herring gulls Larus argentatus and hooded crows Corvus cornix. Based on our findings, we suggest that human presence could be used as a strategic measure in guarding seabird colonies, and that a social-ecological systems perspective is vital for long-term success in protected area management

Inward and outward currents of native and cloned K(ATP) channels (Kir6.2/SUR1) share single-channel kinetic properties

BACKGROUND: The ATP-sensitive K(+) (K(ATP)) channel is found in a variety of tissues extending from the heart and vascular smooth muscles to the endocrine pancreas and brain. Common to all K(ATP) channels is the pore-forming subunit Kir6.x, a member of the family of small inwardly rectifying K(+) channels, and the regulatory subunit sulfonylurea receptor (SURx). In insulin secreting β-cells in the endocrine part of the pancreas, where the channel is best studied, the K(ATP) channel consists of Kir6.2 and SUR1. Under physiological conditions, the K(ATP) channel current flow is outward at membrane potentials more positive than the K(+) equilibrium potential around −80 mV. However, K(ATP) channel kinetics have been extensively investigated for inward currents and the single-channel kinetic model is based on this type of recording, whereas only a limited amount of work has focused on outward current kinetics. METHODS: We have estimated the kinetic properties of both native and cloned K(ATP) channels under varying ionic gradients and membrane potentials using the patch-clamp technique. RESULTS: Analyses of outward currents in K(ATP) and cloned Kir6.2ΔC26 channels, alone or co-expressed with SUR1, show openings that are not grouped in bursts as seen for inward currents. Burst duration for inward current corresponds well to open time for outward current. CONCLUSIONS: Outward K(ATP) channel currents are not grouped in bursts regardless of membrane potential, and channel open time for outward currents corresponds to burst duration for inward currents

Data evaluation and numerical modeling of hydrological interactions between active layer, lake and talik in a permafrost catchment, Western Greenland

SummaryThis study investigates annual water balance conditions and their spatiotemporal variability under a wide variety of atmospheric driving conditions in the periglacial permafrost catchment of Two Boat Lake in Western Greenland. The study uses and combines a comprehensive hydrological multi-parameter dataset measured at the site with site conceptualization and numerical model development, application and testing. The model result reproduces measured lake and groundwater levels, as well as observations made by time-lapse cameras. The results highlights the importance of numerical modeling that takes into account and combines evapotranspiration with other surface and subsurface hydrological processes at various depths, in order to quantitatively understand and represent the dynamics and complexity of the interactions between meteorology, active layer hydrology, lakes, and unfrozen groundwater below permafrost in periglacial catchments. Regarding these interactions, the water flow between the studied lake and a through talik within and beneath it is found to be small compared to other water balance components. The modeling results show that recharge and discharge conditions in the talik can shift in time, while the lake and active layer conditions in the studied catchment are independent of catchment-external landscape features, such as the unfrozen groundwater system below the permafrost and the nearby continental-scale ice sheet

Seabird surveillance: combining CCTV and artificial intelligence for monitoring and research

Ecological research and monitoring need to be able to rapidly convey information that can form the basis of scientifically sound management. Automated sensor systems, especially if combined with artificial intelligence, can contribute to such rapid high-resolution data retrieval. Here, we explore the prospects of automated methods to generate insights for seabirds, which are often monitored for their high conservation value and for being sentinels for marine ecosystem changes. We have developed a system of video surveillance combined with automated image processing, which we apply to common murres Uria aalge. The system uses a deep learning algorithm for object detection (YOLOv5) that has been trained on annotated images of adult birds, chicks and eggs, and outputs time, location, size and confidence level of all detections, frame-by-frame, in the supplied video material. A total of 144 million bird detections were generated from a breeding cliff over three complete breeding seasons (2019–2021). We demonstrate how object detection can be used to accurately monitor breeding phenology and chick growth. Our automated monitoring approach can also identify and quantify rare events that are easily missed in traditional monitoring, such as disturbances from predators. Further, combining automated video analysis with continuous measurements from a temperature logger allows us to study impacts of heat waves on nest attendance in high detail. Our automated system thus produces comparable, and in several cases significantly more detailed, data than those generated from observational field studies. By running in real time on the camera streams, it has the potential to supply researchers and managers with high-resolution up-to-date information on seabird population status. We describe how the system can be modified to fit various types of ecological research and monitoring goals and thereby provide up-to-date support for conservation and ecosystem management

Analysis of transcript and protein overlap in a human osteosarcoma cell line

<p>Abstract</p> <p>Background</p> <p>An interesting field of research in genomics and proteomics is to compare the overlap between the transcriptome and the proteome. Recently, the tools to analyse gene and protein expression on a whole-genome scale have been improved, including the availability of the new generation sequencing instruments and high-throughput antibody-based methods to analyze the presence and localization of proteins. In this study, we used massive transcriptome sequencing (RNA-seq) to investigate the transcriptome of a human osteosarcoma cell line and compared the expression levels with <it>in situ </it>protein data obtained in-situ from antibody-based immunohistochemistry (IHC) and immunofluorescence microscopy (IF).</p> <p>Results</p> <p>A large-scale analysis based on 2749 genes was performed, corresponding to approximately 13% of the protein coding genes in the human genome. We found the presence of both RNA and proteins to a large fraction of the analyzed genes with 60% of the analyzed human genes detected by all three methods. Only 34 genes (1.2%) were not detected on the transcriptional or protein level with any method. Our data suggest that the majority of the human genes are expressed at detectable transcript or protein levels in this cell line. Since the reliability of antibodies depends on possible cross-reactivity, we compared the RNA and protein data using antibodies with different reliability scores based on various criteria, including Western blot analysis. Gene products detected in all three platforms generally have good antibody validation scores, while those detected only by antibodies, but not by RNA sequencing, generally consist of more low-scoring antibodies.</p> <p>Conclusion</p> <p>This suggests that some antibodies are staining the cells in an unspecific manner, and that assessment of transcript presence by RNA-seq can provide guidance for validation of the corresponding antibodies.</p