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Controversy over the plate tectonic affinity and evolution of the Saxon granulites in a two- or multi-plate setting during inter- or intracontinental collision makes the Saxon Granulite Massif a key area for the understanding of the Palaeozoic Variscan orogeny. The massif is a large dome structure in which tectonic slivers of metapelite and metaophiolite units occur along a shear zone separating a diapir-like body of high-Pgranulite below from low-Pmetasedimentary rocks above. Each of the upper structural units records a different metamorphic evolution until its assembly with the exhuming granulite body. New age and petrologic data suggest that the metaophiolites developed from early Cambrian protoliths during high-Pamphibolite facies metamorphism in the mid- to late-Devonian and thermal overprinting by the exhuming hot granulite body in the early Carboniferous. A correlation of new Ar-Ar biotite ages with publishedP-T-tdata for the granulites implies that exhumation and cooling of the granulite body occurred at average rates of similar to 8 mm/year and similar to 80 degrees C/Ma, with a drop in exhumation rate from similar to 20 to similar to 2.5 mm/year and a slight rise in cooling rate between early and late stages of exhumation. A time lag ofc. 2 Ma between cooling through the closure temperatures for argon diffusion in hornblende and biotite indicates a cooling rate of 90 degrees C/Ma when all units had assembled into the massif. A two-plate model of the Variscan orogeny in which the above evolution is related to a short-lived intra-Gondwana subduction zone conflicts with the oceanic affinity of the metaophiolites and the timescale ofc. 50 Ma for the metamorphism. Alternative models focusing on the internal Variscan belt assume distinctly different material paths through the lower or upper crust for strikingly similar granulite massifs. An earlier proposed model of bilateral subduction below the internal Variscan belt may solve this problem.
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel patterns and the source of controversy in a general hypothesis. We apply a decision tree algorithm, assuming that evidence from various contexts can be adequately integrated in a hierarchically nested structure. As a case study, we analyzed 163 articles that studied a prominent hypothesis in invasion biology, the enemy release hypothesis. We explored if any of the nine attributes that classify each study can differentiate conclusions as classification problem. Results corroborated that machine learning can be useful for research synthesis, as the algorithm could detect patterns that had been already focused in previous narrative reviews. Compared with the previous synthesis study that assessed the same evidence collection based on experts' judgement, the algorithm has newly proposed that the studies focusing on Asian regions mostly supported the hypothesis, suggesting that more detailed investigations in these regions can enhance our understanding of the hypothesis. We suggest that machine learning algorithms can be a promising synthesis tool especially where studies (a) reformulate a general hypothesis from different perspectives, (b) use different methods or variables, or (c) report insufficient information for conducting meta-analyses.
Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances
This study is the first to use kinematic data to assess lingual carryover coarticulation in children. We investigated whether the developmental decrease previously attested in anticipatory coarticulation, as well as the relation between coarticulatory degree and the consonantal context, also characterize carryover coarticulation. Sixty-two children and 13 adults, all native speakers of German, were recruited according to five age cohorts: three-year-olds, four-year-olds, five-year-olds, seven-year-olds, and adults. Tongue movements during the production of ə.CV.Cə utterances (C = /b, d, g/, V = /i, y, e, a, o, u/) were recorded with ultrasound. We measured vowel-induced horizontal displacement of the tongue dorsum within the last syllable and compared the resulting coarticulatory patterns between age cohorts and consonantal contexts. Results indicate that the degree of vocalic carryover coarticulation decreases with age. Vocalic prominence within an utterance as well as its change across childhood depended on the postvocalic consonant’s articulatory demands for the tongue dorsum (i.e., its coarticulatory resistance): Low resistant /b/ and /g/ allowed for more vocalic perseveration and a continuous decrease, while the highly resistant /d/ displayed lower coarticulation degrees and discontinuous effects. These findings parallel those in anticipation suggesting a similar organization of anticipatory and carryover coarticulation. Implications for theories of speech production are discussed.
Recent climatic changes have the potential to severely alter river runoff, particularly in snow-dominated river basins. Effects of changing snow covers superimpose with changes in precipitation and anthropogenic modifications of the watershed and river network. In the attempt to identify and disentangle long-term effects of different mechanisms, we employ a set of analytical tools to extract long-term changes in river runoff at high resolution. We combine quantile sampling with moving average trend statistics and empirical mode decomposition and apply these tools to discharge data recorded along rivers with nival, pluvial and mixed flow regimes as well as temperature and precipitation data covering the time frame 1869-2016. With a focus on central Europe, we analyse the long-term impact of snow cover and precipitation changes along with their interaction with reservoir constructions.
Our results show that runoff seasonality of snow-dominated rivers decreases. Runoff increases in winter and spring, while discharge decreases in summer and at the beginning of autumn. We attribute this redistribution of annual flow mainly to reservoir constructions in the Alpine ridge. During the course of the last century, large fractions of the Alpine rivers were dammed to produce hydropower. In recent decades, runoff changes induced by reservoir constructions seem to overlap with changes in snow cover. We suggest that Alpine signals propagate downstream and affect runoff far outside the Alpine area in river segments with mixed flow regimes. Furthermore, our results hint at more (intense) rain-fall in recent decades. Detected increases in high discharge can be traced back to corresponding changes in precipitation.
Global biodiversity is under high and rising anthropogenic pressure. Yet, how the taxonomic, phylogenetic, and functional facets of biodiversity are affected by different threats over time is unclear. This is particularly true for the two main drivers of the current biodiversity crisis: habitat destruction and overexploitation. We provide the first long-term assessment of multifaceted biodiversity changes caused by these threats for any tropical region. Focussing on larger mammals in South America's 1.1 million km(2) Gran Chaco region, we assessed changes in multiple biodiversity facets between 1985 and 2015, determined which threats drive those changes, and identified remaining key areas for all biodiversity facets. Using habitat and threat maps, we found, first, that between 1985 and 2015 taxonomic (TD), phylogenetic (PD) and functional (FD) diversity all declined drastically across over half of the area assessed. FD declined about 50% faster than TD and PD, and these declines were mainly driven by species loss, rather than species turnover. Second, habitat destruction, hunting, and both threats together contributed similar to 57%, similar to 37%, and similar to 6% to overall facet declines, respectively. However, hunting pressure increased where TD and PD declined most strongly, whereas habitat destruction disproportionally contributed to FD declines. Third, just 23% of the Chaco would have to be protected to safeguard the top 17% of all three facets. Our findings uncover a widespread impoverishment of mammal species richness, evolutionary history, and ecological functions across broad areas of the Chaco due to increasing habitat destruction and hunting. Moreover, our results pinpoint key areas that should be preserved and managed to maintain all facets of mammalian diversity across the Chaco. More generally, our work highlights how long-term changes in biodiversity facets can be assessed and attributed to specific threats, to better understand human impacts on biodiversity and to guide conservation planning to mitigate them.
Deep waters represent the largest biome on Earth and the largest ecosystem of Costa Rica. Fungi play a fundamental role in global biogeochemical cycling in marine sediments, yet, they remain little explored. We studied fungal diversity and community composition in several marine sediments from 16 locations sampled along a bathymetric gradient (from a depth of 380 to 3,474 m) in two transects of about 1,500 km length in the Eastern Tropical Pacific (ETP) of Costa Rica. Sequence analysis of the V7-V8 region of the 18S rRNA gene obtained from sediment cores revealed the presence of 787 fungal amplicon sequence variants (ASVs). On average, we detected a richness of 75 fungal ASVs per sample. Ascomycota represented the most abundant phylum with Saccharomycetes constituting the dominant class. Three ASVs accounted for ca. 63% of all fungal sequences: the yeast Metschnikowia (49.4%), Rhizophydium (6.9%), and Cladosporium (6.7%). We distinguished a cluster composed mainly by yeasts, and a second cluster by filamentous fungi, but we were unable to detect a strong effect of depth and the overlying water temperature, salinity, dissolved oxygen (DO), and pH on the composition of fungal communities. We highlight the need to understand further the ecological role of fungi in deep-sea ecosystems.
The southern Central Andes (SCA) (between 27 degrees S and 40 degrees S) is bordered to the west by the convergent margin between the continental South American Plate and the oceanic Nazca Plate. The subduction angle along this margin is variable, as is the deformation of the upper plate. Between 33 degrees S and 35 degrees S, the subduction angle of the Nazca plate increases from sub-horizontal (< 5 degrees) in the north to relatively steep (similar to 30 degrees) in the south. The SCA contain inherited lithological and structural heterogeneities within the crust that have been reactivated and overprinted since the onset of subduction and associated Cenozoic deformation within the Andean orogen. The distribution of the deformation within the SCA has often been attributed to the variations in the subduction angle and the reactivation of these inherited heterogeneities. However, the possible influence that the thickness and composition of the continental crust have had on both short-term and long-term deformation of the SCA is yet to be thoroughly investigated. For our investigations, we have derived density distributions and thicknesses for various layers that make up the lithosphere and evaluated their relationships with tectonic events that occurred over the history of the Andean orogeny and, in particular, investigated the short- and long-term nature of the present-day deformation processes. We established a 3D model of lithosphere beneath the orogen and its foreland (29 degrees S-39 degrees S) that is consistent with currently available geological and geophysical data, including the gravity data. The modelled crustal configuration and density distribution reveal spatial relationships with different tectonic domains: the crystalline crust in the orogen (the magmatic arc and the main orogenic wedge) is thicker (similar to 55 km) and less dense (similar to 2900 kg/m(3)) than in the forearc (similar to 35 km, similar to 2975 kg/m(3)) and foreland (similar to 30 km, similar to 3000 kg/m(3)). Crustal thickening in the orogen probably occurred as a result of stacking of low-density domains, while density and thickness variations beneath the forearc and foreland most likely reflect differences in the tectonic evolution of each area following crustal accretion. No clear spatial relationship exists between the density distribution within the lithosphere and previously proposed boundaries of crustal terranes accreted during the early Paleozoic. Areas with ongoing deformation show a spatial correlation with those areas that have the highest topographic gradients and where there are abrupt changes in the average crustal-density contrast. This suggests that the short-term deformation within the interior of the Andean orogen and its foreland is fundamentally influenced by the crustal composition and the relative thickness of different crustal layers. A thicker, denser, and potentially stronger lithosphere beneath the northern part of the SCA foreland is interpreted to have favoured a strong coupling between the Nazca and South American plates, facilitating the development of a sub-horizontal slab.
One of the most important social cognitive skills in humans is the ability to “put oneself in someone else’s shoes,” that is, to take another person’s perspective. In socially situated communication, perspective taking enables the listener to arrive at a meaningful interpretation of what is said (sentence meaning) and what is meant (speaker’s meaning) by the speaker. To successfully decode the speaker’s meaning, the listener has to take into account which information he/she and the speaker share in their common ground (CG). We here further investigated competing accounts about when and how CG information affects language comprehension by means of reaction time (RT) measures, accuracy data, event-related potentials (ERPs), and eye-tracking. Early integration accounts would predict that CG information is considered immediately and would hence not expect to find costs of CG integration. Late integration accounts would predict a rather late and effortful integration of CG information during the parsing process that might be reflected in integration or updating costs. Other accounts predict the simultaneous integration of privileged ground (PG) and CG perspectives. We used a computerized version of the referential communication game with object triplets of different sizes presented visually in CG or PG. In critical trials (i.e., conflict trials), CG information had to be integrated while privileged information had to be suppressed. Listeners mastered the integration of CG (response accuracy 99.8%). Yet, slower RTs, and enhanced late positivities in the ERPs showed that CG integration had its costs. Moreover, eye-tracking data indicated an early anticipation of referents in CG but an inability to suppress looks to the privileged competitor, resulting in later and longer looks to targets in those trials, in which CG information had to be considered. Our data therefore support accounts that foresee an early anticipation of referents to be in CG but a rather late and effortful integration if conflicting information has to be processed. We show that both perspectives, PG and CG, contribute to socially situated language processing and discuss the data with reference to theoretical accounts and recent findings on the use of CG information for reference resolution.
The demand for peer-to-peer ridesharing services increased over the last years rapidly. To cost-efficiently dispatch orders and communicate accurate pick-up times is challenging as the current location of each available driver is not exactly known since observed locations can be outdated for several seconds. The developed trajectory visualization tool enables transportation network companies to analyze dispatch processes and determine the causes of unexpected delays. As dispatching algorithms are based on the accuracy of arrival time predictions, we account for factors like noise, sample rate, technical and economic limitations as well as the duration of the entire process as they have an impact on the accuracy of spatio-temporal data. To improve dispatching strategies, we propose a prediction approach that provides a probability distribution for a driver’s future locations based on patterns observed in past trajectories. We demonstrate the capabilities of our prediction results to ( i) avoid critical delays, (ii) to estimate waiting times with higher confidence, and (iii) to enable risk considerations in dispatching strategies.