Spatial Extent Research Articles

The spatial development of tourism over eight decades: a Horizon 2050 paper

Purpose The purpose of this paper is to show the spatial extent and growth of tourism and its likely patterns as past forces of change are replaced by new pressures to reduce climate change and meet new definitions of success. Design/methodology/approach The approach involves a review of changes that have occurred over the Horizon period with a focus on the spatial spread and development of tourism, using and based on a literature review, past research and personal experience. Likely new developments are identified based on the expected result of influences including climate change mitigation and altered understandings of what is meant by success in tourism. Findings Much of the spatial change in tourism has been evolutionary rather than revolutionary, but in the future, restrictive forces external to tourism may change travel patterns with severe effects on long haul travel and a change in travel mode. Research limitations/implications The research focus needs to produce effective measures of success as understood by all stakeholders in tourist destinations. Alternative destinations will need to replace those long haul destinations no longer available and research needs to refocus on managing rather than solely attracting visitors. Practical implications Long haul destinations will lose market share, destinations will change goals to satisfaction for stakeholders and travel modes will change to lower emission generators. Social implications Destination choice will be reduced, transport modes may be limited and tourism closer to home will become the norm. Originality/value A general overview of this type has not been presented before.

Future changes in spatially compounding hot, wet or dry events and their implications for the world’s breadbasket regions

Recent years were characterized by an increase in spatially co-occurring hot, wet or dry extreme events around the globe. In this study we analyze data from multi-model climate projections to analyze the occurrence of spatially compounding events and area affected in future climates under scenarios at +1.5 ∘C, +2.0 ∘C, +3.0 ∘C and higher levels of global warming using Earth System Model simulations from the 6th Phase of the Coupled Model Intercomparison Project. Since spatially compounding extreme events can strongly amplify societal impacts as economic supply chains are increasingly interdependent, we want to highlight that the world’s breadbasket regions are projected to be particularly affected by an increase in spatially co-occurring hot, wet or dry extreme events, posing risks to the global food security. We show that the spatial extent of top-producing agricultural regions being potentially threatened by climate extremes will increase drastically if global mean temperatures shift from +1.5 ∘C to +2.0 ∘C. Further we identify a large increase in the projected global land area concurrently affected by hot, wet or dry extremes with increased global warming posing risk to other industries and sectors in addition to the agricultural sector.

Monitoring the impact of forest changes on carbon uptake with solar-induced fluorescence measurements from GOME-2A and TROPOMI for an Australian and Chinese case study

Abstract. Reliable and robust monitoring tools are crucial to assess the effectiveness of land mitigation techniques (LMTs) in enhancing carbon uptake, enabling informed decision making by policymakers. This study, addressing one of the scientific goals of the EU Horizon 2020 Land Use Based Mitigation for Resilient Climate Pathways (LANDMARC) project, examines the feasibility of using satellite solar-induced fluorescence (SIF) in combination with other satellite data as a monitoring proxy to evaluate the effects of LMTs on carbon uptake. Two distinct cases are explored: (1) instantaneous vegetation destruction caused by a 2019 eucalyptus wildfire in southeast Australia and (2) gradual forest gain resulting from reforestation efforts in northern China in 2007–2012. The cases are monitored using SIF from the TROPOspheric Monitoring Instrument (TROPOMI) and Global Ozone Monitoring Experiment-2A (GOME-2A), respectively. Comparing the temporal variability in SIF across the affected areas and nearby reference areas reveals that vegetation dynamics changed as a consequence of the land-use changes in both cases. Specifically, in the Australia case, TROPOMI demonstrated an immediate reduction in the SIF signal of 0.6 mW m−2 sr−1 nm−1 (−72 %) over the eucalypt forest right after the fire. Exploiting the strong correspondence between TROPOMI SIF and gross primary productivity (GPP) at the nearby representative eddy covariance Tumbarumba site and through the FluxSat product, we estimate that the Australian fire led to a loss in GPP of 130–200 GgC in the first 8 months after the fire. Over the northern Chinese provinces of Gansu, Shaanxi, Sichuan, Chongqing, and Shanxi, we report an increase in GOME-2A summertime SIF of 0.1–0.2 mW m−2 sr−1 nm−1, coinciding with reforestation efforts between 2007 and 2012. This increase in the SIF signal is likely driven by a combination of increasingly favourable natural conditions and by the reforestation effort itself. A multivariate model that takes into account growth factors such as water availability and maximum temperature as well as satellite-derived forest-cover data explains the observed variability in GOME-2A SIF in the Chinese case reasonably well (R2=0.72). The model suggests that increases in both forest cover and soil moisture have led, in step, to the observed increase in vegetation activity over northern China. In that region, for every 100 km2 of additional forest cover, SIF increases by 0.1 mW m−2 sr−1 nm−1 between 2007 and 2012. Our study highlights that the use of satellite-based SIF, together with supporting in situ, modelled, and satellite data, allows us to monitor the impact of LMT implementation on regional carbon uptake as long as the scale of the LMT is of sufficient spatial extent.

Rapid seagrass meadow expansion in an Indian Ocean bright spot

The areal extent of seagrass meadows is in rapid global decline, yet they provide highly valuable societal benefits. However, their conservation is hindered by data gaps on current and historic spatial extents. Here, we outline an approach for national-scale seagrass mapping and monitoring using an open-source platform (Google Earth Engine) and freely available satellite data (Landsat, Sentinel-2) that can be readily applied in other countries globally. Specifically, we map contemporary (2021) and historical (2000–2021; n = 10 maps) shallow water seagrass extent across the Maldives. We found contemporary Maldivian seagrass extent was ~ 105 km2 (overall accuracy = 82.04%) and, notably, that seagrass area increased threefold between 2000 and 2021 (linear model, + 4.6 km2 year−1, r2 = 0.93, p < 0.001). There was a strongly significant association between seagrass and anthropogenic activity (p < 0.001) that we hypothesize to be driven by nutrient loading and/or altered sediment dynamics (from large scale land reclamation), which would represent a beneficial anthropogenic influence on Maldivian seagrass meadows. National-scale tropical seagrass expansion is unique against the backdrop of global seagrass decline and we therefore highlight the Maldives as a rare global seagrass ‘bright spot’ highly worthy of increased attention across scientific, commercial, and conservation policy contexts.

Local environmental conditions structured discrete fish assemblages in Arctic lagoons

AbstractRapid changes in sea ice extent and changes in freshwater inputs from land are rapidly changing the nature of Arctic estuarine ecosystems. In the Beaufort Sea, these nearshore habitats are known for their high productivity and mix of marine resident and diadromous fishes that have great subsistence value for Indigenous communities. There is, however, a lack of information on the spatial variation among Arctic nearshore fish communities as related to environmental drivers. In summers of 2017–2019, we sampled fishes in four estuarine ecosystems to assess community composition and relate fish abundance to temperature, salinity, and wind conditions. We found fish communities were heterogeneous over larger spatial extents with rivers forming fresh estuarine plumes that supported diadromous species (e.g., broad whitefish Coregonus nasus), while lagoons with reduced freshwater input and higher salinities were associated with marine species (e.g., saffron cod Eleginus gracilis). West–East directional winds accounted for up to 66% of the community variation, indicating importance of the wind-driven balance between fresh and marine water masses. Salinity and temperature accounted for up to 54% and 37% of the variation among lagoon communities, respectively. Recent sea ice declines provide more opportunity for wind to influence oceanographic conditions and biological communities. Current subsistence practices, future commercial fishing opportunities, and on-going oil and gas activities benefit from a better understanding of current fish community distributions. This work provides important data on fish spatial distributions and community composition, providing a basis for fish community response to changing climatic conditions and anthropogenic use.

Drivers and spatial patterns of avian defaunation in tropical forests

AbstractAimWildlife overexploitation, either for food consumption or for the pet trade, is one of the main threats to bird species in tropical forests. Yet, the spatial distribution and intensity of harvesting pressure on tropical birds remain challenging to quantify. Here, we identify the drivers of hunting‐induced declines in bird abundance and quantify the magnitude and the spatial extent of avian defaunation at a pantropical scale.LocationPantropical.MethodsWe compiled 2968 abundance estimates in hunted and non‐hunted sites across the tropics spanning 518 bird species. Using a Bayesian modelling framework, we fitted species' abundance response ratios to a set of drivers of hunting pressure and species traits. Subsequently, we applied our model to quantify the spatial patterns of avian defaunation across tropical forests and to assess avian defaunation across biogeographic realms, and for species captured for the pet trade or for food consumption.ResultsBody mass and its interactions with hunter accessibility and proximity to urban markets were the most important drivers of hunting‐induced bird abundance declines. We estimated a mean abundance reduction of 12% across the tropics for all species, and that 43% of the extent of tropical forests harbour defaunated avian communities. Large‐bodied species and the Indomalayan realm displayed the greatest abundance declines. Further, moderate to high levels of defaunation extended over 24% of the pantropical forest area, with distinct spatial patterns for species captured for the pet trade (Brazil, China and Indonesia) and for food consumption (SE Asia and West Africa).Main ConclusionsOur study emphasizes the role of hunter accessibility and the proximity to urban markets as major drivers of bird abundance declines due to hunting and trapping. We further identified hotspots where overexploitation has detrimental effects on tropical birds, encompassing local extinction events, thus underscoring the urgent need for conservation efforts to address unsustainable exploitation for both subsistence and trade.

Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA

ABSTRACT Cropland fallowing is choosing not to plant a crop during a season when a crop is normally planted. It is an important component of many crop rotations and can improve soil moisture and health. Knowing which fields are fallow is critical to assess crop productivity and crop water productivity, needed for food security assessments. The annual spatial extent of cropland fallows is poorly understood within the United States (U.S.). The U.S. Department of Agriculture Cropland Data Layer does provide cropland fallow areas; however, at a significantly lower confidence than their cropland classes. This study developed a methodology to map cropland fallows within the Northern Great Plains region of the U.S. using an easily implementable decision tree algorithm leveraging training and validation data from wet (2019), normal (2015), and dry (2017) precipitation years to account for climatic variability. The decision trees automated cropland fallow algorithm (ACFA) was coded on a cloud platform utilizing remotely sensed, time-series data from the years 2010–2019 to separate cropland fallows from other land cover/land use classes. Overall accuracies varied between 96%-98%. Producer’s and user’s accuracies of cropland fallow class varied between 70-87%.

Assessing landscape-level effects of permanent grassland management and landscape configuration on open-land butterflies based on national monitoring data

AbstractHalting and reversing the ongoing insect decline requires in-depth knowledge on key drivers. Due to their sensitivity to habitat quality, butterflies are valuable indicators for grassland management intensity, including mowing. However, most studies examining mowing regime impacts on butterflies are limited to small spatial extents. Here, we tested the potential of citizen science butterfly monitoring data for assessing landscape-level effects of mowing regimes (number of mowing events and timing of the first event) and edge density (density of boundaries between different land-cover types) on butterfly richness, abundance, and community composition. We used generalised linear mixed-effects models to relate nationwide data from the German Butterfly Monitoring Scheme (DEBMS) to high-resolution satellite imagery on mowing events in permanent grasslands (grasslands excluded from crop rotation). As butterfly transects may not consistently be located within grasslands, we ran our models for different thresholds from 0 to 50%, representing increasing shares of the transect route situated within permanent grasslands (10% intervals). We did not find significant associations between mowing regimes and butterflies when focussing on species richness and abundance of all species inhabiting open land. However, we found strong positive associations of delayed mowing with the abundance of grassland specialists with increasing grassland shares per transect. Further, we found negative associations of delayed mowing with the annual number of generations and of more frequent mowing with the abundance of specialists, depending on the share of grassland per transect. Edge density had a positive association with species richness and abundance of species inhabiting open land, as well as abundance of grassland indicator species and grassland specialists in landscapes with a low grassland share per transect. Our findings underscore the importance of low-intensity managed permanent grasslands at the landscape scale for specialised butterflies. Additionally, we highlight the importance of a high density of boundaries for open-land and specialised butterflies, particularly in landscapes with highly fragmented permanent grasslands. To improve future analyses of grassland management impacts, we recommend expanding DEBMS monitoring sites to cover a larger grassland management intensity gradient and to place more transects within grasslands.

Post-processing of a distributed source method for the localization of somatosensory cortex in a cohort of epilepsy patients

Localizing eloquent cortices is crucial for many neurosurgical applications, such as epilepsy and tumor resections. Clinicians may use non-invasive methods such as magnetoencephalography (MEG) to localize these cortical regions using equivalent current dipoles (ECDs). While dipoles are clinically validated, they provide the estimated strength, location, and orientation of only one or a few sources that best describe the recorded neuromagnetic data, requiring clinicians to make subjective decisions on the spatial extent of the underlying cortical area. More accurate delineation of eloquent cortical areas using distributed source localization methods would provide additional pre-surgical information on these regions’ location and spatial distribution, which could lead to reduced post-surgical complications associated with damage to or removal of eloquent cortices. Our objective in this paper was to present a method to post-process the distributed source localization results to yield a directly interpretable, distributed region of activation. As a test case, we selected somatosensory stimulation in a retrospective cohort of focal and multi-focal epilepsy patients. Our algorithm performs source localization using a distributed method (sLORETA), followed by post-processing and blind source separation to identify the area and boundary of the cortical tissue that primarily activates in response to somatosensory stimulation. We calculated the statistical significance of localization by comparing the identified region to an anatomical atlas and random chance. While examining patients who received left (upper left, UL) and right (upper right, UR) sided median nerve stimulation, the cortical areas identified by the algorithm were in anatomically appropriate areas with a median overlap of 97.6% and 94.7%, respectively. We observe that our algorithm localized somatosensory responses better than random chance in 57/58 (98%) patients who performed the UL task (p < 10 × 10−10, binomial test) and 49/50 (98%) patients who performed the UR task (p < 10 × 10−10, binomial test). We compared the localization of our algorithm to current clinical methods and found that our algorithm is not inferior to dipole localization. The algorithm can successfully localize somatosensory responses on the cortical surface in anatomically appropriate regions while providing the spatial extent of cortical activation, reducing subjectivity associated with dipole localization.

Linking aerial hyperspectral data to canopy tree biodiversity: An examination of the spectral variation hypothesis

AbstractImaging spectroscopy is emerging as a leading remote sensing method for quantifying plant biodiversity. The spectral variation hypothesis predicts that variation in plant hyperspectral reflectance is related to variation in taxonomic and functional identity. While most studies report some correlation between spectral and field‐based (i.e., taxonomic and functional) expressions of biodiversity, the observed strength of association is highly variable, and the utility in applying spectral community properties to examine environmental drivers of communities remains unknown. We linked hyperspectral data acquired by airborne imaging spectrometers with precisely geolocated field plots to examine the spectral variation hypothesis along a temperate‐to‐boreal forest gradient in southern Québec, Canada. First, we examine the degree of association between spectral and field‐based dimensions of canopy tree composition and diversity. Second, we ask whether the relationships between field‐based community properties and the environment are reproduced when using spectral community properties. We found support for the spectral variation hypothesis with the strength of association generally greater for the functional than taxonomic dimension, but the strength of relationships was highly variable and dependent on the choice of method or metric used to quantify spectral and field‐based community properties. Using a multivariate approach (comparisons of separate ordinations), spectral composition was moderately well correlated with field‐based composition; however, the degree of association increased when univariately relating the main axes of compositional variation. Spectral diversity was most tightly associated with functional diversity metrics that quantify functional richness and divergence. For predicting canopy tree composition and diversity using environmental variables, the same qualitative conclusions emerge when hyperspectral or field‐based data are used. Spatial patterns of canopy tree community properties were strongly related to the turnover from temperate‐to‐boreal communities, with most variation explained by elevation. Spectral composition and diversity provide a straightforward way to quantify plant biodiversity across large spatial extents without the need for a priori field observations. While commonly framed as a potential tool for biodiversity monitoring, we show that spectral community properties can be applied more widely to assess the environmental drivers of biodiversity, thereby helping to advance our understanding of the drivers of biogeographical patterns of plant communities.

Investigating the Near-Surface Wind Fields of Downbursts using a Series of High-Resolution Idealized Simulations

Abstract Short-lived and poorly organized convective cells, often called weakly forced thunderstorms (WFT), are a common phenomenon during the warm season across the eastern and southeastern United States. While typically benign, wet downbursts emanating from such convection can have substantial societal impacts, including tree, power line, and property damage from strong outflow winds. Observational studies have documented the occurrence of severe (25.7 m s‒1 or higher) wind speeds from wet downbursts, but the frequency of severe downbursts, including the spatial extent and temporal duration of severe winds, remains unclear. The ability for modern observing networks to reliably observe such events is also unknown; however, answering these questions is important for improving forecast skill and verifying convective warnings accurately. This study attempts to answer these questions by drawing statistical inferences from 97 high-resolution idealized simulations of single-cell downburst events. It was found that while 35% of the simulations featured severe winds, the spatial and temporal extent of such winds is limited - on the order of 10 km2 or less and persisting for around 5 minutes on average. Furthermore, through a series of simulated network experiments, it is postulated that the probability that a modern mesonet observes a severe wind gust given a severe downburst is around 1%. From these results, a statistical argument is made that most tree impacts associated with pulse convection are likely caused by sub-severe winds. Several implications for forecasting, warning, and verifying WFT events fall out from these discussions.

Influence of large-scale circulation and local feedbacks on extreme summer heat in Argentina in 2022/23

The summer of 2022/23 in Argentina set a record with ten heatwaves. Here, we compare the synoptic and thermodynamic conditions of the four heatwaves with the largest spatial extent using ERA5 reanalysis data. All heatwaves were associated with mid-level anticyclonic anomalies but with different characteristics: three were quasi-stationary high-pressure systems, while one was transient. We also find that enhanced surface fluxes strongly influenced the daily temperature evolution. Furthermore, we perform an attribution exercise using the analogue technique to measure the contributions of atmospheric circulation, soil moisture, and climate change. For quasi-stationary events, the main contribution came from the circulation (up to 2 °C relative to random flow in the present climate). Conversely, the transient heatwave showed a stronger association with extreme soil moisture deficits, with an estimated increase of ~+1 °C relative to wetter conditions. Climate change has also increased the intensity of heatwaves by +0.5 to +1.2 °C relative to previous decades.

Multi-attention fusion transformer for single-image super-resolution

Recently, Transformer-based methods have gained prominence in image super-resolution (SR) tasks, addressing the challenge of long-range dependence through the incorporation of cross-layer connectivity and local attention mechanisms. However, the analysis of these networks using local attribution maps has revealed significant limitations in leveraging the spatial extent of input information. To unlock the inherent potential of Transformer in image SR, we propose the Multi-Attention Fusion Transformer (MAFT), a novel model designed to integrate multiple attention mechanisms with the objective of expanding the number and range of pixels activated during image reconstruction. This integration enhances the effective utilization of input information space. At the core of our model lies the Multi-attention Adaptive Integration Groups, which facilitate the transition from dense local attention to sparse global attention through the introduction of Local Attention Aggregation and Global Attention Aggregation blocks with alternating connections, effectively broadening the network's receptive field. The effectiveness of our proposed algorithm has been validated through comprehensive quantitative and qualitative evaluation experiments conducted on benchmark datasets. Compared to state-of-the-art methods (e.g. HAT), the proposed MAFT achieves 0.09 dB gains on Urban100 dataset for × 4 SR task while containing 32.55% and 38.01% fewer parameters and FLOPs, respectively.

Phenological mismatch between trees and wildflowers: Reconciling divergent findings in two recent analyses

Abstract Recent evidence suggests that community science and herbarium datasets yield similar estimates of species' phenological sensitivities to temperature. Despite this, two recent studies by Alecrim et al. (2023) and Miller et al. (2022) found very different results when using different data sources (community science and herbarium specimens, respectively) to investigate whether warming threatens wildflowers with phenological mismatch in relation to shading by deciduous trees. Here, we investigated whether differences between the two studies' results could be reconciled by testing four hypotheses related to model design, species, spatiotemporal data extent and phenophase. Hybrid model structures brought results from the two datasets closer together but did not fully reconcile the differences between the studies. Neither the species nor the phenophase selected for analysis seemed to be responsible for differences in results. Cropping the datasets to match spatial and temporal extents appeared to reconcile most differences but only at the cost of much higher uncertainty associated with reduced sample size. Synthesis: Our analysis suggests that although species‐level estimates of phenological sensitivity may be similar between community science and herbarium datasets, inherent differences in the types and extent of data may lead to contradictory inference about complex biotic interactions. We conclude that, until community science data repositories expand to match the range of climate conditions present in herbarium collections or until herbarium collections match the spatial extent and temporal frequency of community science repositories, ecological studies should ideally be evaluated using both datasets to test the possibility of biased results from either.

Artistic geography of "Middle Volga texts" by D. Osokin

This article is devoted to the representation of the Middle Volga space in the works of the Russian prose writer Denis Osokin. Domestic literary scholars propose to consider artistic space from the point of view of spatial topography, which implies the opposition of abstraction to concreteness, its horizontal or vertical orientation, spatial extent and localization (expansion-compression, openness-closedness). The search for new methods for studying literary texts has given rise to the need for a comprehensive method, in which a method combining cultural-historical, mythopoetic and geopoetic analysis is quite promising. The subject of the research is the artistic space of Osokin’s “Volga region” texts. The purpose of the study is to determine the specifics of the literary geography of Osokin’s works related to the Volga region. The work uses such scientific methods of analysis as cultural-geographical, structural-semiotic methods and contextual analysis. The scientific novelty of the research is determined by the fact that among modern literary works there are no works devoted to the study of the artistic space of the works of many modern authors, in particular Denis Osokin, his works are considered insufficiently in relation to the phenomena of Kazan and other regional texts. The main conclusion of the study is the substantiation of the special properties of the artistic space of the Middle Volga in the works of D. Osokin, which has attractive properties - uniqueness, semantic richness, cognitive value. Reflection of geographical space in works of art makes it possible to represent and interpret the sociocultural processes of a place and set ontological guidelines. Osokin’s Middle Volga region is a metaspace where the national is organically combined with the foreign, it is a space of memory and the rediscovery of lost meanings.

Restricting angles of incidence to improve super resolution in time reversal focusing that uses metamaterial properties of a resonator array.

Focusing waves with a spatial extent smaller than a half wavelength (i.e., super resolution or sub diffraction limit) is possible using resonators placed in the near field of time reversal (TR) focusing. While a two-dimensional (2D) Helmholtz resonator array in a three-dimensional reverberant environment has limited ability to produce a high-resolution spatial focus in the TR focusing of audible sound, it is shown that acoustic waves propagating out-of-plane with the resonator array are not as strongly affected by the smaller effective wavelength induced by the resonator array, partially negating the effect of the resonators. A physical 2D waveguide is shown to limit the out-of-plane propagation, leading to improved resolution. It is also shown that post processing using an orthogonal particle velocity decomposition of a spatial scan of the focusing can filter out-of-plane particle motion in the near field of the array, which bypasses the effect of the unwanted third spatial dimension of propagation. The spatial resolution in a reverberant environment is shown to improve in the presence of a 2D Helmholtz resonator array and then further improve by adding a 2D waveguide. The resolution among the resonator array is better still without using a waveguide and instead using the partial-pressure reconstruction.

Impacts of habitat loss and fragmentation on seed dispersal by an Afrotropical bird community in an anthropogenic landscape: Insights from movement models

Habitat loss and fragmentation can affect seed dispersal by impacting seed dispersers' habitat choices, behavior, and movement patterns. Here we studied seed dispersal by an Afrotropical bird community in an anthropogenic landscape in Kenya. We used telemetry data of six bird species, estimated their habitat choices, behavior, and movement patterns in the forest fragments and the matrix. We then integrated our model estimates into a seed dispersal simulation model with multiple artificial anthropogenic landscapes, experiencing different levels of habitat loss and fragmentation. In our simulations, we included two seed disperser groups: forest specialist and habitat generalist birds that moved in the landscape using a mixture-correlated random walk, and encamped and traveled in the different habitat types. Increased habitat loss diminished seed dispersal distances, where seeds carried by forest specialist dispersers suffered a stronger reduction in dispersal distances compared to habitat generalists, and number of seeds deposited in habitat fragments, where fewer seeds were deposited into the fragments by habitat generalist dispersers compared to forest specialists. The effects of habitat fragmentation were similar to but weaker than that of habitat loss, and most apparent at an intermediate level of habitat loss. Other seed dispersal metrics, including spatial extent of seed rain and nearest neighbor distances among seeds, did not show any strong relationships with either habitat loss or fragmentation. Therefore, movement models offer valuable perspectives on how habitat loss and fragmentation can influence seed dispersal patterns, by reliably estimating habitat choices, behavior, and movement patterns of dispersers, and potentially benefiting efforts to conserve this ecological interaction.

Design of a Talbot phase-contrast microscopy imaging system with a digital detector for laser-driven X-ray backlighter sources

Laser-driven shock waves in matter propagate with multiple kilometers per second and therefore require sources like a laser-driven backlighter, which emit the X-rays within picoseconds, to be able to capture sharp images. The small spatial extent of shocks in low-density materials pose challenges on the imaging setup. In this work, we present a design process for a single-shot X-ray phase-contrast imaging system geared towards these objects, consisting of a two-grating Talbot interferometer and a digital X-ray detector. This imaging system is optimized with respect to the detectable refraction angle of the X-rays induced by an object, which implies a high phase sensitivity. Therefore, an optimization parameter is defined that considers experimental constraints such as the limited number of photons, the required magnification, the size and spectrum of the X-ray source, and the visibility of the moiré fringes. In this way, a large parameter space is sampled and a suitable imaging system is chosen. During a campaign at the PHELIX high-power laser facility a static test sample was imaged which is used to benchmark the optimization process and the imaging system under real conditions. The results show good agreement with the predicted performance, which demonstrates the reliability of the presented design process. Likewise, the process can be adapted to other types of laser experiments or X-ray sources and is not limited to the application presented here.

An assessment of anticipated future changes in water erosion dynamics under climate and land use change scenarios in South Asia

Water erosion has emerged as a significant global environmental challenge, particularly in South Asia, recognized as one of the regions hardest to hit globally by climate change. This study aims to identify the potential erosion hotspots in South Asia and to assess areas under risk in the future due to climate and land use change scenarios. We utilized the Revised Universal Soil Loss Equation (RUSLE), an empirical erosion model, to estimate erosion for both historical and future periods, considering two distinct Shared Socio-economic Pathways (SSP126 and SSP585). The baseline model predicts a mean water erosion rate of 10.6 t. ha−1. year−1 in South Asia, with more than 30 t. ha−1. year−1 recorded for 6.3 % of the total land area. Notably, Bangladesh and Nepal exhibit significantly higher erosion rates than other South Asian countries. Further, our projection indicates an + 10 % increase in erosion rates during the near future (2021–2040) under SSP585 compared to the historical estimates. A substantial rise of approximately + 31 % and + 39 % in water erosion rates in South Asia is anticipated during the far future periods of 2061–2080 and 2081–2100 under SSP585. At the country level, Bangladesh (+42 %), Bhutan (+108 %), and Nepal (+70 %) are expected to experience substantial increases in erosion rates during the 2081–2100 period, with India projecting a + 38 % increase. Additionally, a significant + 35 % expansion in the spatial extent of high erosion areas (>30 t. ha−1. year−1) is foreseen in 2081–2100 under SSP585. Furthermore, under the low climate change scenario (SSP126), the impact on the erosion rates is minimal, while under SSP585, a substantial increase in erosion rates is anticipated. Regions such as south India, the arid and semi-arid areas near the India-Pakistan border, and the Himalayan foothills are identified as hotspots for significant changes in erosion rates. Acknowledging a certain level of uncertainty, our study provides valuable insights into erosion risk areas in South Asia and their plausible future impacts due to climate and land use changes. This information can assist policymakers in South Asian countries in developing national-level strategies for soil conservation and climate resilience.

Stable isotope evidence for long-term stability of large-scale hydroclimate in the Neogene North American Great Plains

Abstract. The Great Plains of North America host a stark climatic gradient, separating the humid and well-watered eastern US from the semi-arid and arid western US, and this gradient shapes the region's water availability, its ecosystems, and its economies. This climatic boundary is largely set by the influence of two competing atmospheric circulation systems that meet over the Great Plains – the wintertime westerlies bring dominantly dry air that gives way to moist, southerly air transported by the Great Plains low-level jet in the warmer months. Climate model simulations suggest that, as CO2 rises, this low-level jet will strengthen, leading to greater precipitation in the spring but less in the summer and, thus, no change in mean annual precipitation. Combined with rising temperatures that will increase potential evapotranspiration, semi-arid conditions will shift eastward, with potentially large consequences for the ecosystems and inhabitants of the Great Plains. We examine how hydroclimate in the Great Plains varied in the past in response to warmer global climate by studying the paleoclimate record within the Ogallala Formation, which underlies nearly the entire Great Plains and provides a spatially resolved record of hydroclimate during the globally warmer late Miocene. We use the stable isotopes of oxygen (δ18O) as preserved in authigenic carbonates hosted within the abundant paleosol and fluvial successions that comprise the Ogallala Formation as a record of past hydroclimate. Today, and coincident with the modern aridity gradient, there is a sharp meteoric water δ18O gradient with high (−6 ‰ to 0 ‰) δ18O in the southern Great Plains and low (−12 ‰ to −18 ‰) δ18O in the northern plains. We find that the spatial pattern of reconstructed late Miocene precipitation δ18O is indistinguishable from the spatial pattern of modern meteoric water δ18O. We use a recently developed vapor transport model to demonstrate that this δ18O spatial pattern requires air mass mixing over the Great Plains between dry westerly and moist southerly air masses in the late Miocene – consistent with today. Our results suggest that the spatial extents of these two atmospheric circulation systems have been largely unchanged since the late Miocene and any strengthening of the Great Plains low-level jet in response to warming has been isotopically masked by proportional increases in westerly moisture delivery. Our results hold implications for the sensitivity of Great Plains climate to changes in global temperature and CO2 and also for our understanding of the processes that drove Ogallala Formation deposition in the late Miocene.