Driver Of Disturbance Research Articles

Distinct polytropic behavior of plasma during ICME-HSS interaction

Interplanetary Coronal Mass Ejections (ICMEs) and High-Speed Streams (HSSs) are significant drivers of space disturbance in interplanetary space. The interaction between these structures can lead to various phenomena, including the generation of waves, enhanced geo-effectiveness, particle acceleration, and more. However, understanding the plasma thermodynamic properties during an ICME-HSS interaction remains an open problem. In this study, we utilize observations from STEREO and WIND to investigate the thermodynamic behavior of plasma within an ICME and a HSS. Here, we used the thermal pressure (Pth) and proton number density (Np) data from spacecraft. By fitting the linear model to the scattered data of lnPth vs lnNp we estimated the polytropic index (α). Our analysis reveals that the ICME observed before its interaction with the HSS by STEREO-A exhibits a polytropic index α∼1.0, indicating an isothermal process. Conversely, WIND observations of the same ICME before its interaction with the HSS show a nearly isothermal behavior, with α=0.7. The HSS observed by WIND demonstrates α=1.8 before its interaction with the ICME. Further analysis of WIND observations within the ICME-HSS interaction region determines a polytropic index of α=2.5. These findings suggest that the HSS region displays a nearly adiabatic behavior, the ICME region manifests closely isothermal characteristics, and the ICME-HSS interaction region exhibits super-adiabatic behavior. We propose that the expansion of ICME increases due to its propagation in the vicinity of HSS, potentially leading to additional cooling of the observed ICME magnetic cloud, which differs from the ambient solar wind.

Kinematic Differences between Gradual and Impulsive Coronal Mass Ejections: The Role of Flares

Coronal Mass Ejections (CMEs) are significant solar events that involve intense explosions of magnetic fields and mass particles out from the corona. These events are known to be the main driver of space weather and other disturbances experienced by the Earth. Generally, there are two types of CMEs – gradual and impulsive, and each type has different properties which is important to be studied on as they have potential to cause breakdowns in our systems. This study is aimed to analyze and differentiate the kinematic behavior of gradual and impulsive CME with the association of weak and strong flares. Data collection is made through SOHO LASCO catalogues and STEREO database which include velocity, acceleration and angular width as well as images. At the end of this study, it can be deduced that impulsive CME (specifically associated with strong flare) is the most prominent event that has greatest angular width and average velocity. The associated flare has contributed more heat energy to speed up the magnetic energy conversion which results to high velocity of plasma discharge. Since fast CME carries huge amount of momentum during the ejection, impulsive CMEs also experience decelerations due to loss of momentum that has been transferred to background solar wind.

Landscape configuration and storm characteristics drive spatial patterns of wind disturbance in boreal forest landscapes

ContextWind is an important disturbance in circumboreal forests, and its frequency and severity may change with climate change, highlighting the need to understand the drivers of wind disturbance. Currently, how landscape configuration drives wind disturbance is poorly understood.ObjectivesWe investigated whether and how landscape configuration is related to the extent and spatial pattern of wind disturbance, and how these relationships vary between windstorms and thunderstorms.MethodsWe used salvage logging data after 16 storms that occurred in Finland between 2011 and 2021. We placed a total of 301 landscapes, each encompassing an area of 8024 ha, within the storm tracks and used regression models to test how wind disturbance extent, disturbance patch size, number of disturbance patches, and disturbance patch clustering were related to landscape configuration and storm characteristics.ResultsIncreasing mean gap size and edge density, including permanent openings (e.g., lakes) and recent harvest gaps, increased disturbance extent, disturbance patch size, and number of disturbance patches. Conversely, increasing mean harvest gap size decreased disturbance patch clustering. Increasing wind speed had the largest contribution to increasing disturbance extent and number of disturbance patches, and decreasing disturbance patch clustering, with the magnitude of the effect varying between windstorms and thunderstorms.ConclusionsThe extent and spatial pattern of wind disturbances varied with landscape configuration and storm characteristics. Disturbance patches were larger in landscapes with large canopy gaps, resulting in a greater disturbance extent, exacerbated by increasing wind speed and thunderstorm development.

Artificial light at night drives diel activity patterns of synanthropic pipistrelle bats and their prey

The use of artificial light at night (ALAN) has increased drastically worldwide over the last decades. ALAN can have major effects on nocturnal communities, including insects and bats. Insects are attracted to street lights and few bat species take advantage of this by foraging on the attracted insects. ALAN potentially affects the temporal patterns of insect abundance and thereby bat foraging behaviour. In a natural dark environment, these patterns are usually bimodal, with an activity peak in the early evening and the morning. Little is known about how ALAN affects insect presence throughout the night, and whether the light spectrum plays a role. This is important, as these temporal changes may be a key driver of disturbances in bat-insect interactions. Here, we studied how white and red light affect insects' and bats' nightly activity patterns. The activity of insects and bats (Pipistrellus spp.) was recorded throughout the night at seven experimentally illuminated sites in a forest-edge ecosystem. ALAN disrupted activity patterns, with both insects and bats being more active throughout the night. ALAN facilitated all-night foraging in bats especially near white light, but these effects were attenuated near red light. The ability to forage throughout the night may be a key advantage causing synanthropic bats to dominate in illuminated environments, but this could also prove detrimental in the long term. As red light reduced disturbing effects of ALAN on insects and bats diel activity pattern, it opens the possibility of using spectral composition as a mitigation measure.

Enhancing individual tree mortality mapping: The impact of models, data modalities, and classification taxonomy

Tree mortality is rapidly increasing as a result of more frequent and extensive droughts and forest fires across the globe. The increasing pace and scale of disturbance and resulting mortality necessitates the study of tree mortality at the scale at which it occurs (individual trees) to develop effective management strategies. Achieving this objective requires high-resolution aerial or satellite remote sensing data supported by field validation and efficient modeling. However, the optimal remote sensing data modalities and models for mapping overstory tree mortality remain uncertain and there is a lack of benchmark datasets for reproducible research, comparison, and model improvement. In this research, we propose a framework to generate tree mortality maps at the scale of individual trees and a labeled benchmark dataset using open-source high-resolution remote sensing data. Our benchmark dataset consists of over 15,000 image crops that have been manually labeled via multi-annotator majority for live, dead, mixed, and other classes in National Ecological Observatory Network (NEON) RGB, NEON hyperspectral, and National Agriculture Imagery Program (NAIP) RGBNIR imagery. Specifically, we present a multi-class classification framework that categorizes lidar-derived tree segments as live, dead, mixed, or other. We compared the performance of different machine learning models, remote sensing data modalities and their associated spatial resolution, spectral depth, and orthorectification using our benchmark dataset. Among various models, we found Convolutional Neural Network (CNN) models outperformed all other models with the highest accuracies and F1 scores across all data modalities. Similarly, among remote sensing data modalities, NEON RGB data at 0.1 m resolution performed best due to its high spatial resolution and high quality orthorectification. The overall accuracy of 87.27% with a macro F1 score of 0.76 was achieved using the RGB data with the CNN model. Our framework can be applied to any forest ecosystem in which lidar and raster imagery are available. We applied the framework using the best performing model and data modality to produce an individual tree mortality map over the Teakettle Experimental Forest in the southern Sierra Nevada. The framework and high-resolution mortality map can be valuable resources for forest managers and provide an invaluable basis for studying potential mortality drivers of dominant trees, forest inventory, selective logging, fire disturbance, and succession modeling.

A concept elicitation study to understand the relationship between sleep and pain in rheumatoid arthritis and axial spondyloarthritis

PurposeThis qualitative study (GSK study: 213635) was designed to better understand sleep disturbance as experienced by individuals with rheumatoid arthritis (RA) or axial spondyloarthritis (axSpA), and the relationship between sleep disturbance and pain and other aspects of the disease and disease activity.MethodsSixty-minute, one-on-one, concept elicitation interviews were conducted with 30 participants (15 with RA and 15 with axSpA) from the US. Interviews were audio-recorded and transcribed verbatim. Interview transcripts were coded and analyzed to explore themes related to pain and sleep disturbance, and relationships among those themes.ResultsPain was a prominent driver of sleep disturbance; 12 participants with RA (80%) and 14 with axSpA (93%) reported that pain impacted their ability to fall asleep, while all 15 with RA (100%) and 14 with axSpA (93%) reported that pain impacted their ability to stay asleep. Two-thirds of participants with RA (67%) or axSpA (60%) described a bi-directional relationship, whereby pain worsened sleep disturbance and sleep disturbance further aggravated pain. Factors other than pain, such as fatigue and emotional health, were also reported as important contributors to sleep disturbance (RA: n = 12/15, 80%; axSpA: n = 14/15, 93%). Participants with RA or axSpA described complex interconnections between fatigue, emotional health, pain, and sleep, often labeling these relationships as “vicious cycles”. Notably, half of all participants reported sleep disturbance occurring without pain or other understood causes.ConclusionThese perspectives collected from people with RA or axSpA suggest that reducing sleep disruption directly may offer clinically relevant benefits.

Dominant species determine grazing effects on the stability of herbaceous community production at multiple scales in drylands

Abstract Sustainable provision of critical ecosystem services in drylands is reliant on their stability under anthropogenic disturbances. Livestock grazing and shrub encroachment are the primary drivers of disturbance that impact their biodiversity and production dynamics. However, the effects of grazing on the stability at multiple scales, particularly following the transition from grass‐dominated to shrub‐encroached drylands, is still largely unexplored. Here, we conducted comparable sheep‐grazing experiments in two types of drylands (grass‐dominated vs. shrub‐encroached grasslands) on the Mongolia Plateau to explore the effects of grazing and shrub encroachment on biodiversity and stability at multiple scales. We examined how grazing affected the temporal stability of aboveground biomass in herbaceous communities in both grass‐dominated and shrub‐encroached grasslands, through two potential mechanisms: insurance effects and changes in the population‐level stability of individual species. We found that an increase in sheep grazing intensity had significant and negative effects on insurance effects by decreasing both species asynchrony and spatial asynchrony but it had no effects on population stability, consequently leading to reductions in herbaceous community stability of the grasslands. However, grazing‐increased insurance effects cancelled out grazing‐decreased population stability, contributing to no changes in the community stability of shrub‐encroached grasslands. Likely, because grazing‐induced reductions in the relative abundance of the dominant species were more noticeable in shrub‐encroached grasslands than that of in grasslands. Moreover, the grazing‐decreased abundance of dominant species was directly correlated to increases in insurance effects in shrub‐encroached grasslands but not in grasslands, despite the positive relationships between population stability and the relative abundance of the dominant species in both grass‐dominated and shrub‐encroached drylands. Synthesis and applications. Our results indicate that grazing can decrease the stability of herbaceous production in drylands but this negative effect is attenuated with the transition from grasslands to shrub‐encroached grasslands, suggesting that grazing effects on herbaceous community stability can be altered by shrub encroachment in drylands. Furthermore, the stability of dominant grasses plays a crucial role in stabilizing herbaceous communities and should be considered in promoting sustainable ecosystem functioning and services in drylands.

Differences in the response to CME and CIR drivers of geomagnetic disturbances

Utilizing 1-minute resolution data on the geomagnetic indices SYM-H, AE, solar wind parameters (velocity Vsw and density Np), and z-component Bz of the interplanetary magnetic field (IMF) during solar cycles 23 and 24, we have statistically analyzed the correlations between geomagnetic activity (storms and substorms), Vsw, Np, Bz, and energy coupling functions of solar wind and Earth’s magnetosphere. For the selected 131 CME-driven storms, SYM-H stronger depends on Vsw and B than other parameters, whereas the selected 161 CIR-driven storms have nearly the same dependence on the solar wind electric field, the rate of open magnetic flux dφ/dt, and the reconnection electric field Ekl. Thus, the solar wind electric field and the dayside magnetic reconnection are likely to have different contributions for storms of the two types. During storms of different types, the substorm intensity AE relies mainly on the IMF Bz, rate of open magnetic flux and reconnection electric field.

Monitoring direct drivers of small-scale tropical forest disturbance in near real-time with Sentinel-1 and -2 data

Advancements in satellite-based forest monitoring increasingly enable the near real-time detection of small-scale tropical forest disturbances. However, there is an urgent need to enhance such monitoring methods with automated direct driver attributions to detected disturbances. This would provide important additional information to make forest disturbance alerts more actionable and useful for uptake by different stakeholders. In this study, we demonstrate spatially explicit and near real-time methods to monitor direct drivers of small-scale tropical forest disturbance across a range of tropical forest conditions in Suriname, the Republic of the Congo and the Democratic Republic of the Congo. We trained a convolutional neural network with Sentinel-1 and Sentinel-2 data to continuously classify newly detected RAdar for Detecting Deforestation (RADD) alerts as smallholder agriculture, road development, selective logging, mining or other. Different monitoring scenarios were evaluated based on varying sensor combinations, post-disturbance time periods and confidence levels. In general, the use of Sentinel-2 data was found to be most accurate for driver classifications, especially with data composited over a period of 4 to 6 months after the disturbance detection. Sentinel-1 data showed to be valuable for more rapid classifications of specific drivers, especially in areas with persistent cloud cover. Throughout all monitoring scenarios, smallholder agriculture was classified most accurately, while road development, selective logging and mining were more challenging to distinguish. An accuracy assessment throughout the full extent of our study regions revealed a Macro-F1 score of 0.861 and an Overall Accuracy of 0.897 for the best performing model, based on the use of 6-month post-disturbance Sentinel-2 composites. Finally, we addressed three specific monitoring use cases that relate to rapid law enforcement against illegal activities, ecological impact assessments and timely carbon emission reporting, by optimizing the trade-off in classification timeliness and confidence to reach required accuracies. Our findings demonstrate the strong capacities of high spatiotemporal resolution satellite data for monitoring direct drivers of small-scale forest disturbance, considering different user interests. The produced forest disturbance driver maps can be accessed via: https://bartslagter94.users.earthengine.app/view/forest-disturbance-drivers.

Forest Tent Caterpillar Outbreaks Drive Change in Ant Communities in Boreal Forests

Insect outbreaks are major drivers of natural disturbances in forest ecosystems. Outbreaks can have both direct and indirect effects on the composition of soil arthropod communities through canopy opening, nutrient addition and predator-prey interactions. In this study, we aimed to understand the effects of forest tent caterpillar (Malacosoma disstria; FTC) outbreaks through cascading effects on ant communities in both temperate and boreal forests in Canada. Pitfall traps and Berlese funnels were used to compare the ant communities, as well as the surrounding arthropod communities, between control and outbreak sites in boreal and temperate forests (in Quebec, Canada). Using the Sørensen dissimilarity index, we determined the alpha and beta diversity of the ant community. Other arthropods collected in the traps were counted to evaluate the richness and abundance of potential prey for the ants and other potential predators of the FTC. We used an indicator species analysis to examine the species associated with sites defoliated by the outbreak. In the boreal forest, we found that FTC outbreaks caused decreases in species richness and increases in the evenness of ant communities in defoliated sites. In the boreal forest sites, species composition varied significantly between control and outbreak sites. This pattern was driven in part by the presence of other predators. A similar, but weaker pattern was observed in the temperate forest. We saw no changes in the beta diversity in the boreal forest, but did see a significant decrease in the temperate forest between the outbreak sites and the control sites. Ant species in the boreal forest tended to exhibit a more marked preference for either control or previously defoliated sites than species in the temperate forest. Our study showed that disturbances such as insect outbreaks can drive changes in the ant community. While we saw small effects of outbreaks, manipulation experiments using resource addition could help us validate the mechanisms behind these relationships.

Patterns and drivers of disturbance in tropical forest reserves of southern Ghana

Ghana has retained a substantial area of tropical forests in an extensive network of protected reserves. These forests are impacted by land uses such as logging, mining, and agriculture as well as wildfires. We studied forest disturbance and recovery from 2013 to 2020 using annual maps of forest cover derived from Landsat imagery. Fire-associated disturbance was distinguished using VIIRS active fire data. We used boosted regression trees to model disturbances in closed and open forests as a function of climate variability, human accessibility, and landscape structure. A total of 3562 km2 of forest reserves were disturbed, of which 17% (615 km2) were fire disturbances and 83% (2946 km2) were non-fire disturbances. Of the total disturbed area, 68% was degradation (change from closed to open forest), 28% was open forest loss, and only 4% was closed forest loss. Over the same period, 2702 km2 of forest reserves recovered, with 1948 km2 of these recovering to closed-canopy forests. Fire disturbances were strongly associated with precipitation anomalies and occurred mostly in drier years, whereas non-fire disturbances had weaker relationships with precipitation. Disturbances in closed forests occurred in landscapes where closed forest cover was already low. In contrast, disturbances in open forests were most common in locations with intermediate levels of population pressure from nearby cities and proximity to non-forest land cover. The results support the idea that forest disturbance in Ghana is a multi-stage process involving degradation of closed forests followed by loss of the resulting open forests. Although non-fire disturbance rates are consistent from year to year, sharp increases in fire disturbance occur in drought years. Locations with the highest disturbance risk are associated with measurable indicators of climate, human pressure, and fragmentation, which can be used to identify these areas for conservation and forest restoration activities.

Spatiotemporal Variability in Disturbance Frequency and Severity across Mexico: Evidence from Conifer Tree Rings

It is critical to understand the ecological processes of forest dynamics by identifying past forest disturbances to take appropriate management actions. Tree-rings are commonly used for this purpose due to their reliability and accuracy. Here, we used a network of ring-width data distributed along a broad ecological gradient for the spatiotemporal identification of forest disturbances in 15 species of 13 sites of young Mexican conifers. We found different spatial and temporal patterns in the occurrence of forest disturbance. The species with the highest disturbance rates were Pinus patula (Ppa; El Jacalón), Pinus montezumae (Pmo; La Cueva), Pinus hartwegii (Phc; Cerro El Moro), and Pinus teocote (Pts; Rancho Joyas del Durazno) of the Gulf of Mexico, and Pinus ayacahuite (Pay; Corral de los Borregos) of the Mexico Center. The highest number of disturbances was found in 1953, 1956, 1976, and 1980; however, we noted that the number of disturbances tended to increase from 1975 to 1990 and particularly from 2000 onwards. The species close to the Gulf of Mexico presented a higher frequency and severity of disturbances than those located close to the Pacific Ocean. Thus, our results demonstrate a spatiotemporal pattern of disturbance events, which deserves further analysis, including regarding the drivers of disturbance. This knowledge is crucial for a better understanding of the dynamics of contemporary species.

Gut Microbiome-Host Metabolome Homeostasis upon Exposure to PFOS and GenX in Male Mice

Alterations of the normal gut microbiota can cause various human health concerns. Environmental chemicals are one of the drivers of such disturbances. The aim of our study was to examine the effects of exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS)-specifically, perfluorooctane sulfonate (PFOS) and 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy) propanoic acid (GenX)-on the microbiome of the small intestine and colon, as well as on liver metabolism. Male CD-1 mice were exposed to PFOS and GenX in different concentrations and compared to controls. GenX and PFOS were found to have different effects on the bacterial community in both the small intestine and colon based on 16S rRNA profiles. High GenX doses predominantly led to increases in the abundance of Clostridium sensu stricto, Alistipes, and Ruminococcus, while PFOS generally altered Lactobacillus, Limosilactobacillus, Parabacteroides, Staphylococcus, and Ligilactobacillus. These treatments were associated with alterations in several important microbial metabolic pathways in both the small intestine and colon. Untargeted LC-MS/MS metabolomic analysis of the liver, small intestine, and colon yielded a set of compounds significantly altered by PFOS and GenX. In the liver, these metabolites were associated with the important host metabolic pathways implicated in the synthesis of lipids, steroidogenesis, and in the metabolism of amino acids, nitrogen, and bile acids. Collectively, our results suggest that PFOS and GenX exposure can cause major perturbations in the gastrointestinal tract, aggravating microbiome toxicity, hepatotoxicity, and metabolic disorders.

Monitoring shifting cultivation in Laos with Landsat time series

Shifting cultivation is an agricultural practice in which plots of land are cultivated temporarily, then abandoned, and vegetation is allowed to regenerate during fallow periods. Shifting cultivation is usually associated with cutting and burning forests and thus it is an important driver of forest disturbance in the tropics. However, studies of shifting cultivation are limited, and current area estimates of shifting cultivation are highly uncertain. Although Southeast Asia is a hotspot of shifting cultivation, there are no national maps of shifting cultivation in Southeast Asia at moderate or high resolution (less than or equal to 30 m). Monitoring shifting cultivation is challenging because it is highly dynamic, small-scale and results in complex post-disturbance landscapes. In this study, we monitored shifting cultivation using Landsat time series on Google Earth Engine for the entire country of Laos from 1991 to 2020. First, CCDC-SMA (Continuous Change Detection and Classification - Spectral Mixture Analysis) was used to detect forest disturbances. Then, these disturbances were attributed by combining time series analysis, object-based image analysis (OBIA), and post-disturbance land cover classification. Forest disturbances were assigned to Shifting cultivation, New plantation, Deforestation, Severe Drought, and Subtle Disturbance annually from 1991 to 2020 at a 30-m resolution. The major forest disturbances in 1991–2020 were mapped with an overall accuracy of 85%. Shifting cultivation is mapped with a producer's accuracy of 88% and a user's accuracy of 80%. The margin of error of the sampling-based area estimates of Shifting cultivation is 5.9%. Shifting cultivation is the main land use in Laos, accounting for 32.9% ± 1.9% of Laos over the past 30 years. To study changes in shifting cultivation over time, the area of shifting cultivation was estimated at 5-year intervals between 1991 and 2020 with all margins of error <17%. Results show that the area of slash-and-burn activities in Laos increased in 2015–2020. Our study provides an effective approach for monitoring shifting cultivation, which can be potentially applied into other regions. Our results not only provide valuable information for land management in Laos, but also can support analysis of spatial-temporal patterns of shifting cultivation and estimation of carbon emissions associated with shifting cultivation for REDD+ reporting.

Multispectral Spaceborne Proxies of Predisposing Forest Structure Attributes to Storm Disturbance—A Case Study from Germany

Windstorms are among the primary drivers of forest disturbances. Although they are inherent part of the natural ecosystem processes, they severely impact managed forests. Modeling approaches serve as key tools for the evaluation of disturbance risk and different predisposing factors. However, data availability on relevant forest attributes can be problematic on a larger scale. While spaceborne remote sensing has already proven itself as a tool for disturbance detection, its use in relation to predisposing forest attributes remains underexploited. The present work explores multispectral object-based proxy predictors for statistical wind disturbance modeling based on the publicly available Sentinel-2 imagery and recorded damage polygons from the pan-European FORWIND database. Potential predictors were tested in logistic and random forests (RF) regression models for both disturbance occurrence and severity for a case study of a major storm event in Northern Germany from 2017. The results reveal a general potential of the derived spaceborne variables to be used as proxy variables to critical predisposing forest attributes. The presented proxy variables also outperformed a set of publicly available derived spatial data products for modeling both disturbance occurrence and severity. Model accuracies were moderate (reaching AUC = 0.76 for logistic regression fit and AUC = 0.69 for predictive accuracy of RF models), yet falling within the range of reported results in previous studies from the field. Limitations of the spectral satellite imagery as a single information source were acknowledged; however, the results indicate the further potential of spaceborne imagery applications in disturbance modeling, assessment and resulting mapping of disturbance susceptibility at different spatial scales. Considering the growing spatiotemporal availability of high-resolution spaceborne data, we propose that a model representation of post-disturbance forest patterns could improve the understanding of complex disturbance regimes and recurrent susceptibility.

Improving CME evolution and arrival predictions with AMR and grid stretching in Icarus

Context.Coronal mass ejections (CMEs) are one of the main drivers of disturbances in interplanetary space. Strong CMEs, when directed towards the Earth, cause geomagnetic storms upon interacting with the Earth’s magnetic field, and can cause significant damage to our planet and affect everyday life. As such, efficient space weather prediction tools are necessary to forecast the arrival and impact of CME eruptions. Recently, a new heliospheric model called Icarus was developed based on MPI-AMRVAC, which is a 3D ideal magnetohydrodynamics model for the solar wind and CME propagation, and it introduces advanced numerical techniques to make the simulations more efficient. In this model the reference frame is chosen to be co-rotating with the Sun, and radial grid stretching together with adaptive mesh refinement (AMR) can be applied to the numerical domain.Aims.Grid stretching and AMR speed up simulation results and performance. Our aim is to combine the advanced techniques available in the Icarus model in order to obtain better results with fewer computational resources than with the equidistant grid. Different AMR strategies are suggested, depending on the purpose of the simulation.Methods.In this study, we model the CME event that occurred on July 12, 2012. A cone model was used to study the CME’s evolution through the background solar wind, and its arrival at and impact with the Earth. Grid stretching and AMR were combined in the simulations by using multiple refinement criteria, to assess its influence on the simulations’ accuracy and the required computational resources. We compare simulation results to the EUHFORIA model.Results.We applied different refinement criteria to investigate the potential of solution AMR for different applications. As a result, the simulations were sped up by a factor of ∼17 for the most optimal configuration in Icarus. For the cone CME model, we found that limiting the AMR to the region around the CME-driven shock yields the best results. The results modelled by the simulations with radial grid stretching and AMR level 4 are similar to the results provided by the original EUHFORIA and Icarus simulations with the ‘standard’ resolution and equidistant grids. The simulations with 5 AMR levels yielded better results than the simulations with an equidistant grid and standard resolution.Conclusions.Solution AMR is flexible and provides the user the freedom to modify and locally increase the grid resolution according to the purpose of the simulation. We find that simulations with a combination of grid stretching and AMR can reproduce the simulations performed on equidistant grids significantly faster. The advanced techniques implemented in Icarus can be further used to improve the forecasting procedures, since the reduced simulation time is essential to make physics-based forecasts less computationally expensive.

Fire Severity Causes Temporal Changes in Ground-Dwelling Arthropod Assemblages of Patagonian Araucaria–Nothofagus Forests

Fire is one of the main drivers of anthropogenic disturbances in temperate forest ecosystems worldwide, with multiple effects spread across ecological networks. Nevertheless, the biodiversity effects of fire are poorly known for species-diverse groups such as arthropods. In this research, we used a burn gradient generated two and three years after a large fire event to assess how different levels of fire severity affect arthropod diversity in the forest with the main forest forming long-living tree species Araucaria araucana, in southern Chile. The species richness and abundance of arthropods among trophic guilds was estimated annually in four fire-severity levels. We found that arthropods responded differently to fire severity levels, depending on their trophic guilds and years after fire (two and three years after fire). During the second year after fire, zoophages, phytophages, and parasitoids were more diverse in areas with high fire severity within the second year after fire, as compared to those in areas with low severity or unburned stands. In the third year after fire, a change in this trend was observed, where the abundance of all groups dropped significantly, with positive changes in the diversity in zoophages, phytophages, polyphages and saprophages, which is more noticeable in sites with high severity. These results indicate that annual variation in environmental conditions triggers bottom-up cascading effects for arthropods. Forests stands severely impacted by fires support highly fluctuating and possibly unstable arthropod assemblages. Hence, restoration efforts should be focused on recovering microhabitat conditions in these stands to allow the persistence of arthropods.

Mining the drivers of forest cover change in the upper Indus Valley, high Asia region from 1990 to 2020

The high Asia region is the water tower for many river valleys in East and South Asia, which has vital significance for regional environmental conservation and ecological security. In the upper Indus Valley, the role of forests is often overlooked, and their loss will lead to a reduction in ecological services, such as water conservation and disaster prevention, and will indirectly affect the water and food security of 230 million people in South Asia. Quantifying the drivers of forest cover change is a prerequisite for ensuring sustainable development in the upper Indus Valley. This study used forest disturbance and recovery data, history fire data, topographic data, and land use data to construct a decision tree model for mining the of drivers of forest cover change. Classification of the drivers of forest disturbance and recovery was achieved in the upper Indus Valley. The results showed that (1) disturbance mainly occurred in the central region of the upper Indus Valley, where forest degradation was the main driver accounting for 69.0%, and agricultural transfer was the secondary driver accounting for 21.6%; commercial cultivation and deforestation drivers both disturbed about 4% of the area, and fire, human activities, and natural hazards disturbed only a small area of forest accounting for less than 1%; (2) the spatial distribution of recovery was basically consistent with the disturbance, with natural recovery being the main driver of forest recovery, accounting for 60.1%, and artificial recovery being the secondary driver, accounting for 39.9%; (3) relevant governance measures or forest conversation policies in the Indus Valley were recommended, such as increasing the supply of non-biomass energy, controlling the scale of livestock, and establishing friendly land use policies, to maintain the growth and balance of forest area and quality.

Dynamics of Large-Scale Solar-Wind Streams Obtained by the Double Superposed Epoch Analysis: 5. Influence of the Solar Activity Decrease

In solar cycles 23–24, solar activity noticeably decreased and, as a result, solar wind parameters decreased. Based on the measurements of the OMNI base for the period 1976–2019, the time profiles of the main solar wind parameters and magnetospheric indices for the main interplanetary drivers of magnetospheric disturbances (solar wind types CIR. Sheath, ejecta and MC) are studied using the double superposed epoch method. The main task of the research is to compare time profiles for the epoch of high solar activity at 21–22 SC and the epoch of low activity at 23–24 SC. The following results were obtained. (1) The analysis did not show a statistically significant change in driver durations during the epoch of minimum. (2) The time profiles of all parameters for all types of SW in the epoch of low activity have the same shape as in the epoch of high activity, but locate at lower values of the parameters. (3) In CIR events, the longitude angle of the solar wind flow has a characteristic S shape; but in the epoch of low activity, it varies in a larger range than in the previous epoch.

Artificial light at night (ALAN) affects behaviour, but does not change oxidative status in freshwater shredders

Artificial light at night (ALAN) alters circadian rhythms in animals and therefore can be a source of environmental stress affecting their physiology and behaviour. The impact of ALAN can be related to the increased light level, but also to the spectral composition of night lighting. Previous research showed that many species can be particularly sensitive to the LED light, but it is unclear if they respond to its broad spectrum or specifically to the blue light wavelength. In this study, we tested whether dim ALAN (2 lx) differing in the spectral quality (warm white LED, blue LED, high-pressure sodium HPS light) modifies behaviour and changes oxidative status in two nocturnal freshwater shredder species: Dikerogammarus villosus and Gammarus jazdzewskii (Gammaroidea, Amphipoda). Our experiment revealed that ALAN, irrespective of its spectral quality, did not affect the oxidative stress markers in cells (the level of reactive oxygen species and lipid peroxidation). However, ALAN changed the gammarid behaviour in a species-specific manner, which can potentially reduce the fitness of the shredders. Dikerogammarus villosus avoided all types of light compared to darkness. Therefore, confined to the shelter, D. villosus may have fewer opportunities to forage and/or mate. Gammarus jazdzewskii was sensitive only to the narrow-spectrum blue light, but did not respond to the HPS and white LED light. Avoidance is a typical response of gammarids to natural light, thus the disruption of this behaviour in the presence of common ALAN sources can increase the predation risk in this species. To summarize, behavioural modifications induced by ALAN seem more pronounced than changes in physiology and can constitute the main driver of disturbances in the processing of organic matter in freshwater ecosystems by invertebrate shredders.