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Primary determinants of communities in deadwood vary among taxa but are regionally consistent
(2020)
The evolutionary split between gymnosperms and angiosperms has far‐reaching implications for the current communities colonizing trees. The inherent characteristics of dead wood include its role as a spatially scattered habitat of plant tissue, transient in time. Thus, local assemblages in deadwood forming a food web in a necrobiome should be affected not only by dispersal ability but also by host tree identity, the decay stage and local abiotic conditions. However, experiments simultaneously manipulating these potential community drivers in deadwood are lacking. To disentangle the importance of spatial distance and microclimate, as well as host identity and decay stage as drivers of local assemblages, we conducted two consecutive experiments, a 2‐tree species and 6‐tree species experiment with 80 and 72 tree logs, respectively, located in canopy openings and under closed canopies of a montane and a lowland forest. We sampled saproxylic beetles, spiders, fungi and bacterial assemblages from logs. Variation partitioning for community metrics based on a unified framework of Hill numbers showed consistent results for both studies: host identity was most important for sporocarp‐detected fungal assemblages, decay stage and host tree for DNA‐detected fungal assemblages, microclimate and decay stage for beetles and spiders and decay stage for bacteria. Spatial distance was of minor importance for most taxa but showed the strongest effects for arthropods. The contrasting patterns among the taxa highlight the need for multi‐taxon analyses in identifying the importance of abiotic and biotic drivers of community composition. Moreover, the consistent finding of microclimate as the primary driver for saproxylic beetles compared to host identity shows, for the first time that existing evolutionary host adaptions can be outcompeted by local climate conditions in deadwood.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Exploring biophysical properties of virus-encoded components and their requirement for virus replication is an exciting new area of interdisciplinary virological research. To date, spatial resolution has only rarely been analyzed in computational/biophysical descriptions of virus replication dynamics. However, it is widely acknowledged that intracellular spatial dependence is a crucial component of virus life cycles. The hepatitis C virus-encoded NS5A protein is an endoplasmatic reticulum (ER)-anchored viral protein and an essential component of the virus replication machinery. Therefore, we simulate NS5A dynamics on realistic reconstructed, curved ER surfaces by means of surface partial differential equations (sPDE) upon unstructured grids. We match the in silico NS5A diffusion constant such that the NS5A sPDE simulation data reproduce experimental NS5A fluorescence recovery after photobleaching (FRAP) time series data. This parameter estimation yields the NS5A diffusion constant. Such parameters are needed for spatial models of HCV dynamics, which we are developing in parallel but remain qualitative at this stage. Thus, our present study likely provides the first quantitative biophysical description of the movement of a viral component. Our spatio-temporal resolved ansatz paves new ways for understanding intricate spatial-defined processes central to specfic aspects of virus life cycles.
Extinction of fear responses is critical for adaptive behavior and deficits in this form of safety learning are hallmark of anxiety disorders. However, the neuronal mechanisms that initiate extinction learning are largely unknown. Here we show, using single-unit electrophysiology and cell-type specific fiber photometry, that dopamine neurons in the ventral tegmental area (VTA) are activated by the omission of the aversive unconditioned stimulus (US) during fear extinction. This dopamine signal occurred specifically during the beginning of extinction when the US omission is unexpected, and correlated strongly with extinction learning. Furthermore, temporally-specific optogenetic inhibition or excitation of dopamine neurons at the time of the US omission revealed that this dopamine signal is both necessary for, and sufficient to accelerate, normal fear extinction learning. These results identify a prediction error-like neuronal signal that is necessary to initiate fear extinction and reveal a crucial role of DA neurons in this form of safety learning.
Synthesis, crystal structure and structure–property relations of strontium orthocarbonate, Sr2CO4
(2021)
Carbonates containing CO4 groups as building blocks have recently been discovered. A new orthocarbonate, Sr2CO4 is synthesized at 92 GPa and at a temperature of 2500 K. Its crystal structure was determined by in situ synchrotron single-crystal X-ray diffraction, selecting a grain from a polycrystalline sample. Strontium orthocarbonate crystallizes in the orthorhombic crystal system (space group Pnma) with CO4, SrO9 and SrO11 polyhedra as the main building blocks. It is isostructural to Ca2CO4. DFT calculations reproduce the experimental findings very well and have, therefore, been used to predict the equation of state, Raman and IR spectra, and to assist in the discussion of bonding in this compound.
The CLOUD (Cosmics Leaving OUtdoor Droplets) experiment at CERN is studying the nucleation and growth of aerosol particles under atmospheric conditions, and their activation into cloud droplets. A key feature of the CLOUD experiment is precise control of the experimental parameters. Temperature uniformity and stability in the chamber are important since many of the processes under study are sensitive to temperature and also to contaminants that can be released from the stainless steel walls by upward temperature fluctuations. The air enclosed within the 3 m CLOUD chamber is equipped with several arrays (strings) of high precision, fast-response thermometers to measure its temperature. Here we present a study of the air temperature uniformity inside the CLOUD chamber under various experimental conditions. Measurements were performed under calibration conditions and run conditions, which are distinguished by the flow rate of fresh air and trace gases entering the chamber: 20 l/min and up to 210 l/min, respectively. During steady-state calibration runs between −70 °C and +20 °C, the air temperature uniformity is better than +/−0.06 °C in the radial direction and +/−0.1 °C in the vertical direction. Larger non-uniformities are present during experimental runs, depending on the temperature control of the make-up air and trace gases (since some trace gases require elevated temperatures until injection into the chamber). The temperature stability is a few times 0.01 °C over periods of several hours during either calibration or steady-state run conditions. During rapid adiabatic expansions to activate cloud droplets and ice particles, the chamber walls are up to 10 °C warmer than the enclosed air. This results in larger non-uniformities while the air returns to its equilibrium temperature with time constant of about 200 s.
The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.
The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.
Atmospheric aerosols and their effect on clouds are thought to be important for anthropogenic radiative forcing of the climate, yet remain poorly understood1. Globally, around half of cloud condensation nuclei originate from nucleation of atmospheric vapours2. It is thought that sulfuric acid is essential to initiate most particle formation in the atmosphere3,4, and that ions have a relatively minor role5. Some laboratory studies, however, have reported organic particle formation without the intentional addition of sulfuric acid, although contamination could not be excluded6,7. Here we present evidence for the formation of aerosol particles from highly oxidized biogenic vapours in the absence of sulfuric acid in a large chamber under atmospheric conditions. The highly oxygenated molecules (HOMs) are produced by ozonolysis of α-pinene. We find that ions from Galactic cosmic rays increase the nucleation rate by one to two orders of magnitude compared with neutral nucleation. Our experimental findings are supported by quantum chemical calculations of the cluster binding energies of representative HOMs. Ion-induced nucleation of pure organic particles constitutes a potentially widespread source of aerosol particles in terrestrial environments with low sulfuric acid pollution.