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As one of the world's most regulated river basins, the semi-arid Murray–Darling Basin (MDB) in south-eastern Australia is considered at high ecological risk, with substantial declines in native fish populations already identified and climate change threats looming. This places great importance on the collection and use of data to document population trends over large spatial extents, inform management decisions, and provide baselines from which change can be measured. We used two medium-term data sets (10 MDB basin-wide fish surveys from 2004–2022) covering the 23 catchments and 68 sub-catchments of the MDB to investigate trends in the distribution of common riverine species at the entire basin scale. Fifteen native species were analysed for changes in their contemporary range, and whilst short-term changes were identified, all species showed no significant continuous trend over the study period. We further analysed the native species extent relative to their historic records, with bony herring and golden perch occurring in 78% and 68% of their historic river kilometres, respectively, whereas southern pygmy perch, northern river blackfish, silver perch, mountain galaxias, and freshwater catfish were all estimated to occur in less than 10% of their historic extent. Six established non-native species were also analysed and were very consistent in extent over the years, suggesting that they are near the available limits of expansion of their invasion. We provide effect sizes for the spatial extent index which can be used as baselines for future studies, especially those aiming to monitor changes in the spatial extent and population status of native species, or changes in the spatial extent of new or existing non-native species. [ABSTRACT FROM AUTHOR]

Spatially compounding droughts and floods challenge water management and may become more severe in a warming climate. However, the influence of climate change on widespread hydrologic extremes remains largely unknown because they are neither well represented in observations nor in models. Here, we present a non‐stationary stochastic streamflow generator that captures streamflow dependencies between different catchments and represents seasonal covariations of streamflow with temperature. We run this model for 925 nearly natural catchments in the Alps to generate daily streamflow time series for a reference period and three warming levels of 1, 2, and 3°C. Then, we identify drought and flood events, determine their spatial extents, and assess changes in all of these characteristics. This sensitivity analysis for different warming levels suggests that changes in flood characteristics and spatial extent are substantially weaker than those in drought characteristics and spatial extent. While floods show changes in their timing toward earlier in the year, simulated changes in magnitude, volume, duration, and spatial extent are negligible. In contrast, droughts show changes not just in timing but also intensity, deficit, duration, and extent. Specifically, droughts are projected to intensify, last longer, and slightly increase in spatial extent, with the magnitude of change increasing with the warming level. These projected changes highlight the need to develop adaptation strategies in particular for droughts. Such adaptation strategies should go beyond local adaptation and consider that extreme events become more widespread in a warming world. Plain Language Summary: Widespread droughts and floods challenge water management and may become more severe in a warming climate. However, the influence of climate change on widespread hydrologic extremes remains largely unknown because they are neither well represented in observations nor in models. Here, we propose a stochastic streamflow generator that allows us to simulate streamflow time series for different warming scenarios. We run this model for a large number of catchments in the Alps to simulate droughts and floods in a warming climate. Our simulations suggest weaker future changes in flooding than in droughts. Floods are projected to happen earlier in the year while simulated changes in magnitude are negligible. In contrast, droughts show changes not just in timing but also increases in intensity, deficit, duration, and extent. These projected changes highlight the need to develop adaptation strategies in particular for droughts. Such adaptation strategies should go beyond local adaptation and consider that extreme events become more widespread in a warming world. Key Points: We propose a non‐stationary stochastic model for daily streamflow generation using temperature as a co‐variateOur sensitivity analysis for different warming levels suggests weak future changes in flood characteristics and extentIn addition, it projects increases in drought magnitude and timing, and weak increases in drought spatial extent [ABSTRACT FROM AUTHOR]

As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large‐sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P‐ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land‐surface but decreases again for groundwater because of sub‐surface heterogeneity. Plain Language Summary: As rainfall deficits develop into discharge and groundwater deficits, the impacts of droughts increase. While we know that drought impacts and properties change during drought development, it is yet unknown how the spatial characteristics of droughts change over the duration of an event. Here, we use a large dataset of 70 watersheds in Central Europe to study the development of drought characteristics over the duration of a drought event. We show that drought development leads to longer, later, fewer, and larger droughts. 20% of the rainfall droughts develop into discharge droughts, and 10% into groundwater droughts. Of the discharge droughts, 40% develop into groundwater droughts. Drought extent increases during drought development from rainfall to discharge thanks to effects at the land‐surface but decreases again for groundwater because of sub‐surface variations. Key Points: Drought propagation affects local and regional drought characteristics and leads to longer, later, fewer, and larger droughtsOnly 20% of the precipitation deficits propagate to streamflow, while 40% of the streamflow deficits propagate to groundwaterSpatial drought connectedness increases from precipitation to streamflow but decreases again for groundwater [ABSTRACT FROM AUTHOR]

Context: The spatial extent at which landscape variables most strongly influences wildlife populations (i.e., scale of effect) is of key importance to ecology and conservation. Many factors can influence scales of effect, but these relationships are poorly understood. In particular, the way scales of effect vary with different landscape metrics has not been extensively tested. Objectives: Our study tested whether metrics of landscape configuration have wider or narrower scales of effect than habitat composition. We also examined how species traits and landscape context influence the magnitude of differences in scales of effect between metrics. Methods: We calculated scales of effect for four metrics of habitat configuration and one metric of composition directly from species presence/absence data in online repositories including 102 species of forest mammals from 33 studies across the globe. We then compared the magnitudes and variability of scales of effect using Hedge's g. Results: Two metrics of configuration (flux and patch density) had significantly wider scales of effect than habitat composition, while the differences between the other two metrics of configuration and composition were not statistically significant. The magnitude of the difference between metrics varied among samples, but none of the factors tested explained this variability. Conclusions: For forest mammals, the scale of effect of a configuration metric can be expected to be 15–20% wider than a composition metric. However, this pattern may not hold for metrics of configuration that do not quantify attributes of the landscape that mediate species dispersal or that are correlated with the metric of composition. [ABSTRACT FROM AUTHOR]

There is continuing interest in the investigation of change in temperature over space and time. For this analysis, we offer statistical tools to illuminate changes temporally, at desired temporal resolution, and spatially, using data generated from suitable space–time models. The proposed tools can be used with the output from any suitable model fitted to any set of spatially referenced time series data. The tools to assess space and time changes include spatial surfaces of probabilities and spatial extents for events defined by exceeding a threshold. The spatial surfaces capture the spatial variation in the probability or risk of an exceedance event, while the spatial extents capture the expected proportion of incidence of an event for a region of interest. This approach is used analyse the changes in daily maximum temperature in an inland Mediterranean region (NE of Spain) in the period 1956–2015. The area is very heterogeneous in orography and climate, including the central Ebro valley and part of the Pyrenees. We use a collection of daily temperature series obtained from simulation under a Bayesian daily temperature model fitted to 18 stations in that area. The results for the summer period show that, although there is an increasing risk in all the events used to quantify the effects of climate change, it is not spatially homogeneous, with the largest increase arising in the centre of the Ebro valley and the Eastern Pyrenees area. The risk of an increase in the average daily maximum temperature from 1966–1975 to 2006–2015 higher than 1°C is higher than 0.5 over all of the region, and close to 1 in the previous areas. The extent of daily maximum temperature higher than the reference mean has increased 3.5% per decade. The mean of the extent indicates that 95% of the area under study has suffered a positive increment of the average temperature, and almost 70% an increment higher than 1°C. [ABSTRACT FROM AUTHOR]

Abstract Spatially compounding droughts and floods challenge water management and may become more severe in a warming climate. However, the influence of climate change on widespread hydrologic extremes remains largely unknown because they are neither well represented in observations nor in models. Here, we present a non‐stationary stochastic streamflow generator that captures streamflow dependencies between different catchments and represents seasonal covariations of streamflow with temperature. We run this model for 925 nearly natural catchments in the Alps to generate daily streamflow time series for a reference period and three warming levels of 1, 2, and 3°C. Then, we identify drought and flood events, determine their spatial extents, and assess changes in all of these characteristics. This sensitivity analysis for different warming levels suggests that changes in flood characteristics and spatial extent are substantially weaker than those in drought characteristics and spatial extent. While floods show changes in their timing toward earlier in the year, simulated changes in magnitude, volume, duration, and spatial extent are negligible. In contrast, droughts show changes not just in timing but also intensity, deficit, duration, and extent. Specifically, droughts are projected to intensify, last longer, and slightly increase in spatial extent, with the magnitude of change increasing with the warming level. These projected changes highlight the need to develop adaptation strategies in particular for droughts. Such adaptation strategies should go beyond local adaptation and consider that extreme events become more widespread in a warming world.

Abstract As droughts propagate both in time and space, their impacts increase because of changes in drought properties. Because temporal and spatial drought propagation are mostly studied separately, it is yet unknown how drought spatial extent and connectedness change as droughts propagate though the hydrological cycle from precipitation to streamflow and groundwater. Here, we use a large‐sample dataset of 70 catchments in Central Europe to study the propagation of local and spatial drought characteristics. We show that drought propagation leads to longer, later, and fewer droughts with larger spatial extents. 75% of the precipitation droughts propagate to P‐ET, among these 20% propagate further to streamflow and 10% to groundwater. Of the streamflow droughts, 40% propagate to groundwater. Drought extent and dependence increase during drought propagation along the drought propagation pathway from precipitation to streamflow thanks to synchronizing effects of the land‐surface but decreases again for groundwater because of sub‐surface heterogeneity.

The structure and diversity of plant communities respond to changes in landscape structure and vary with spatial scale, stand age and plant size. Therefore, it is important to identify the scale (grain size and extent) at which secondary forest attributes of large and/or small plants and landscape structure are more closely associated. We performed multi-scale analyses in which different grain sizes and extents were assessed to determine the most appropriate spatial scale for assessing the association of large/small tree aboveground biomass and species richness with successional age and landscape structure using regression analysis. AGB and species richness were more strongly associated with landscape structure when large grain sizes (500 m2) were used, with R2 values between 0.31 and 0.43. Variation in AGB and species richness was explained primarily by successional age and landscape structure, respectively. At large extents, successional age was related to the AGB of large trees (R2 = 0.43); at intermediate extents, landscape structure was related to the species richness of large trees (R2 = 0.31). The approach and results of this study may facilitate the identification of appropriate areas and scales for the maintenance or restoration of tree diversity, carbon storage, and the provision of ecosystem services in tropical dry forests.

As one of the world’s most regulated river basins, the semi-arid Murray–Darling Basin (MDB) in south-eastern Australia is considered at high ecological risk, with substantial declines in native fish populations already identified and climate change threats looming. This places great importance on the collection and use of data to document population trends over large spatial extents, inform management decisions, and provide baselines from which change can be measured. We used two medium-term data sets (10 MDB basin-wide fish surveys from 2004–2022) covering the 23 catchments and 68 sub-catchments of the MDB to investigate trends in the distribution of common riverine species at the entire basin scale. Fifteen native species were analysed for changes in their contemporary range, and whilst short-term changes were identified, all species showed no significant continuous trend over the study period. We further analysed the native species extent relative to their historic records, with bony herring and golden perch occurring in 78% and 68% of their historic river kilometres, respectively, whereas southern pygmy perch, northern river blackfish, silver perch, mountain galaxias, and freshwater catfish were all estimated to occur in less than 10% of their historic extent. Six established non-native species were also analysed and were very consistent in extent over the years, suggesting that they are near the available limits of expansion of their invasion. We provide effect sizes for the spatial extent index which can be used as baselines for future studies, especially those aiming to monitor changes in the spatial extent and population status of native species, or changes in the spatial extent of new or existing non-native species.

A deeper understanding of the spatial relationships of β-amyloid (Aβ), tau, and neurodegeneration in Alzheimer's disease (AD) could provide insight into pathogenesis and clinical trial design. We included 81 amyloid-positive patients (age 64.4 ± 9.5) diagnosed with AD dementia or mild cognitive impairment due to AD and available 11C-PiB (PIB), 18F-Flortaucipir (FTP),18F-FDG-PET, and 3T-MRI, and 31 amyloid-positive, cognitively normal participants (age 77.3 ± 6.5, no FDG-PET). W-score voxel-wise deviation maps were created and binarized for each imaging-modality (W > 1.64, P  tau > neurodegeneration was the most frequent hierarchy for both groups (79-77%, respectively), followed by tau > amyloid > neurodegeneration (13-10%) and amyloid > neurodegeneration > tau (6-13%). For symptomatic participants, most abnormal voxels were PIB+/FTP+/ND- (median 35%), and the great majority of ND+ voxels (91%) colocalized with molecular pathology. Amyloid spatially exceeded tau and neurodegeneration, with individual heterogeneities. Molecular pathology and neurodegeneration showed a progressive overlap along AD course, indicating shared vulnerabilities or synergistic toxic mechanisms.

The regolith of the Chang'E-4 landing site was disturbed by its engine exhaust. To explore the interaction between the engine exhaust and the regolith, it was necessary to identify the exhaust-disturbed region. This article focuses on determining the extent of the disturbed region by using lunar reconnaissance orbiter camera narrow angle camera (LROC NAC) images. For this purpose, the tools of temporal-ratio images, phase-ratio images, reflectance profiles, and reflectance isoline graphs are employed. The reflectance profiles and isoline graphs derived from the temporal-ratio images reveal the reflectance changes before and after landing. Compared with the reflectance profiles, isoline graphs further include the spatial information of isolines, thus more robust to noise. Based on the magnitudes of changed reflectance around the lander, the engine exhaust-disturbed region was further divided into the focus disturbed region (FDR) and the diffuse disturbed region (DDR). The final estimated spatial extent along the north–south and east–west directions of the FDR were ∼9.6 and ∼10.8 m, and those of the DDR were ∼75 and ∼80 m. As compared with the estimated spatial extent of the Chang'E-3 landing site, the DDR of the Chang'E-4 landing site was larger, but the FDR was smaller. We attributed this to geological and topography factors. The reflectance changes between the FDR and the undisturbed region increased by ∼10±1%. This indicates similar processes causing the variations in the regolith properties, likely including the smoothing of the surface from microscopic to macroscopic by destroying fine-grained regolith components, or changing of the surface maturity.

Context: Old-growth forest loss drives the global biodiversity crisis. Nevertheless, this impact could be buffered by the increasing expansion of secondary (regenerating) forests, which can provide supplementary habitat for wildlife. Objectives: We tested this hypothesis assessing the effect of old-growth and secondary forest cover on the abundance and immature-to-female ratio (proxy of reproductive success) of two endangered primates: Geoffroy' spider monkeys and black howler monkeys. Methods: We measured the response and predictor variables across 18 whole landscapes (landscape-scale approach) in the Lacandona rainforest, Mexico. As there could be tipping points of forest loss beyond which species extinction is accelerated (extinction thresholds), we separately tested the linear and non-linear effect of forest cover on each response, independently for three spatial scales. Results: We found stronger and larger-scale negative responses to forest loss in spider monkeys than in howler monkeys. However, the data were better predicted by linear models, giving no support to the extinction threshold hypothesis. In both species, forest loss had stronger negative impacts on monkey abundance when considering old-growth forest, than when considering secondary forest cover, or total (old-growth + secondary) forest cover. Yet, the immature-to-female ratio was weakly related to forest cover in both species. Conclusion: Secondary forests seem to have a weak buffering effect in both species, possibly because they are relatively young (< 30 years old) and do not have large trees. This implies that old-growth forests are irreplaceable for preventing primate extirpation, especially for species with specialized diet and large spatial requirements, such as spider monkeys. [ABSTRACT FROM AUTHOR]

Europe has been affected by record‐breaking heat waves in recent decades. Using station data and a gridded reanalysis as input, four commonly used heat wave indices, the heat wave magnitude index daily (HWMId), excess heat factor (EHF), wet‐bulb globe temperature (WBGT) and universal thermal climate index (UTCI), are computed. The extremeness of historical European heat waves between 1979 and 2019 using the four indices and different metrics is ranked. A normalisation to enable the comparison between the four indices is introduced. Additionally, a method to quantify the influence of the input parameters on heat wave magnitude is introduced. The spatio‐temporal behaviour of heat waves is assessed by spatial–temporal tracking. The areal extent, large‐scale intensity and duration are visualized using bubble plots. As expected, temperature explains the largest variance in all indices, but humidity is nearly as important in WBGT and wind speed plays a substantial role in UTCI. While the 2010 Russian heat wave is by far the most extreme event in duration and intensity in all normalized indices, the 2018 heat wave was comparable in size for EHF, WBGT and UTCI. Interestingly, the well‐known 2003 central European heat wave was only the fifth and tenth strongest in cumulative intensity in WBGT and UTCI, respectively. The June and July 2019 heat waves were very intense, but short‐lived, thus not belonging to the top heat waves in Europe when duration and areal extent are taken into account. Overall, the proposed normalized indices and the multi‐metric assessment of large‐scale heat waves allow for a more robust description of their extremeness and will be helpful to assess heat waves worldwide and in climate projections. [ABSTRACT FROM AUTHOR]

Snow cover is highly sensitive to global climate change and strongly influences the climate at global and regional scales. Because of limited in situ observations, snow cover dynamics in the Nyang River basin (NRB) have been examined in few studies. Five snow cover indices derived from observation and remote sensing data from 2000 to 2018 were used to investigate the spatial and temporal variation of snow cover in the NRB. There was clear seasonality in the snow cover throughout the entire basin. The maximum snow-covered area was 8,751.35 km2, about 50% of the total basin area, and occurred in March. The maximum snow depth (SD) was 5.35 cm and was found at the northern edge of the middle reaches of the basin. Snow cover frequency, SD, and fraction of snow cover area increased with elevation. The decrease in SD was the most marked in the elevation range of 5,000–6,000 m. Above 6,000 m, the snow water equivalent showed a slight upward trend. There was a significant negative correlation between snow cover and temperature. The results of this study could improve our understanding of changes in snow cover in the NRB from multivariate perspectives. It is better for water resources management. HIGHLIGHTS Different snow cover indices were used to evaluate the snow cover characteristics of Nyang River basin. Snow cover days data were collected for calculating snow cover frequency to evaluate the character of the basin.; The temporal and spatial distribution of snow cover in Nyang River basin was clarified.; There is a significant negative correlation between snow cover and air temperature.;

Abstract Europe has been affected by record‐breaking heat waves in recent decades. Using station data and a gridded reanalysis as input, four commonly used heat wave indices, the heat wave magnitude index daily (HWMId), excess heat factor (EHF), wet‐bulb globe temperature (WBGT) and universal thermal climate index (UTCI), are computed. The extremeness of historical European heat waves between 1979 and 2019 using the four indices and different metrics is ranked. A normalisation to enable the comparison between the four indices is introduced. Additionally, a method to quantify the influence of the input parameters on heat wave magnitude is introduced. The spatio‐temporal behaviour of heat waves is assessed by spatial–temporal tracking. The areal extent, large‐scale intensity and duration are visualized using bubble plots. As expected, temperature explains the largest variance in all indices, but humidity is nearly as important in WBGT and wind speed plays a substantial role in UTCI. While the 2010 Russian heat wave is by far the most extreme event in duration and intensity in all normalized indices, the 2018 heat wave was comparable in size for EHF, WBGT and UTCI. Interestingly, the well‐known 2003 central European heat wave was only the fifth and tenth strongest in cumulative intensity in WBGT and UTCI, respectively. The June and July 2019 heat waves were very intense, but short‐lived, thus not belonging to the top heat waves in Europe when duration and areal extent are taken into account. Overall, the proposed normalized indices and the multi‐metric assessment of large‐scale heat waves allow for a more robust description of their extremeness and will be helpful to assess heat waves worldwide and in climate projections.

The spatial extent of a dual-frequency echosounder and its potential impact on cetacean species were examined. Sound emissions of output frequencies of 83 kHz and 200 kHz were tested at a maximum distance of 400 m. This is the minimum vessel approach distance for killer whales (Orcinus orca) in southern British Columbia, which was introduced as a measure for limiting disturbance of southern resident killer whales (SRKWs). The experiment was conducted in shallow (34 m) and deep (220–235 m) water. Recordings were made at depths of 5 and 30 m for both locations, as well as at 100 and 200 m in the deeper water to examine the effect of the echosounder through the water column and at SRKW diving depths. The recordings showed that 200 kHz echosounder emissions were contained within a 250 m radius of the source, with most of the acoustic energy focused within 100 m in shallow waters. For the 83 kHz signal and for deeper water testing of the 200 kHz signal, the echosounder transmissions exceeded the 400 m threshold, intimating that whales could experience noise additions of 30 dB or more above the ambient level at the minimum vessel approach distance. Evaluating the noise additions to the ambient level from the echosounder in frequencies used by SRKWs for echolocation (15–100 kHz) further showed the potential impact on whales in close proximity to vessels (≤400 m) when using echosounders or fish-finders. [ABSTRACT FROM AUTHOR]

Marine temperature extremes are anomalous ocean temperature events, often persisting over several weeks or longer, with potential impacts on physical and ecological processes that often encompass socio-economic implications. In recent years, a considerable effort has been directed at the development of metrics allowing an objective characterization of both marine heatwaves (MHWs) and marine cold spells (MCSs). However, the majority of these metrics do not consider explicitly the spatial extent of the events. Here, we rank and evaluate the relative importance of marine temperature extreme events thanks to a metric, called activity, that combines the number of events, duration, intensity and spatial extent. According to this definition, in the Mediterranean basin between 1982 and 2021, summer 2018 experienced slightly more MHW activity than summer 2003, documented as an exceptional extreme event. Besides, MHW activities were higher in the last two decades while winter MCS activities were higher in the 1980s-1990s. The highest MHW activities occurred preferentially in the western Mediterranean while the strongest MCS activities took place preferentially in the eastern Mediterranean. Moreover, the duration, mean intensity, and activity of the three strongest MHWs are twice as high as those of the three strongest MCSs. The long-term tendency of extreme events activity shows an accelerated increase for summer MHWs (about +150°C.days.10⁶km²) and a linear decrease for winter MCSs in the Mediterranean (about -60°C.days.10⁶km²) over the last four decades.

Context: Biodiversity patterns depend on landscape structure, but the spatial scale at which such dependence is strongest (scale of effect, SoE) remains poorly understood, especially for elusive species such as arboreal tropical mammals. Objectives: To identify the SoE of arboreal mammals and assess whether it depends on the biological response and/or landscape predictor. Methods: We surveyed arboreal mammals during one year placing camera traps in 100 trees within 20 forest patches in the Lacandona rainforest, Mexico. In each patch, we estimated species richness, total abundance, and species-specific relative abundance. We related each response variable to percent forest cover, matrix openness, patch density, and edge density measured within 13 concentric buffers from the geographic centre of sampling sites (100–1300 m radius). We identified the SoE for each combination of mammal response and landscape predictor. Results: Edge density tended to have larger SoE than forest cover and matrix openness, and SoE did not differ between species richness and total abundance. SoE tended to be positively related to the body mass of mammals. Conclusions: The relatively large SoE of edge density suggests that this predictor affects mammals mainly by regulating large-scale processes, such as increasing dispersal rates in landscapes with higher edge density, and not by moderating local-scale processes (e.g. edge effects). Species richness and total abundance seem to be moderated by ecological processes acting across similar spatial scales. SoE tends to increase with body mass, confirming that conservation plans for larger mammals often need to be implemented across larger areas. [ABSTRACT FROM AUTHOR]

The exponential population growth of Karachi city has taken a very heavy toll on the indigenous environment of this South Asian megacity. In this context, the unlikely roadsides plantation of nonnative species by the city decision-makers was a short-term solution to cultivate green belts, ultimately, to improve city environment. However, this has backfired and become a very serious ecological crisis as the species become invasive alien species and destroyed the native ecological environment of the city significantly. This study provided an accurate spatial extent of invasive alien species and evaluated the intensity of the problem using remote sensing technology. Firstly, the importance value index was developed to highlight the intensity of invasive alien species in native plant communities. Afterwards, the hot spots were sampled to develop training areas for Object Based Image Analysis to map the extent of invasive alien species in the city using high-resolution GeoEye satellite imagery. The overall accuracy of mapping was 93.17% with Kappa coefficient value of 0.904. In addition, to explore hyperspectral remote sensing analysis, two techniques—Derivative Vegetation Index and Spectral Angle Mapper—were employed on EO-I hyperspectral imagery to map invasive alien species using spectral signatures. The analysis revealed 99.94% correlation between the two mapping techniques. Finally, to identify the impact of invasive alien species on the microclimate of the city, a spatiotemporal analysis (1992–2016) at selected sites was performed on Landsat thermal images. The study ruled out the concept of invasive alien species influence on the microclimate of the city as both vegetation growth and ambient air temperature change were not interdependent. [ABSTRACT FROM AUTHOR]

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.

This study examines the up-to-date observed trends of subseasonal to annual range climate extremes over the East Asia region using the high-resolution global unified gauge-based analysis of the NOAA Climate Prediction Center for 1981–2021. The spatial extent of extreme events is identified using the Expert Team on Climate Change Detection and Indices (ETCCDI)-based modified climate extreme index (EmCEI) with five subcomponents (maximum temperature, minimum temperature. total rainfall, heavy rainfall, and wet and dry days). By combining the spatiotemporal fields into a simple index, trends in climate extremes are systematically obtained in various time ranges. Annual and semi-annual long-term trends in East Asia showed a statistically significant increase in the percentage of area affected by the upper-extreme climate (warm days, warm nights, wet extreme) and concurrently by the decrease of lower-extreme climate (cool days, cool nights, dry extreme). As the time range becomes higher, the tendency is consistent but extremeness depends on seasons and calendar months. The total EmCEI shows an increasing trend greater in the warm (summer) season than in the cold (winter) season. The temperature extreme components (C1 and C2) are dominated in spring and summer. In the subseasonal months, March has the highest trend among the calendar months both in C1 and C2. The increasing trend is consistently distinct in the 2010s for all time ranges and all components. The long-term trend in winter exhibits distinctive features of the smallest increase than in other seasons and months caused by robust interannual to multidecadal variability in the 1990s–2000s. The area affected by heavy rainfall is mainly dominated in summer while the total rainfall and wet day extreme extend in summer and fall, respectively. The EmCEI suggests that the change in the spatial extent of climate extremes is mainly caused by a shift in temperature and rainfall distributions toward warm and wet extremes over East Asia.

China's rapid deployment of solar photovoltaic (PV) power plants has positioned it as the global leader in cumulative installed capacity. The expansion patterns of PV power plants in China play a crucial role in promoting PV diffusion in markets, shaping policies, and analyzing environmental and social impacts. However, the current geospatial datasets of PV power plants available for China cannot fully address these needs due to either missing installation dates or outdated information. Hence, this study develops a framework to extract the spatial extent and installation date of PV power plants from Sentinel-2 and Landsat data using deep learning and change detection techniques and uncover their expansion patterns in China. A geospatial dataset of PV polygons with installation dates in China from 2010 to 2022 is obtained with the F1-score of 96.08% for its spatial extent and the overall accuracy of 89.86% for its installation dates. We found that western China has a higher total PV area but a lower density of large-size PV power plants whereas eastern and central China have lower total PV areas but a higher density of small-size PV power plants. The area of PV power plants in China has over 600-fold increase from 5.86 km2 in 2010 to 3712.1 km2 in 2022 with the average annual growth of 285 km2 and western China has the highest annual growth proportion of 53%. The PV power plants in eastern and central China mainly established on croplands (24.6%) and the occupation of croplands presents a significant reduction of 48% from 2017 to 2022. In contrast, PV installations in western China, especially poverty-stricken areas, are primarily deployed on grasslands (28.3%) and unused lands (27.5%) and a declining pattern is observed in the occupation of grasslands. The up-to-date geospatial dataset of PV power plants and their expansion pattern analysis offer valuable insights into the understanding of PV development and its land occupation in both space and time, and thereby contribute to the policy-making of carbon mitigation for China. • A framework is proposed to extract PV power plants and uncover their expansions. • The PV polygons with installation dates in China from 2010 to 2022 is provided. • The expansion patterns of PV power plants are explored in both space and time. • The occupation of cropland and grassland by PV power plants has a declining trend. [ABSTRACT FROM AUTHOR]

Recent studies have shown that several sources of variation can influence our ability to quantify biological responses to environmental variables, and that spatial scales are important in this process. For instance, sampling methods may differ in their efficiency or specificity, leading to different inferred relationships between community responses and landscape composition—i.e., forest cover (%), landscape heterogeneity, edge effects, and functional connectivity. Consequently, this can also influence the predictive power of the models when evaluating organisms as bioindicators of habitat loss and land use modification. Here, we evaluated how sampling methods (i.e., Winkler, pitfall, beating, and baits) influence our capacity to assess the scale of effect of two landscape composition metrics on ant diversity. We conducted ant sampling in 16 landscapes within a Mexican tropical rainforest and assessed the relationship between species richness and landscape composition metrics through buffers with 12 different spatial extents (from 50 to 1000 m). We found that the sampling method influenced the scale of effect when evaluating the relationships between ant species richness and forest cover and landscape heterogeneity. Combining all sampling methods, we found that the scales that best explained ant species richness were 700 m for forest cover and 900 m for landscape heterogeneity. Therefore, we highlight that our ability to detect ant-based diversity responses to environmental variables depends on the sampling method and spatial extent used in the study. [ABSTRACT FROM AUTHOR]

Biodiversity-productivity relationship (BPR) has become a central issue of ecology and conservation biology. The current understanding of BPR mainly comes from local scales, which is, however, difficult to extend to the BPR pattern at the regional scale owing to the scale dependence of regional communities. 2. To elucidate the BPR at the regional communities across multiple spatial scales, we investigated the 328 plots with about 30,000 trees across 700,000 km2 regional area in the temperate forests. In this study, the n closest plots were aggregated to form regional clusters representing the spatial scale characterized by the spatial extent of regional communities, which were used to explore the relationships of multiple facets of biodiversity (i.e. taxonomic, functional, and phylogenetic diversity) with the productivity of regional communities. 3. Our study provides insight into the discrepancy among taxonomic, functional, phylogenetic biodiversity in modulating productivity across the different specific biogeographical clusters within a large regional area. We found that the spatial extent of the tree community could change the importance of the multiple facets of biodiversity on productivity. Phylogenetic diversity may be a better driver of productivity at the smaller spatial scale of the regional communities. In contrast, taxonomic diversity appears to be more predominant in affecting productivity at the broader spatial scale. 4. Our results suggest that the understanding of the BPR patterns benefited from the multiple facets of biodiversity. The findings highlight the scale dependence of the BPRs, representing the significance of the spatial extent of the regional communities on them. This would improve our abilities to interpret and predict temperate forest productivity across the different spatial scales of the regional communities. [ABSTRACT FROM AUTHOR]

The spatial extent of a dual-frequency echosounder and its potential impact on cetacean species were examined. Sound emissions of output frequencies of 83 kHz and 200 kHz were tested at a maximum distance of 400 m. This is the minimum vessel approach distance for killer whales (Orcinus orca) in southern British Columbia, which was introduced as a measure for limiting disturbance of southern resident killer whales (SRKWs). The experiment was conducted in shallow (34 m) and deep (220–235 m) water. Recordings were made at depths of 5 and 30 m for both locations, as well as at 100 and 200 m in the deeper water to examine the effect of the echosounder through the water column and at SRKW diving depths. The recordings showed that 200 kHz echosounder emissions were contained within a 250 m radius of the source, with most of the acoustic energy focused within 100 m in shallow waters. For the 83 kHz signal and for deeper water testing of the 200 kHz signal, the echosounder transmissions exceeded the 400 m threshold, intimating that whales could experience noise additions of 30 dB or more above the ambient level at the minimum vessel approach distance. Evaluating the noise additions to the ambient level from the echosounder in frequencies used by SRKWs for echolocation (15–100 kHz) further showed the potential impact on whales in close proximity to vessels (≤400 m) when using echosounders or fish-finders.

Context: As an important type of sustainable landscape patterns, ecological security patterns focus on the spatial assessment of landscape function importance. However, there is a lack of attention to the scale effect, one of core cognitions of landscape ecology, especially the impact of extent changes on sustainable landscape patterns. Objectives: Taking Weifang City and its surrounding six cities as the study area, this study was aimed to integrate regional and interregional approaches to identify ecological security patterns with a special focus on the effect of spatial extent changes. Methods: We assessed the ecosystem service importance and integrated the ecological sources identified in view of regional and interregional perspectives. The key or fragile ecological corridors were then identified and the differences of ecological security patterns in different approaches were explored through several landscape metrics. Results: 11 central ecological sources and 21 surrounding ecological sources were identified. 70% key ecological corridors were the interregional ecological corridors across Weifang City and other cities. Different study extents would cause up to about 24% of the difference in high ecosystem service importance areas of Weifang City, and the corridor connectivity could be improved in the ecological security patterns by integrating the regional and interregional approaches. Conclusions: This study made up for the shortcomings of identifying sustainable landscape patterns within the single spatial extent, especially the discontinuity of ecological sources between the adjacent areas through regional approach, and the neglected local ecological land conservation through interregional approach. [ABSTRACT FROM AUTHOR]

Wetlands are highly valued and significant ecosystems with a large range of services and functions. To help manage and protect them, it is important to map and monitor their spatial extent and condition. However, wetlands have not yet been comprehensively and reliably mapped at the national level, although elements for mapping national coverage exist in two of our national databases: Waters of National Importance (WONI), and the New Zealand Land Cover Database (LCDB). The extent of freshwater wetlands in WONI was derived by identifying all types of freshwater wetlands, excluding inland saline. The extent of freshwater wetlands in the LCDB was derived by identifying areas with either a wet context, herbaceous freshwater vegetation, or flax. We then combined identified freshwater wetlands from the two databases recognising the superior boundary delineation of LCDB and the superior wetland detection of WONI. The current spatial extent of freshwater wetlands in New Zealand is now calculated at 249 214 ha, or 10.08% of the historical extent, rather than the 7.4% reported by LCDB5 alone. This is at least 5954 ha less than that in 1996. The revised extent of freshwater wetlands is an improvement over either WONI or LCDB because it now includes a more comprehensive set of wetlands over 0.5 ha in area with well-defined boundaries. However, the revised extent does not include small wetlands less than 0.5 ha in area. While adding little to the total area of wetlands in New Zealand, small wetlands have significant ecological value. The National Policy Statement for Freshwater Management mandates the national mapping of the small wetlands down to 0.05 ha, but we suggest their ecological value be considered in land use change decisions only, thereby avoiding the excessive cost of mapping many millions of small wetlands. [ABSTRACT FROM AUTHOR]

The spatial and temporal knowledge on spread of invasive aquatic plants helps to determine their extent, abundance, and propagation rates in invaded water systems. Water hyacinth Eichhornia crassipes (Liliales: Pontederiaceae) appeared in Rwandan water bodies in 1957, and it was legislated and accepted as a problematic invasive species in Rwanda in 1999. Water hyacinth has led to a reduction in water quantity and threatened the livelihood of local communities that live off fishing. To comprehend the status of the water hyacinth invasion and assist management strategies, it is important to have detailed and consistent information on its spatio-temporal spread, magnitude, and rate of change dynamics in water systems. This was investigated using time series Landsat satellite images for the years 1989, 2002, and 2017. Image classifications using the nonparametric classifier random forest as well as change detection analysis were carried out to process the satellite data. The results revealed a fluctuation in the extent of water hyacinth over the time series of 1989, 2002, and 2017 with estimated percentage cover of 17.7%, 22.4%, and 20.8%, respectively. An annual increase of 1.9% in water hyacinth invasion was observed from 1989 to 2002; while, a decline of 1.7% per annum was observed from 2002 to 2017. The decline observed in 2017 could be due to manual control undertaken by the government since 2002. This study confirms the potential of using remotely sensed imagery as a valuable method for determining the change in the extent and distribution of invasive alien weeds over time. [ABSTRACT FROM AUTHOR]

The accumulation of tau abnormality in sporadic Alzheimer's disease is believed typically to follow neuropathologically defined Braak staging. Recent in-vivo PET evidence challenges this belief, however, as accumulation patterns for tau appear heterogeneous among individuals with varying clinical expressions of Alzheimer's disease. We, therefore, sought a better understanding of the spatial distribution of tau in the preclinical and clinical phases of sporadic Alzheimer's disease and its association with cognitive decline. Longitudinal tau-PET data (1370 scans) from 832 participants (463 cognitively unimpaired, 277 with mild cognitive impairment and 92 with Alzheimer's disease dementia) were obtained from the Alzheimer's Disease Neuroimaging Initiative. Among these, we defined thresholds of abnormal tau deposition in 70 brain regions from the Desikan atlas, and for each group of regions characteristic of Braak staging. We summed each scan's number of regions with abnormal tau deposition to form a spatial extent index. We then examined patterns of tau pathology cross-sectionally and longitudinally and assessed their heterogeneity. Finally, we compared our spatial extent index of tau uptake with a temporal meta-region of interest-a commonly used proxy of tau burden-assessing their association with cognitive scores and clinical progression. More than 80% of amyloid-beta positive participants across diagnostic groups followed typical Braak staging, both cross-sectionally and longitudinally. Within each Braak stage, however, the pattern of abnormality demonstrated significant heterogeneity such that the overlap of abnormal regions across participants averaged less than 50%, particularly in persons with mild cognitive impairment. Accumulation of tau progressed more rapidly among cognitively unimpaired and participants with mild cognitive impairment (1.2 newly abnormal regions per year) compared to participants with Alzheimer's disease dementia (less than 1 newly abnormal region per year). Comparing the association of tau pathology and cognitive performance our spatial extent index was superior to the temporal meta-region of interest for identifying associations with memory in cognitively unimpaired individuals and explained more variance for measures of executive function in patients with mild cognitive impairments and Alzheimer's disease dementia. Thus, while participants broadly followed Braak stages, significant individual regional heterogeneity of tau binding was observed at each clinical stage. Progression of the spatial extent of tau pathology appears to be fastest in cognitively unimpaired and persons with mild cognitive impairment. Exploring the spatial distribution of tau deposits throughout the entire brain may uncover further pathological variations and their correlation with cognitive impairments., Competing Interests: The authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

In recent years, there have been increasing efforts to understand effects of prescribed fire on population dynamics of wild turkeys (Meleagris gallopavo; turkeys) in pine (Pinus spp.) forests. Although distribution of turkeys is not limited to pine forests, these forests provide nesting and brood‐rearing habitat throughout the southeastern United States. Previous studies have investigated direct (e.g., nest loss to fire) and indirect (e.g., nest‐ and brood‐site selection) effects of prescribed fire, but little is known about how turkeys are influenced by the spatial scale and shape of prescribed fire. We constructed an individual‐based model (IBM) with landscapes of 2 burn unit shapes and 17 spatial scales. We used telemetry data obtained from global positioning system‐marked female turkeys to replicate movement behaviors of turkeys within the model. We hypothesized that use of units burned during the current year (<1 yr) would decrease as scale of fires increased, and that shape of burn units would influence use by turkeys. Spatial scale most influenced turkey use; the greatest use was in burned stands of approximately 23 ha in size, whereas least use was associated with burned stands >1,269 ha. At a spatial scale of 23 ha, the daily percent use of rectangular burn units was 7% greater than square‐shaped burn units. Likewise, daily percent use of rectangular burn units was 34% greater than square‐shaped burn units at a spatial scale of 1,269 ha. When burn units were rectangular‐shaped, daily percent use decreased by 48% as the spatial extent of the fires increased from 23 ha to 203 ha. Likewise, when burn units were square‐shaped, turkey use decreased by 49% as spatial extent of fires increased from 23 ha to 203 ha. Our findings suggest the importance of managing forested landscapes with prescribed fires not exceeding approximately 200 ha if wild turkeys are a management concern. © 2020 The Wildlife Society. : Our findings suggest that predicted use by wild turkeys declined consistently as spatial scale of prescribed fires increased. We recommend that resource agencies managing upland pine forests with prescribed fire conduct burns at spatial scales ≤200 ha when possible. [ABSTRACT FROM AUTHOR]

The article attempts to indicate the hypothetical spatial extent of the process of rural gentrification. To this end, using the extended case method, the author elaborates on the rural gentrification index that has been developed by describing demographic, social, economic, and spatial changes. This approach made it possible to identify areas where the phenomenon in question is the most active. It turns out that the potential range of gentrification in Poland mainly includes counties located near large cities - especially those located in central, northern, western and, south-western parts of Poland - which could be described with the English-language term as city's countryside. [ABSTRACT FROM AUTHOR]

In the context of global warming, cold waves have generated less interest in the scientific community than heat waves, despite their impacts on public health, transport infrastructures and energy consumption. The present study analyses climate change scenarios with simulations of the EURO-CORDEX project, using the Excess Cold Factor (ECF) index for the Iberian Peninsula and Balearic Islands (IPB). The dimensions of intensity, frequency, duration and spatial extent are evaluated for the near future (2021–2050) with respect to the historical period of reference (1971–2000). The projections show a significant overall decrease in all dimensions. The mean change in maximum cold wave intensity is −50% over most of the IPB as a whole in the near future (2021–2050). The largest changes occur in the interior of the Peninsula, where the decrease is around −100%. The annual mean number of cold wave days decreases for the IPB as a whole by −50% compared to 1971–2000, with the maximum extent decreasing by more than the mean, with decreases of between −2.4%/decade and − 5.5%/decade. Although a smaller number of cold waves suggests less human exposure, the acclimatisation of the population to higher temperatures will imply that cold waves will continue to pose a serious local threat. • There are no specific studies on the intensity and spatial extent of future cold waves in the Iberian Peninsula. • The highest intensities are observed in the northeastern peninsula and mountainous areas. The maximum extent of cold waves decreases much more than the average extent. [Display omitted] • There are no specific studies on the intensity and spatial extent of future cold waves in the Iberian Peninsula. • The Excess Cold Factor directly incorporates the aspect of intensity and the acclimatisation process of the human body. • The highest intensities are observed in the northeastern peninsula and mountainous areas. • The average annual number of cold wave days in the IPB will be reduced by 50% compared to 1971–2000. • The maximum extent of cold waves decreases much more than the average extent. [ABSTRACT FROM AUTHOR]

Static indicators may fail to capture spatiotemporal differences in the spatial influence of urban features on different crime types. In this study, with a base station analogy, we introduced crime risk stations that conceptualize the spatial influence of urban features as crime risk signals broadcasted throughout a coverage area. We operationalized these risk signals with two novel risk scores, risk strength and risk intensity, obtained from novel distance-aware risk signal functions. With a crime-specific spatiotemporal approach, through a spatiotemporal influence analysis we examined and compared these risk scores for different crime types across various spatiotemporal models. Using a correlation analysis, we examined their relationships with concentrated disadvantage. The results showed that bus stops had relatively lower risk intensity, but higher risk strength, while fast-food restaurants had a higher risk intensity, but a lower risk strength. The correlation analysis identified elevated risk intensity and strength around gas stations in disadvantaged areas during late-night hours and weekends. The results provided empirical evidence for a dynamic spatial influence that changes across space, time, and crime type. The proposed risk functions and risk scores could help in the creation of spatiotemporal crime hotspot maps across cities by accurately quantifying crime risk around urban features.

The aim of the study is to analyze the occurrence of hot days and heat waves in Poland, their intra-annual distribution, and their long-term variability, and to present the circulation factors favoring the appearance of extensive waves in the country. Hot days were days with Tmax not lower than the threshold value defined by the 95th percentile of summer Tmax in the period 1961–1990. Atmospheric circulation was described using sea level pressure, geopotential of 700 and 500 hPa level, and horizontal and vertical wind on these levels. A statistically significant increase in the number of hot days in the entire study period and a significant acceleration in growth after 1980 were shown. In the entire analyzed period, only 11 waves were found covering at least 25% of the country area and lasting no less than a week. Among them, only one occurred before 1990, and more than half were observed in the last decade. Four circulation patterns favoring the extensive heat waves were distinguished differing the location of main baric center location. Spatial and temporal distribution of vertical velocity anomalies allows distinguishing clear phases of strengthening, stabilization, and weakening of anticyclone accompanying the occurrence of a heat wave.

• This study quantifies the multiscale structure of urban impervious surfaces (UIS) across space. • UIS exhibits power law scaling within local cities, but a staircase pattern beyond them. • The amount of UIS scales more tightly with urban area than with urban population size. • UIS increases faster than urban area but more slowly than urban population. • UIS can be predicted across space following a hierarchical scaling-ladder approach. Urban impervious surfaces (UIS) influence the structure and function of urban systems, and are widely considered a key indicator of urban environmental conditions. However, the amount and pattern of UIS both change with spatial scale, which complicates the computation and interpretation of UIS as an indicator. A better understanding of the spatial scaling relations of UIS is needed to resolve this predicament. Thus, the main objective of this study was to explore how UIS would change with increasing spatial extent and population size across urban hierarchical levels, using data from the three largest urban agglomerations in China. In addition, a comparative analysis of six world metropolitan regions was conducted to test the generality of the UIS scaling relations. Scalograms and standardized major axis regression were used to investigate the scaling relations with respect to spatial extent and city size, respectively. Our major findings include: (1) the total amount of UIS increased, whereas the percentage of UIS decreased, in a staircase-like fashion when the spatial extent of analysis expanded from within a local city to the entire urban agglomeration; (2) the spatial scaling of UIS followed a rather consistent and tight power law function within a local city, but became less consistent and less tight beyond a local city; (3) the scaling relations of the total amount of UIS were more consistent than those of the percentage of UIS, and the total amount of UIS scaled more tightly with urban area than with urban population size. These findings shed new light on the scale dependence of UIS, suggesting that a multiscale approach should be adopted for quantifying UIS and for using it as an urban environmental indicator. [ABSTRACT FROM AUTHOR]

Abstract Concurrent precipitation and temperature extremes usually have significant impacts on the society, economy and ecosystem. Changes in precipitation or temperature extremes in China have been extensively studied; however, less attention has been paid to their concurrence (or compound extremes) to date. This study explores the historical variations of compound extremes including dry/warm, dry/cold, wet/warm, and wet/cold combinations based on monthly precipitation and temperature observations during summer and winter from 1961 to 2014 over China. Results show that there is a significant increase in the frequency of compound dry/warm and wet/warm extremes while a decrease in compound dry/cold and wet/cold extremes for the period 1988–2014 relative to 1961–1987. In addition, statistically significant increase in the spatial extent exists in compound dry/warm and wet/warm extremes, while the areas affected by the compound dry/cold and wet/cold extremes present a decrease across China, which is shown to be partly related to the large-scale circulation patterns. The results of this study could improve our understanding of changes of compound precipitation and temperature extremes from a multivariate perspective. Graphical abstract Unlabelled Image Highlights • The frequency and spatial extent of compound extremes has changed over China. • The dry/warm and wet/warm occurrences increased in most parts of China. • The dry/cold and wet/cold occurrences decreased in most parts of China. • The spatial extent of the warm (cold) mode showed an increase (decrease). [ABSTRACT FROM AUTHOR]

Highlights • EEG-fMRI is useful to detect epileptic focus for refractory epilepsy, but is not always successful. • Number of interictal epileptic discharges is important factor to obtain significant BOLD cluster. • Widespread interictal discharges are more likely to localize the seizure onset zone than focal ones. Abstract Objective We hypothesized that the number of interictal epileptic discharges (IEDs) during scan and their spatial extent are contributing factors in obtaining appropriate activations that reveal the seizure onset zone (SOZ) in EEG-fMRI. Methods 157 IED types, each corresponding to one EEG scalp distribution, in 64 consecutive EEG-fMRI studies from 64 patients with refractory localization-related epilepsy were reviewed. To determine reliable activation, we used the threshold corresponding to corrected whole-brain topological false discovery rate (FDR). The location with maximum activation was compared to the presumed SOZ as defined by a comprehensive evaluation for each patient. Results The number of IEDs was significantly higher in the types with t -value above FDR than with t -value below FDR. The presumed SOZ could be delineated in 30 of the 64 patients. Among these patients, the types of IED concordant with the SOZ had significantly larger extent on scalp EEG than the IED types discordant with the SOZ. Conclusions The number of IEDs is important factor in obtaining reliable activations in EEG-fMRI. IEDs with larger spatial extent are more likely to reveal, on maximum BOLD, accurate location of the SOZ. Significance Widespread discharges are more likely to yield a reliable activation for SOZ in EEG-fMRI. [ABSTRACT FROM AUTHOR]

Visible, near-infrared and short-wave infrared (VNIR/SWIR, 400–2500 nm) laboratory soil spectrometry is now considered to provide accurate estimations of primary soil properties (clay, calcium carbonate, iron, soil organic carbon, etc.). The performances of primary soil property prediction models are evaluated in regard to figures of merit calculated over calibration and validation databases but not in regard to the spatial extent of predicted soil samples. The objective of this study was to analyze regional model performances for soil property prediction at regional and within-field extents within contrasted representative geopedological situations. This study used a database of 240 soil samples collected over eight vineyard fields located in the Languedoc Region (southern France) (between 20 and 36 soil samples per field) for which VNIR/SWIR laboratory spectra were acquired and two soil physico-chemical properties (clay and calcium carbonate) were measured. Soil property prediction models were built using the classical partial least square regression (PLSR) method, which links the VNIR/SWIR laboratory spectra and the physico-chemical soil property. Our results showed that both clay and calcium carbonate prediction models are accurate at the regional extent, whereas prediction model performances at the within-field extent depend on the model robustness. Therefore, primary soil properties predicted by VNIR/SWIR laboratory spectra must be used with care at different extents. [ABSTRACT FROM AUTHOR]

Widespread streamflow droughts can pose substantially greater societal challenges than spatially less extensive events because of the complex realities of trans-regional water management. In a warming climate, drought spatial extent may change along with changes in underlying hydro-meteorological contributors. Here, we assess changes in streamflow drought spatial extent over the period 1981–2018 across the conterminous United States, and how the importance of potential hydro-meteorological contributors has changed over time. We first derive a monthly time series of drought spatial extent and look at trends in streamflow drought spatial extent. We then determine the spatial percentage ‘overlap’ of precipitation droughts, temperature anomalies, snow-water-equivalent deficits, and soil moisture deficits with the area under streamflow drought to look at the changing influence of these contributors on spatial extent. Our results show that (1) the spatial extent of droughts has increased, mainly because of increases in the extent of small droughts; (2) streamflow drought extents overall substantially overlap with soil moisture deficits and the relationship of drought to precipitation and temperature anomalies varies seasonally; and (3) the importance of temperature as a contributor to drought extent has increased over time. We therefore conclude that continued global warming may further increase drought extents, requiring adaptation of regional drought management strategies.