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The determination of the spin state of iron-bearing compounds at high pressure and temperature is crucial for our understanding of chemical and physical properties of the deep Earth. Studies on the relationship between the coordination of iron and its electronic spin structure in iron-bearing oxides, silicates, carbonates, iron alloys, and other minerals found in the Earth's mantle and core are scarce because of the technical challenges to simultaneously probe the sample at high pressures and temperatures. We used the unique properties of a pulsed and highly brilliant x-ray free electron laser (XFEL) beam at the High Energy Density (HED) instrument of the European XFEL to x-ray heat and probe samples contained in a diamond anvil cell. We heated and probed with the same x-ray pulse train and simultaneously measured x-ray emission and x-ray diffraction of an FeCO3 sample at a pressure of 51 GPa with up to melting temperatures. We collected spin state sensitive Fe K beta(1,3) fluorescence spectra and detected the sample's structural changes via diffraction, observing the inverse volume collapse across the spin transition. During x-ray heating, the carbonate transforms into orthorhombic Fe4C3O12 and iron oxides. Incipient melting was also observed. This approach to collect information about the electronic state and structural changes from samples contained in a diamond anvil cell at melting temperatures and above will considerably improve our understanding of the structure and dynamics of planetary and exoplanetary interiors.
Early detection of salt stress is vital for plant survival and growth. Still, the molecular processes controlling early salt stress perception and signaling are not fully understood. Here, we identified SALT-RESPONSIVE ERF1 (SERF1), a rice (Oryza sativa) transcription factor (TF) gene that shows a root-specific induction upon salt and hydrogen peroxide (H2O2) treatment. Loss of SERF1 impairs the salt-inducible expression of genes encoding members of a mitogen-activated protein kinase (MAPK) cascade and salt tolerance-mediating TFs. Furthermore, we show that SERF1-dependent genes are H2O2 responsive and demonstrate that SERF1 binds to the promoters of MAPK KINASE KINASE6 (MAP3K6), MAPK5, DEHYDRATION-RESPONSIVE ELEMENT BINDING2A (DREB2A), and ZINC FINGER PROTEIN179 (ZFP179) in vitro and in vivo. SERF1 also directly induces its own gene expression. In addition, SERF1 is a phosphorylation target of MAPK5, resulting in enhanced transcriptional activity of SERF1 toward its direct target genes. In agreement, plants deficient for SERF1 are more sensitive to salt stress compared with the wild type, while constitutive overexpression of SERF1 improves salinity tolerance. We propose that SERF1 amplifies the reactive oxygen species-activated MAPK cascade signal during the initial phase of salt stress and translates the salt-induced signal into an appropriate expressional response resulting in salt tolerance.
Growth regulation is an important aspect of plant adaptation during environmental perturbations. Here, the role of MULTIPASS (OsMPS), an R2R3-type MYB transcription factor of rice, was explored. OsMPS is induced by salt stress and expressed in vegetative and reproductive tissues. Over-expression of OsMPS reduces growth under non-stress conditions, while knockdown plants display increased biomass. OsMPS expression is induced by abscisic acid and cytokinin, but is repressed by auxin, gibberellin and brassinolide. Growth retardation caused by OsMPS over-expression is partially restored by auxin application. Expression profiling revealed that OsMPS negatively regulates the expression of EXPANSIN (EXP) and cell-wall biosynthesis as well as phytohormone signaling genes. Furthermore, the expression of OsMPS-dependent genes is regulated by auxin, cytokinin and abscisic acid. Moreover, we show that OsMPS is a direct upstream regulator of OsEXPA4, OsEXPA8, OsEXPB2, OsEXPB3, OsEXPB6 and the endoglucanase genes OsGLU5 and OsGLU14. The multiple responses of OsMPS and its target genes to various hormones suggest an integrative function of OsMPS in the cross-talk between phytohormones and the environment to regulate adaptive growth.
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
Larix species range dynamics in Siberia since the Last Glacial captured from sedimentary ancient DNA
(2022)
Climate change is expected to cause major shifts in boreal forests which are in vast areas of Siberia dominated by two species of the deciduous needle tree larch (Larix). The species differ markedly in their ecosystem functions, thus shifts in their respective ranges are of global relevance.
However, drivers of species distribution are not well understood, in part because paleoecological data at species level are lacking. This study tracks Larix species distribution in time and space using target enrichment on sedimentary ancient DNA extracts from eight lakes across Siberia. We discovered that Larix sibirica, presently dominating in western Siberia, likely migrated to its northern distribution area only in the Holocene at around 10,000 years before present (ka BP), and had a much wider eastern distribution around 33 ka BP. Samples dated to the Last Glacial Maximum (around 21 ka BP), consistently show genotypes of L. gmelinii.
Our results suggest climate as a strong determinant of species distribution in Larix and provide temporal and spatial data for species projection in a changing climate.
Using ancient sedimentary DNA from up to 50 kya, dramatic distributional shifts are documented in two dominant boreal larch species, likely guided by environmental changes suggesting climate as a strong determinant of species distribution.