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Funder: Bavarian Climate Research Network (BayKliF), Funder: Gutenberg Research College; Id: http://dx.doi.org/10.13039/501100004812, Dendroclimatology offers the unique opportunity to reconstruct past climate at annual resolution and wood from historical buildings can be used to extend such information back in time up to several millennia. However, the varying and often unclear origin of timbers affects the climate sensitivity of individual tree‐ring samples. Here, we compare tree‐ring width and density of 143 living larch (Larix decidua Mill.) trees at seven sites along an elevational transect from 1400 to 2200 m asl and 99 historical tree‐ring series to parametrize state‐of‐the‐art classification models for the European Alps. To achieve geographical provenance of the historical series, nine different supervised machine learning algorithms are trained and tested in their capability to solve our classification problem. Based on this assessment, we consider a tree‐ring density‐based and a tree‐ring width‐based dataset for model building. For each of these datasets, a general not species‐related model and a larch‐specific model including the cyclic larch budmoth influence are built. From the nine tested machine learning algorithms, Extreme Gradient Boosting showed the best performance. The density‐based models outperform the ring‐width models with the larch‐specific density model reaching the highest skill (f1 score = 0.8). The performance metrics reveal that the larch‐specific density model also performs best within individual sites and particularly in sites above 2000 m asl, which show the highest temperature sensitivities. The application of the specific density model for larch allows the historical series to be assigned with high confidence to a particular elevation within the valley. The procedure can be applied to other provenance studies using multiple tree growth characteristics. The novel approach of building machine learning models based on tree‐ring density features allows to omit a common period between reference and historical data for finding the provenance of relict wood and will therefore help to improve millennium‐length climate reconstructions.

Currently, numerous physician practices in industrial and emerging countries are being taken over by private equity firms and integrated into novel physician corporations. This involves private equity firms producing a global wealth chain (GWC) between their investors and the target asset, using offshore financial centres to facilitate tax-avoiding reflux of capital. Moreover, they are opening up ambulatory health care as an asset for capital investment by overcoming previous market barriers to ambulatory health care via a legal construct. In this paper, we trace the spatial links of these finance-side and sector-specific corporate chains based on a capital flow analysis of private equity takeovers of Medical Care Centres (MCCs) in Bavaria, Germany. With our heuristics of a double-layered GWC, which enables the extraction of value from the German health system, we contribute to the emerging GWC debate that aims to conceptualise the complex and often opaque spatialisations of financialisation processes.

Crisis management is often conceived from the position of an omniscient narrator, albeit the general consensus that crises are subjectively interpreted and experienced. The paper makes an analytical attempt to de-homogenize the notion of crisis. We argue that the perception of crises differs and present a spatial perspective on crisis to foreground the positionality of different actor groups. By referring to the EHEC outbreak 2011 in Germany, we explore two spatial configurations that seem to be of particular relevance: territories embedded in a nested hierarchy and topologies of interconnected places. State authorities think and act strongly in terms of territorial borders and along sectoral boundaries. From their point of view, the crisis tends to be threatening due to its "transboundary" character. Medical experts, in contrast, coped with the crisis in trans-local networks of colleagues. For this group, the crisis was also an opportunity to substantially enhance professional knowledge.

Social, burrowing mammals such as prairie dogs, ground squirrels or marmots are keystone species in grassland ecosystems. Grasslands have been converted into cropland or pastures globally, yet it remains virtually unknown how this has affected the biogeography of burrowing mammals, as efficient, broad-scale survey methods are lacking. We aimed to test whether structures created by burrowing rodents can be reliably detected on publicly available, very-high-resolution satellite images, in order to assess rodent distribution and abundance. We identified burrows of Bobak marmot (Marmota bobak), a keystone burrowing steppe rodent, on 1300 randomly selected plots of 1 km diameter (78.53 ha) across the species’ range (~950 000 km²) in Kazakhstan and southern Russia using Google Earth and Bing images. We then used burrow occurrences and species distribution models to map marmot distribution. We assessed how marmot occurrence and density vary across land-use types. We also combined satellite-based burrow densities and ground-survey data to derive a new population estimate for the species across Kazakhstan. We mapped a total of 7425 burrows from the satellite imagery. Field visits at a subsample of burrows suggested that burrow occurrence was detected reliably. Broad-scale marmot distribution was mainly determined by summer rainfall, land use and elevation. Occurrence probability was highest on arable croplands, followed by abandoned croplands and grazed steppe. The current Bobak marmot population size for Kazakhstan was estimated at 6.1 (±2.4) million individuals. Our results demonstrate that publicly available, very-high-resolution images can be used to reliably map the distribution of burrowing mammals across large geographic scales. The observed and predicted distributions indicate that the Bobak's range has remained almost unchanged in Kazakhstan since the 1950s, despite several drastic episode of land-use change. This suggests that burrowing mammals can be remarkably resilient to land-use pressure, questioning prevailing narratives of population collapse in these species following agricultural expansion., Finanziert über die DEAL-Vereinbarung mit Wiley 2019-2022.

Prediction of stable mineral equilibria in the Earth’s lithosphere is critical to un-ravel the tectonomagmatic history of exposed geological sections. While the recent ad-vances in geodynamic modelling allow us to explore the dynamics of magmatic trans-fer in solid mediums, there is to date no available thermodynamic package that can eas-ily be linked and efficiently accounts for the computation of phase equilibrium in mag-matic systems. Moreover, none of the existing tools fully exploit single point calculationparallelization which strongly hinders their applicability for direct geodynamic couplingor for thermodynamic database inversions. Here, we present a new Mineral AssemblageGibbs Energy Minimizer (magemin). The package is written as a parallel C library, pro-vides a direct Julia interface and is callable from any petrological/geodynamic tool. Fora given set of pressure, temperature and bulk-rock composition magemin uses a com-bination of linear programming, extended Partitioning Gibbs Energy and gradient-basedlocal minimization to compute the stable mineral assemblage. We apply our new min-imization package to the igneous thermodynamic dataset of (Holland et al., 2018) andproduce several phase diagrams at supra-solidus conditions. The phase diagrams are thendirectly benchmarked against thermocalc and exhibit very good agreement. The highscalability of magemin on parallel computing facilities opens new horizons e.g., for mod-elling reactive magma flow, for thermodynamic dataset inversion and for petrological/geophysicalapplications.

In ad 1362, a major storm surge drowned wide areas of cultivated medieval marshland along the north‐western coast of Germany and turned them into tidal flats. This study presents a new methodological approach for the reconstruction of changing coastal landscapes developed from a study site in the Wadden Sea of North Frisia. Initially, we deciphered long‐term as well as event‐related short‐term geomorphological changes, using a geoscientific standard approach of vibracoring, analyses of sedimentary, geochemical and microfaunal palaeoenvironmental parameters and radiocarbon dating. In a next step, Direct Push (DP)‐based Cone Penetration Testing (CPT) and the Hydraulic Profiling Tool (HPT) were applied at vibracore locations to obtain in situ high‐resolution stratigraphic data. In a last step, multivariate linear discriminant analysis (LDA) was successfully applied to efficiently identify different sedimentary facies (e.g., fossil marsh or tidal flat deposits) from the CPT and HPT test dataset, to map the facies' lateral distribution, also in comparison to reflection seismic measurements and test their potential to interpolate the borehole and CPT/HPT data. The training dataset acquired for the key site from coring and DP sensing finally allows an automated facies classification of CPT/HPT data obtained elsewhere within the study area. The new methodological approach allowed a detailed reconstruction of the local coastal landscape development in the interplay of natural marsh formation, medieval land reclamation and storm surge‐related land losses., Presenting a new approach of automated facies identification based on palaeoenvironmental parameter (PEP) analyses of vibracores, Direct Push‐based Cone Penetration Testing (CPT) and the Hydraulic Profiling Tool (HPT) sensing data, linear discriminant analysis (LDA) and seismic measurements, gradual as well as extreme landscape changes associated with major storm surges in ad 1362 and ad 1634 are reconstructed for a study area in the Wadden Sea of North Frisia (Germany). image, Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, Research Foundation http://dx.doi.org/10.13039/100005930

The in situ measurement of Sr isotopes in carbonates by MC‐ICP‐MS is limited by the availability of suitable microanalytical reference materials (RMs), which match the samples of interest. Whereas several well‐characterised carbonate reference materials for Sr mass fractions > 1000 µg g−1 are available, there is a lack of well‐characterised carbonate microanalytical RMs with lower Sr mass fractions. Here, we present a new synthetic carbonate nanopowder RM with a Sr mass fraction of ca. 500 µg g−1 suitable for microanalytical Sr isotope research (‘NanoSr’). NanoSr was analysed by both solution‐based and in situ techniques. Element mass fractions were determined using EPMA (Ca mass fraction), as well as laser ablation and solution ICP‐MS in different laboratories. The 87Sr/86Sr ratio was determined by well‐established bulk methods for Sr isotope measurements and is 0.70756 ± 0.00003 (2s). The Sr isotope microhomogeneity of the material was determined by LA‐MC‐ICP‐MS, which resulted in 87Sr/86Sr ratios of 0.70753 ± 0.00007 (2s) and 0.70757 ± 0.00006 (2s), respectively, in agreement with the solution data within uncertainties. Thus, this new reference material is well suited to monitor and correct microanalytical Sr isotope measurements of low‐Sr, low‐REE carbonate samples. NanoSr is available from the corresponding author., Geostandards and Geoanalytical Research, 44 (1), ISSN:1639-4488, ISSN:1751-908X