Disturbance Events Research Articles

Inferring microalgae density and net ecosystem production on soft sediments using infrared imaging

AbstractMeasuring microalgae density in soft‐sediment benthos has challenges for even the most sophisticated methods. If the goal is to assess the photosynthetic potential of epipelon, then microalgae should be sampled only at the surface of the benthos to the depth of light penetration. Furthermore, microalgae density may show spatial and temporal variability that can only be captured by using many point samples and nondestructive sampling. Here, we use simple near‐infrared (NIR) imagery to assess surface density of microalgae in soft underwater sediments and to infer their photosynthetic capacity. In lab studies, NIR imagery gives estimates of epipelon density that are strongly correlated with standard chlorophyll a (Chl a) assays using pigment extraction and fluorometry ( = 0.70), but NIR imagery is better able to separate experimental treatments. In analyses of sediment samples from a lake, NIR imagery gives estimates of epipelon Chl a density that are strongly correlated to net ecosystem production (NEP). Near‐infrared imagery also gives a fine‐grained assessment of the spatial distribution of epipelon that helps to explain the relationship between epipelon density and NEP. Finally, images from an underwater NIR camera over the course of a wind disturbance event give estimates of the relative density of microalgae that is buried and is likely to be, at least temporarily, photosynthetically inactive. These results show that NIR imagery provides an easy and nondestructive method for sampling surface densities of microalgae which is particularly suitable for remote field locations and for educational settings in which students can generate results with cheap and robust equipment.

Legacies of a Large Flood and Biological Control on Riparian Vegetation Successional Trajectories Along a Dryland Braided River

ABSTRACTThe interplay of disturbance and stability drives vegetation dynamics. Disturbance reduces vegetation biomass, and stability fosters its development. In riparian systems, natural disturbance is largely manifested through flood‐driven fluvial processes, but other forms of disturbance, such as herbivory or fire, may influence vegetation dynamics. We studied the successional trajectories of plant communities following a 40‐year flood in 2010 that significantly changed floodplain vegetation along the lower Virgin River (southwestern USA). Shortly (0–2 years) after this flood, another large disturbance event of a different nature occurred: extensive defoliation and some mortality of alien Tamarix shrubs (which dominated vegetation cover at that time in the study area) by a biological control beetle. In 2021, we resampled vegetation and topography in 439 plots that we previously monitored in 2010, 2012, 2015, and 2017 along 23 transects across five river reaches. Between 2015 and 2021, stability predominated, with only small floods (1.5‐ to 3‐year) and limited Tamarix defoliation. By 2021, plant communities were converging, but persistent divergences existed and were associated with legacy effects of fluvial disturbance and defoliation. Native Pluchea sericea shrubs had the highest cover across all fluvial landforms. Tamarix partially recovered from defoliation, but only reached similar cover to P. sericea in plots less affected by the 40‐year flood. Native Populus fremontii, Prosopis pubescens, and Salix gooddingii trees, and Salix exigua shrubs, remained subordinate. Our study illustrates how successional trajectories in riparian systems depend on the nature and regime of disturbance and its legacy effects on vegetation.

A Sentinel-2 machine learning dataset for tree species classification in Germany

Abstract. We present a machine learning dataset for tree species classification in Sentinel-2 satellite image time series of bottom-of-atmosphere reflectance. It is geared towards training classifiers but is less suitable for validating the resulting maps. The dataset is based on the German National Forest Inventory of 2012 as well as analysis-ready satellite imagery computed using the Framework for Operational Radiometric Correction for Environmental monitoring (FORCE) processing pipeline. From the National Forest Inventory data, we extracted the tree positions, filtered 387 775 trees in the upper canopy layer, and automatically extracted the corresponding bottom-of-atmosphere reflectance time series from Sentinel-2 L2A images. These time series are labeled with the corresponding tree species, which allows pixel-wise classification tasks. Furthermore, we provide auxiliary information such as the approximate tree position, the year of possible disturbance events, or the diameter at breast height. Temporally, the dataset spans the years from July 2015 to the end of October 2022, with approx. 75.3 million data points for trees of 48 species and 3 species groups as well as 13.8 million observations for non-tree backgrounds. Spatially, it covers the whole of Germany. The dataset is available at the following DOI (Freudenberg et al., 2024): https://doi.org/10.3220/DATA20240402122351-0.

Browning events in Arctic ecosystems: Diverse causes with common consequences

Arctic ecosystems are experiencing extreme climatic, biotic and physical disturbance events that can cause substantial loss of plant biomass and productivity, sometimes at scales of >1000 km2. Collectively known as browning events, these are key contributors to the spatial and temporal complexity of Arctic greening and vegetation dynamics. If we are to properly understand the future of Arctic terrestrial ecosystems, their productivity, and their feedbacks to climate, understanding browning events is essential. Here we bring together understanding of browning events in Arctic ecosystems to compare their impacts and rates of recovery, and likely future changes in frequency and distribution. We also seek commonalities in impacts across these contrasting event types. We find that while browning events can cause high levels of plant damage (up to 100% mortality), ecosystems have substantial capacity for recovery, with biomass largely re-established within five years for many events. We also find that despite the substantial loss of leaf area of dominant species, compensatory mechanisms such as increased productivity of undamaged subordinate species lessen the impacts on carbon sequestration. These commonalities hold true for most climatic and biotic events, but less so for physical events such as fire and abrupt permafrost thaw, due to the greater removal of vegetation. Counterintuitively, some events also provide conditions for greater productivity (greening) in the longer-term, particularly where the disturbance exposes ground for plant colonisation. Finally, we find that projected changes in the causes of browning events currently suggest many types of events will become more frequent, with events of tundra fire and abrupt permafrost thaw expected to be the greatest contributors to future browning due to their severe impacts and occurrence in many Arctic regions. Overall, browning events will have increasingly important consequences for ecosystem structure and function, and for feedback to climate.

Intelligent active and reactive power control using multi-layer neural network based MPPT controller for grid tied solar PV system under fault conditions

The integration of renewable energy sources, particularly grid-tied solar photovoltaic (PV) systems, into the modern power grid has become increasingly prevalent. However, ensuring the reliable and efficient operation of grid-tied PV systems under various grid conditions, including fault scenarios, poses a significant challenge. In the event of grid faults or disturbances, traditional control methods often fall short in maintaining stable and reliable operation. This paper introduces a multi-layer neural network (MLNN) based MPPT controller that adapts intelligently to grid fault conditions, mitigating the impact on the grid-tied PV system's performance and providing low voltage ride through (LVRT). The research employs a detailed simulation framework on MATLAB to validate the effectiveness of the proposed controller under fault conditions. The LVRT capability of the designed system was analyzed and validated according to Indian grid code. The proposed controller leverages its capacity to learn and make real-time decisions to optimize the active and reactive power outputs of the PV system as per the grid code. Simulation results demonstrate that the proposed controller not only improves the fault tolerance of grid-tied PV systems but also enhances their performance, ensuring a stable and continuous power supply in the face of grid disturbances.

Using Community Composition and Successional Theory to Guide Site-Specific Coral Reef Management.

High spatial or temporal variability in community composition makes it challenging for natural resource managers to predict ecosystem trajectories at scales relevant to management. This is commonly the case in nearshore marine environments, where the frequency and intensity of disturbance events vary at the sub-kilometer to meter scale, creating a patchwork of successional stages within a single ecosystem. The successional stage of a community impacts its stability, recovery potential, and trajectory over time in predictable ways. Here we demonstrate the value of successional theory for interpreting fine-scale community heterogeneity using Hawaiian coral reefs as a case study. We tracked benthic community dynamics on 36 forereefs over a 6-year period (2017-2023) that captures impacts from high surf events, a marine heatwave, and unprecedented shifts in human behavior due to the COVID-19 pandemic. We document high spatial variation in benthic community composition that was only partially explained by island and environmental regime. Through hierarchical clustering, we identify three distinct community types that appear to represent different successional stages of reef development. Reefs belonging to the same community type exhibited similar rates of change in coral cover and structural complexity over time, more so than reefs located on the same island. Importantly, communities that were indicative of early succession (low coral cover reefs dominated by stress-tolerant corals) were most likely to experience an increase in coral cover over time, while later-stage successional communities were more likely to experience coral decline. Our findings highlight the influence of life history and successional stage on community trajectories. Accounting for these factors, not simply overall coral cover, is essential for designing effective management interventions. Site-specific management that accounts for a community's unique composition and history of disturbance is needed to effectively conserve these important ecosystems.

An ecological-evolutionary perspective on the genomic diversity and habitat preferences of the Acidobacteriota.

Members of the phylum Acidobacteriota inhabit a wide range of ecosystems including soils. We analysed the global patterns of distribution and habitat preferences of various Acidobacteriota lineages across major ecosystems (soil, engineered, host-associated, marine, non-marine saline and alkaline and terrestrial non-soil ecosystems) in 248 559 publicly available metagenomic datasets. Classes Terriglobia, Vicinamibacteria, Blastocatellia and Thermoanaerobaculia were highly ubiquitous and showed a clear preference to soil over non-soil habitats, while classes Aminicenantia and Holophagae showed preferences to non-soil habitats. However, while specific preferences were observed, most Acidobacteriota lineages were habitat generalists rather than specialists, with genomic and/or metagenomic fragments recovered from soil and non-soil habitats at various levels of taxonomic resolution. Comparative analysis of 1930 genomes strongly indicates that phylogenetic affiliation plays a more important role than the habitat from which the genome was recovered in shaping the genomic characteristics and metabolic capacities of the Acidobacteriota. The observed lack of strong habitat specialization and habitat-transition-driven lineage evolution in the Acidobacteriota suggest ready cross-colonization between soil and non-soil habitats. We posit that such capacity is key to the successful establishment of Acidobacteriota as a major component in soil microbiomes post-ecosystem disturbance events or during pedogenesis.

A Dynamic Scheduling Method Combining Iterative Optimization and Deep Reinforcement Learning to Solve Sudden Disturbance Events in a Flexible Manufacturing Process

Unpredictable sudden disturbances such as machine failure, processing time lag, and order changes increase the deviation between actual production and the planned schedule, seriously affecting production efficiency. This phenomenon is particularly severe in flexible manufacturing. In this paper, a dynamic scheduling method combining iterative optimization and deep reinforcement learning (DRL) is proposed to address the impact of uncertain disturbances. A real-time DRL production environment model is established for the flexible job scheduling problem. Based on the DRL model, an agent training strategy and an autonomous decision-making method are proposed. An event-driven and period-driven hybrid dynamic rescheduling trigger strategy (HDRS) with four judgment mechanisms has been developed. The decision-making method and rescheduling trigger strategy solve the problem of how and when to reschedule for the dynamic scheduling problem. The data experiment results show that the trained DRL decision-making model can provide timely feedback on the adjusted scheduling arrangements for different-scale order problems. The proposed dynamic-scheduling decision-making method and rescheduling trigger strategy can achieve high responsiveness, quick feedback, high quality, and high stability for flexible manufacturing process scheduling decision making under sudden disturbance.

Too hot to handle? The impact of the 2023 marine heatwave on Florida Keys coral

The summer 2023 marine heatwave was the most severe on record for Florida’s Coral Reef, with unprecedented water temperatures and cumulative heat stress leading to 100% coral bleaching. An existing fate-tracking program of over 4200 brain and boulder coral colonies across five offshore and four inshore reefs allowed for analyses of bleaching-related mortality and diseases through the event. Across the vast majority of assessed corals, there was no partial or full mortality as a result of the 2023 bleaching event. At seven of the nine sites, only 0 – 2% of fate-tracked colonies experienced any mortality. The other two sites, both inshore, had the highest cumulative heat stress and did experience substantial bleaching-related mortality. However, acute mortality at one of them began at relatively low cumulative heat stress, suggesting death was the result of exceeding thermal maxima rather than bleaching-related resource depletion. At the two most impacted sites, 43% and 30% of all monitored corals died, but mortality varied among species: brain corals fared worse than boulder corals. The health status of corals before the bleaching event had little impact on whether they exhibited mortality during the event. At three sites, we observed unusual lesions on Orbicella faveolata colonies shortly after color returned to the corals; these were only present for a few months, but on some colonies led to substantial tissue loss. Though not part of the monitoring program, we also observed local extinctions of Acroporid corals at most sites, as well as local extinctions of octocorals at three inshore reefs. Though most reef-building corals survived the 2023 marine heatwave in the Florida Keys, continually rising temperatures are likely to make these temperature regimes more common. We encourage future research on why the brain and boulder corals fared differently at highly-impacted sites, and on what the unusual O. faveolata lesions are. Our results also provide perspective on how restoration strategies, particularly those focused on species likely to die under current and future climate regimes, might prioritize species likely to survive. Finally, these results highlight the importance of fate-tracking individuals of different species and in different geographies and habitat types through disturbance events.

Influence of preoperative comprehensive education on anxiety, depression, pain, and sleep in elderly patients operated under general anesthesia.

Owing to the particularities of their physical characteristics, older patients undergoing surgery under general anesthesia experience great surgical traumas. Thus, exploring more refined and individualized nursing approaches is an urgent need to mitigate the negative effects of surgery on such patients. To analyze the influence of preoperative comprehensive education on anxiety, depression, pain, and sleep in older patients who underwent surgery under general anesthesia. In total, 163 older adults who underwent surgery under general anesthesia between June 2022 and November 2023 were selected, 77 of them received routine nursing care (control group), and 86 received preoperative comprehensive education (research group). Subsequently, comparative analyses were performed from the following perspectives: Surgical indicators (operation time, time to complete regain of consciousness, and temperature immediately after the procedure and upon recovery from anesthesia) before and after nursing care; negative emotions [self-rating anxiety scale (SAS)/self-rating depression scale (SDS)]; pain severity [visual analog scale (VAS)]; sleep quality [Pittsburgh sleep quality index (PSQI)]; incidence of sleep disturbances (difficulties in falling asleep for the first time, falling asleep again after waking up frequently at night, falling asleep again after waking up early, and falling asleep all night); and incidence of adverse events (airway obstruction, catheter detachment, aspiration, and asphyxia). The research group had significantly lower operation time and time to complete regain of consciousness than the control group after nursing care and markedly better recovery of postoperative body temperature and body temperature at awakening. In addition, more notable decreases in SAS, SDS, VAS, and PSQI scores were observed in the research group than in the control group. Furthermore, the incidence rate of sleep disturbance (8.14% vs 29.87%) and adverse events (4.65% vs 19.48%) were lower in the research group than in the control group. Preoperative comprehensive education in older patients who underwent surgery under general anesthesia can improve postoperative indicators, effectively reduce the occurrence of anxiety and depression, alleviate postoperative pain, and improve sleep quality.

Occurrence records and taxonomic voucher specimens for study of wild bee communities in early seral forests generated by wildfire, post-fire salvage logging, and intensive forest management in southwest Oregon

Early seral forests regenerating after stand-replacing disturbance events can provide important habitat for populations of wild bees, an important group of pollinating insects. However, variability in the abundance and diversity of wild bee communities across different types of early seral forests is poorly understood, and can inform pollinator conservation efforts and sustainable forest management practices. In this study, we compared wild bee assemblages from early seral forests regenerating from three widespread stand-replacing disturbances across a gradient in stand ages in the Klamath Ecoregion of southwest Oregon using blue vane traps. Here, we present occurrence data for each bee specimen observed in the study, including voucher specimens deposited to the Oregon State Arthropod Collection.

Occurrence records and taxonomic voucher specimens for study of wild bee communities in early seral forests generated by wildfire, post-fire salvage logging, and intensive forest management in southwest Oregon

Early seral forests regenerating after stand-replacing disturbance events can provide important habitat for populations of wild bees, an important group of pollinating insects. However, variability in the abundance and diversity of wild bee communities across different types of early seral forests is poorly understood, and can inform pollinator conservation efforts and sustainable forest management practices. In this study, we compared wild bee assemblages from early seral forests regenerating from three widespread stand-replacing disturbances across a gradient in stand ages in the Klamath Ecoregion of southwest Oregon using blue vane traps. Here, we present occurrence data for each bee specimen observed in the study, including voucher specimens deposited to the Oregon State Arthropod Collection.

Disturbance drives concordant functional biodiversity shifts across regions: new evidence from river eDNA

Major disturbance events can profoundly influence biodiversity patterns, although the extent to which such shifts are predictable remains poorly understood. We used environmental DNA (eDNA) to compare forested versus recently deforested stream insect communities across disjunct regions of New Zealand, to test for parallel shifts in response to widescale disturbance. Although eDNA analyses revealed highly distinct species pools across regions, they detected concordant functional diversity shifts linked to recent deforestation, including parallel decreases in the diversity of grazing taxa. The finding that taxonomically distinct freshwater biotas have experienced broadly concordant functional shifts in the wake of deforestation indicates that disturbance can drive deterministic ecological change. By contrast, the finding that some closely related species within functional groups show discordant responses to deforestation suggests that ecological differentiation among cryptic taxa may contribute to idiosyncratic shifts. These findings highlight the potential of eDNA for resolving subtle species‐level differences among anthropogenically impacted ecological assemblages.

Synthesis and Perspectives on Disturbance Interactions, and Forest Fire Risk and Fire Severity in Central Europe

Wildfire risk increases following non-fire disturbance events, but this relationship is not always linear or cumulative, and previous studies are not consistent in differentiating between disturbance loops versus cascades. Previous research on disturbance interactions and their influence on forest fires has primarily focused on fire-prone regions, such as North America, Australia, and Southern Europe. In contrast, less is known about these dynamics in Central Europe, where wildfire risk and hazard are increasing. In recent years, forest disturbances, particularly windthrow, insect outbreaks, and drought, have become more frequent in Central Europe. At the same time, climate change is influencing fire weather conditions that further intensify forest fire dynamics. Here, we synthesize findings from the recent literature on disturbance interactions in Central Europe with the aim to identify disturbance-driven processes that influence the regional fire regime. We propose a conceptual framework of interacting disturbances that can be used in wildfire risk assessments and beyond. In addition, we identify knowledge gaps and make suggestions for future research regarding disturbance interactions and their implications for wildfire activity. Our findings indicate that fire risk in the temperate forests of Central Europe is increasing and that non-fire disturbances and their interactions modify fuel properties that subsequently influence wildfire dynamics in multiple ways.

Research on prediction of high energy microseismic events in rock burst mines based on BP neural network

In response to the frequent occurrence of high-energy microseismic events in coal mines in China, a back propagation neural network (BPNN) prediction model based on surface subsidence data has been proposed to provide a basis for safely and efficiently predicting coal mine disasters. Theoretical research on the relationship between surface displacement, mining disturbance, and high-energy microseismic event levels has demonstrated a significant correlation among these factors. When there is a sudden increase or decrease in surface displacement or mining disturbance, the advancing working face typically exhibits dynamic characteristics. Therefore, feature parameters relevant to predicting high-energy microseismic event levels were selected as input variables for the BPNN model. Raw data from 88 sets of microseismic events in the 301 working face of the third mining area of a certain coal mine in Inner Mongolia were extracted. First, outlier preprocessing was conducted to obtain a complete dataset, which is then divided into a training set and a testing set. The BPNN model was trained with the training set and subsequently tested to evaluate its predictive performance. Finally, by comparing several model evaluation metrics, it was found that the BPNN model outperforms other common models in predicting high-energy events. The overall prediction accuracy is 86.4%, and the root mean square error (RMSE) is 0.45, indicating that the BPNN-based prediction model for high-energy microseismic events in coal mines is feasible.

Current Insight: Habitat mosaic and landscape ecological services mapping based on local community knowledge in Karuing Village, Katingan Regency, Central Kalimantan

Abstract Habitat mosaic is an ecological phenomenon in which different habitats are found close together in varying patch sizes. This phenomenon is caused by environmental heterogeneity and disturbance events, both natural and anthropogenic. This anthropogenic disturbance cannot be separated from the existence of local communities that utilize its ecological services for their survival. Karuing Village is a village on the banks of the Katingan River in Katingan Regency, Central Kalimantan. The village landscape is surrounded by rivers and streams as well as forest ecosystems. The people of Karuing village have lived by utilizing ecological services for many years, especially aquatic resources from fishing. As time goes by, climate change occurs, causing shifts in the habitat mosaic and allowing new habitat patches to form. This research aims to map the habitat mosaic based on local knowledge of the community in Karuing Village, Katingan Regency, Central Kalimantan. In addition, this research also explores its potential as an ecological service that can be utilized by local communities. The results of this study provide the latest insight into the habitat mosaic and its ecological services in Karuing Village, Katingan Regency, Central Kalimantan, as a basis for conservation management plans and recommendations.

Assessing the effect of tissue and fire‐response traits on plant growth rates post‐disturbance in eastern Australia

Abstract Variation in plant growth strategies facilitate species' coexistence in a community. Some functional traits are predicted to influence the growth rates of developing individuals by capturing trade‐offs in resource allocation. However, despite being used broadly in community ecology, the assumed generality and predictability of trait‐growth relationships lack widespread empirical testing. The megafires of 2019–2020 burned extensive areas throughout New South Wales and were followed by high rainfall, causing the large‐scale synchronous regeneration of fire‐adapted species. We took advantage of this mass disturbance event to test hypothesised relationships between functional traits and growth across six spatially distributed sclerophyllous systems throughout NSW, in which sampled vegetation was part of the same growth cohort. We investigated whether resprouting as a trait facilitated faster initial height growth compared to reseeding and, in reseeding species, tested whether the effects of four structural functional traits—stem specific density (SSD), leaf nitrogen per area, standardised stem diameter and specific leaf area (SLA)—on height growth rates followed directions predicted by theory. Resprouters grew an average of 25.92 cm year−1 more than reseeders at 14–15 months post‐fire, indicating an advantage in light capture over reseeding species in the period soon after fire. Of the four structural functional traits tested, SSD and leaf nitrogen per area displayed evidence of relationships with height growth rate, while standardised stem diameter and SLA had no evidence of an effect. These relationships were consistent across sites. Our results indicate that (i) ontogenetic variation in growth rates should be integrated into the fast‐slow growth economics spectrum and that (ii) while some functional traits predict height growth, this is not a guarantee for all traits. Read the free Plain Language Summary for this article on the Journal blog.

Aggregative responses of marine predators to a pulsed resource.

Pulsed resources resulting from animal migrations represent important, transient influxes of high resource availability into recipient communities. The ability of predators to respond and exploit these large increases in background resource availability, however, may be constrained when the timing and magnitude of the resource pulse vary across years. In coastal Newfoundland, Canada, we studied aggregative responses of multiple seabird predators to the annual inshore pulse of a key forage fish species, capelin (Mallotus villosus). Seabird aggregative responses to fish biomass were quantified from weekly hydroacoustic and seabird surveys during July-August within an annually persistent foraging area (10 km2) associated with a cluster of capelin spawning sites across 10 years (2009-2010, 2012, 2014-2020). Seabird predators included breeding members of the families Alcidae (Common Murres Uria aalge, Razorbills Alca torda, Atlantic Puffins Fratercula arctica) and Laridae (Great Black-backed Gulls Larus marinus, American Herring Gulls L. argentatus smithsonianus) and Northern Gannets Morus bassanus, along with non-breeding, moulting members of the Family Procellariidae (Sooty Shearwaters Ardenna griseus, Great Shearwaters A. gravis). The inshore migration of spawning capelin resulted in 5-619 times (mean ± SE, 146 ± 59 times) increase in coastal fish biomass along with a shift towards more, larger and denser fish shoals. Within years, seabird abundance did not increase with inshore fish biomass but rather peaked near the first day of spawning, suggesting that seabirds primarily respond to the seasonal resource influx rather than short-term variation in fish biomass. Across years, the magnitude of the seabird aggregative response was lower during low-magnitude resource pulse years, suggesting that predators are unable to perceive low-magnitude pulses, avoid foraging under high competitor densities, and/or shift dietary reliance away from capelin under these conditions. The seabird response magnitude, however, was higher when the resource pulse was delayed relative to the long-term average, suggesting that predators increase exploitation during years of minimal overlap between the resource pulse and energetically demanding periods (e.g. breeding, moulting). This long-term study quantifying responses of multiple predators to a pulsed resource illustrates the ability of natural systems to tolerate natural and human-induced disturbance events.

Dynamic Integrated Scheduling of Production Equipment and Automated Guided Vehicles in a Flexible Job Shop Based on Deep Reinforcement Learning

The high-quality development of the manufacturing industry necessitates accelerating its transformation towards high-end, intelligent, and green development. Considering logistics resource constraints, the impact of dynamic disturbance events on production, and the need for energy-efficient production, the integrated scheduling of production equipment and automated guided vehicles (AGVs) in a flexible job shop environment is investigated in this study. Firstly, a static model for the integrated scheduling of production equipment and AGVs (ISPEA) is developed based on mixed-integer programming, which aims to optimize the maximum completion time and total production energy consumption (EC). In recent years, reinforcement learning, including deep reinforcement learning (DRL), has demonstrated significant advantages in handling workshop scheduling issues with sequential decision-making characteristics, which can fully utilize the vast quantity of historical data accumulated in the workshop and adjust production plans in a timely manner based on changes in production conditions and demand. Accordingly, a DRL-based approach is introduced to address the common production disturbances in emergency order insertions. Combined with the characteristics of the ISPEA problem and an event-driven strategy for handling dynamic events, four types of agents, namely workpiece selection, machine selection, AGV selection, and target selection agents, are set up, which refine workshop production status characteristics as observation inputs and generate rules for selecting workpieces, machines, AGVs, and targets. These agents are trained offline using the QMIX multi-agent reinforcement learning framework, and the trained agents are utilized to solve the dynamic ISPEA problem. Finally, the effectiveness of the proposed model and method is validated through a comparison of the solution performance with other typical optimization algorithms for various cases.

Benthic response to event deposition and environmental disturbance in a shoreface to subaqueous delta system: Ichnology of the Silurian-Devonian Furada Formation of Asturias, Spain

The Furada Formation of Asturias, Spain, represents a clastic shallow-marine unit deposited during the middle Silurian to the Early Devonian. This formation contains abundant evidence of event deposition and non-uniform distribution of bioturbation structures representing a benthic response to multiple stressors. The 170-m-thick succession was measured and described, and the ichnotaxa were recorded and associated with five sedimentary facies. Most shallow-marine environments are characterized by periodic events of environmental disturbance, mainly by episodic deposition, which may be recorded by a change in both the degree of bioturbation and ichnodiversity. The general depositional setting for this formation has been previously interpreted as a wave-dominated and storm-influenced shallow-marine environment. However, sedimentologic features described in this study, such as anomalous heterolithic and mudstone units, representing fluid mud layers, hyperpycnal flow deposits and plume collapse accumulations, suggest the influence of fluvial discharge, making it a more complex depositional setting. The proposed model comprises an inner sandy shoreface belt flanked seawards by a muddy subaqueous delta platform. The trace-fossil assemblages of this formation reflect environmental stress factors introduced by the interplay of storms and fluvial input (e.g., high sedimentation rate, fluctuating hydrodynamic energy, decreased substrate consolidation), resulting in reduced ichnodiversity and low abundance. From an ichnofacies perspective, the shoreface complex is characterized by the Cruziana Ichnofacies, whereas the subaqueous delta platform is represented by the Phycosiphon Ichnofacies. Integration of sedimentologic and ichnologic datasets allows for a refined depositional interpretation of the formation and greater understanding of the environmental diversity of wave-and river-influenced shallow-marine clastic systems, including the responses of the middle Paleozoic shallow-marine benthos to event sedimentation and environmental disturbance. This study is one of the first detailed documentations of the ichnology of subaqueous deltas.