Dispersive Model Research Articles

Assessing the suitability of pollen dispersal and deposition model: A model-empirical data comparison study in the spruce (Picea schrenkiana) forest edge of Tian Shan Mountains, northwestern China

Assessing the suitability of pollen dispersal and deposition model: A model-empirical data comparison study in the spruce (Picea schrenkiana) forest edge of Tian Shan Mountains, northwestern China

Tephra fallout and dispersal modeling of phreatic eruptions: implications for volcanic hazard assessment in Martinique and Guadeloupe (Lesser Antilles)

Tephra fallout and dispersal modeling of phreatic eruptions: implications for volcanic hazard assessment in Martinique and Guadeloupe (Lesser Antilles)

Probabilistic tephra fallout hazard maps for Sangay volcano, Ecuador

Sangay volcano (Ecuador) shows a quasi-continuous activity at least since the seventeenth century and has produced several eruptions which affected towns and cities at considerable distance (up to > 170 km). For this reason, despite its remote location, recent efforts were aimed at reviewing its volcanic history, quantifying the occurrence probability of four eruptive scenarios of different magnitude (Strong Ash Venting, Violent Strombolian, sub-Plinian, and Plinian) and the associated uncertainty, and, for each eruptive scenario, estimating the probability distribution of key eruptive source parameters (fallout volume, average plume height, and eruption duration). In this study, we utilize such information to produce probabilistic hazard maps and curves. To this aim, we use coupled plume and dispersal models (PLUME-MOM-TSM and HYSPLIT, respectively) with the application of a novel workflow for running an ensemble of thousands of simulations following a stochastic sampling of input parameters. We produced probabilistic hazard maps for each scenario by considering four ground load thresholds (i.e., 0.1, 1, 10, and 100 kg/m2) and two types of model initialization strategies, based on the elicited total deposit volume and on the elicited plume height, respectively, which produced non-negligible differences. In addition, we produced hazard curves for nine sites of interest from a risk perspective, corresponding to towns/cities potentially affected by tephra accumulation. Finally, we also derived combined maps by merging maps of single scenarios with their probability of occurrence as obtained from expert elicitation. Results indicate that in case of a future eruption, even for a moderate-scale one (Violent Strombolian), probability of tephra accumulation larger than 1 kg/m2 is relatively high (from 21 to 24% considering different model initializations) in the town of Guamote, i.e., the most severely affected site among those tested (43 km W of Sangay). For larger-scale events (i.e., sub-Plinian), the impact of tephra accumulation results to be significant even for the city of Guayaquil (176 km W of Sangay), with probability of tephra accumulation larger than 1 kg/m2 from 3 to 22% considering different model initializations. For maps combining single maps of historically observed scenarios, the probability (% - [5th-Mean-95th]) of having ≥ 10 kg/m2 for Guamote is [4-13-25] as maximum values.

P-1307. AI-Optimized Assessment of Vaccination Strategies in Smallpox Reemergence: an LA Case Study

Abstract Background The resilience of Los Angeles (LA) to smallpox was evaluated using a modified Susceptible, Exposed, Infectious, Recovered, Hospitalized, Deceased (SEIRHD) model, which simulated its spread via an artificial intelligence (AI) mobility matrix and assessed different vaccination regimens (one dose primary series vs a two dose primary series) for outbreak control. Methods The matrix combined data from travel surveys, transportation authorities, GPS caches, and population density estimates from LA County. Fifteen LA government districts plus a 30-mile radius city limit were considered for differential force of infection and mobility matrix variables. Transmission parameters, derived from a review of 20th-century epidemics, assigned 90% transmission to households and 80% to workplaces. Residual immunity against smallpox was set at 8.8%. Intensive care unit (ICU) capacity within 30 miles of LA city limits was set as 2,500 beds per the California Health and Human Services Open Data Portal. One and two dose ring vaccine regimens initiated at day 7 were assessed in 16 districts and as a dispersed city model to understand zonal resilience in eradication and if contagion exceeded ICU capacity limits via an R-programed scenario. Results The naïve general scenario had an infection peak at day 73, with a hospitalization peak of 5,600,227 (day 80) of a susceptible population of 18,833,640. With a 50% effective one dose vaccine, contagion remained below the ICU threshold in the basic 30-mile radius model. However, in specific districts (1, 6-9, and 13-15), even a 95% effective one dose vaccine couldn’t maintain contagion below the ICU threshold according to the AI-assisted zonal model. Hypothetical one dose primary series vaccination regimens outperformed two dose regimens in both city-wide and zonal scenarios (P< 0.05). Zonal analysis based on housing conditions and mobility revealed that even with the most effective hypothetical one dose vaccine (95% efficacy after 7 days), 7 out of 15 LA district ICU thresholds were exceeded, indicating the importance of geospatial modelling. Conclusion The model highlights the importance of zone-based evaluations in preparedness and the need for high-efficacy single-dose vaccinations in ring vaccination. Disclosures Tristan Learoyd, MPharm MA MSc MBA PhD MRPharmS, Emergent: Employee John E. Pittman, PharmD, Emergent: Employee

Motility genes are associated with the occurrence of Drosophila melanogaster-associated gut microbes

Abstract Recent work highlighted the role of motility genes in dispersing fly-associated microbes and their spread between hosts. We investigated whether bacterial genes encoding motility are associated with the occurrence of bacteria above passive dispersal levels in the gut of wild Drosophila melanogaster. We revisited 16S amplicon and shotgun metagenome data of wild flies and correlated four genera of bacteria (Commensalibacter, Gluconobacter, Lactobacillus, and Tatumella) with motility genes. We plotted the microbes against neutral models of ecological drift and passive dispersal. Microbes with positive correlations to motility were exclusively found at or above neutral model predictions, suggesting motility genes are crucial for fly microbiota spread and colonization. This information is crucial for understanding how specific gene functions contribute to microbial community dispersal and colonization within the fly host. Moreover, this study’s findings serve as a proof of concept for using the neutral model to predict microbial functions essential for survival and dissemination in diverse hosts.

A female sterilization method for use in field-based behavioral studies of the invasive Asian longhorned beetle (Anoplophora glabripennis).

Asian longhorned beetle (Anoplophora glabripennis Motschulsky), a wood borer (Coleoptera: Cerambycidae) native to China, has been unintentionally and repeatedly introduced to North American and European landscapes as a stow-away in the wood packing material commonly used in international trade. Asian longhorned beetle causes extensive damage and mortality in multiple deciduous tree species and in response, countries in both North America and Europe have adopted policies of eradication. Models that integrate patterns of Asian longhorned beetle dispersal with records of infested trees are critical in optimizing survey and eradication efforts and tracking eradication progress. While these tools continue to be developed, they have been limited by the availability of experimental dispersal data. Existing data is restricted to observations made in the beetle's native range in China or based on inference of dispersal in invaded landscapes. Direct observation of beetle dispersal behavior in invaded landscapes could provide critical behavioral information, but the experimental release of gravid females has been incompatible with eradication program efforts. To fill this knowledge gap, there is a need to identify field-portable methods of effectively sterilizing mated females that do not alter ovipositional behavior. Here, we present a protocol for cauterizing a beetle's ovipositor to prevent successful oviposition. Results of lab trials demonstrate the efficacy of ovipositor cauterization in inhibiting successful oviposition without altering the egg-laying behavior of gravid Asian longhorned beetle females. This method enables research to inform models of beetle dispersal and infestation risk without adding to actual or perceived risk of exacerbating infestations in an eradication program.

Meta-Analysis of Larval Bivalve Growth in Response to Ocean Acidification and its Application to Sea Scallop Larval Dispersal in the Mid-Atlantic Bight

Ocean acidification, caused by increasing atmospheric carbon dioxide and coastal physical, biological, and chemical processes, is an ongoing threat to carbonate-utilizing organisms living in productive coastal shelves. Bivalves exposed to acidification have shown reduced growth, reproduction, and metabolic processes, with larval stages exhibiting the greatest susceptibility. Here, we compile results from published studies on larval bivalve growth responses to acidification to estimate a relationship between larval growth and seawater aragonite saturation state. We then apply this relationship to a larval dispersal individual-based model for Atlantic sea scallops (Placopecten magellanicus), an economically vital species in the Mid-Atlantic Bight that is historically under-studied in acidification research. To date, there have been no published studies on sea scallop larval response to ocean acidification. Model simulations allowed the identification of potential impacts of acidification on scallop success in the region. Results show that larval sea scallops that are sensitive to ocean acidification had a 17% lower settlement success rate and over 50% reduction in larval passage between major Mid Atlantic Bight fisheries habitats than those that are not sensitive to acidification. Additionally, temperature and ocean acidification interact as drivers of larval success, with aragonite saturation states > 3.0 compensating for temperature-induced mortality (> 19 ˚C) in some cases. This balance between drivers influences larval settlement success across spatial and interannual scales in the Mid Atlantic Bight.

Sectoral inflation under fragmentation of information

Abstract We examine the role of fragmentation of information in explaining the dynamics of sectoral inflation. Using the quarterly survey of firms’ prices and costs in Japan, we first document two empirical facts: the sensitivity of sectoral inflation to changes in sectoral costs monotonically decreases with the dispersion of changes in (i) current costs and (ii) those in the past. A direct application of the dispersed information model can reconcile the fact (i) but fails to reconcile the fact (ii). We then extend the standard imperfect information model to construct a dynamic general equilibrium model that features fragmentation of information, wherein a finite number of groups of firms exist and firms in the same group share common idiosyncratic noises in their signals. Using this model, we find that the degree of fragmentation of information plays a crucial role in explaining these empirical facts.

Investigation of Lane-consistent dispersive optical-model potential for <sup>208</sup>Pb

Lead is an important alloy material nuclide. And lead eutectic is also an important coolant, which is applied in the construction of Lead-cooled Fast Reactor such as The European Lead-cooled System (ELSY) and the China Lead-based Research reactor (CLEAR-I), as well as in research related to Generation-IV reactor. The study and calculation of lead nuclear data have important theoretical value and application prospects. <sup>208</sup>Pb is the most stable and abundant isotope in lead nuclei, and high quality description of <sup>208</sup>Pb nuclear scattering data is the key to achieving theoretical calculations of nuclear reaction data for lead nuclei. Based on the dispersive optical model, this work describes nucleon scattering on <sup>208</sup>Pb by using the dispersive optical potential. The dispersive optical model potential is defined by energy-dependent real potentials, imaginary potentials, the corresponding dispersive contributions to the real potential which are calculated analytically from the corresponding imaginary potentials by using a dispersion relation, and isospin dependence is reasonably considered by introducing isovector component (i.e. Lane term) in the potential depth constants of the real Hartree-Fock potential <i>V</i><sub>HF</sub> and the surface imaginary potential <i>W</i><sub>s</sub>. Unlike K-D potential, which requires two different sets of parameters to describe neutron and proton induced scattering data, this optical potential uses the same set of parameters to simultaneously describe nucleon-nucleus scattering data. The derived potential in this work shows a very good description of nucleon-nucleus scattering data on <sup>208</sup>Pb up to 200 MeV. Calculated neutron total cross sections, neutron and proton elastic scattering angular distributions, as well as neutron and proton elastic analyzing powers are shown to be in good agreement with experimental data. Additionally, the difference in potential between the neutron and protons induced is described by the isovector term, a reasonable good prediction of quasielastic (p, n) scattering data is achieved.

Post-Glacial Vegetation Trajectories on the Eastern Tibetan Plateau Reflect Millennial-Scale Migration Lags in Complex Mountain Terrain Based on Sedimentary Ancient DNA and Dynamic Dispersal Modeling.

Mountains with complex terrain and steep environmental gradients are biodiversity hotspots such as the eastern Tibetan Plateau (TP). However, it is generally assumed that mountain terrain plays a secondary role in plant species assembly on a millennial time-scale compared to climate change. Here, we investigate plant richness and community changes during the last 18,000 years at two sites: Lake Naleng and Lake Ximen on the eastern TP with similar elevation and climatic conditions but contrasting terrain. We applied plant DNA metabarcoding to lake sediments leveraging a new regional reference database for taxa identification. Furthermore, we developed a simplified species dispersal model named SMARC. This was used to simulate species migration along river valleys in response to past climate change at the taxonomic resolution of the sedimentary ancient DNA (sedaDNA) approach. Statistical analyses, including ordination-based ecological trajectory analysis, yielded a significant match between sedaDNA and simulated results at single taxon and community levels including certain site-specific differences. Steep terrain downstream of Lake Naleng enhances connectivity to glacial lowland refugia during postglacial warming. In contrast, gentle terrain over long distances implies weak connectivity to the lowland and thus resulted in a strong migration lag at Lake Ximen. Likewise, terrain differences among our sites defined the different connectivity to alpine refugia during late-Holocene cooling. Our consistent proxy- and model-based results, for the first time, indicate that dispersal related migration lags in complex mountain terrain lead to uneven vegetation trajectories at sites with similar climatic conditions mainly because of differences in connectivity to refugia. Ultimately our results indicate that connectivity to refugia is a first-order factor for species migration in addition to elevation-related climatic conditions shaping the postglacial vegetation trajectory in mountainous terrain. This has hitherto largely been ignored when forecasting mountain vegetation responses to climate change and related risk assessment.

Propagation direction of traveling waves for a class of nonlocal dispersal bistable epidemic models

Propagation direction of traveling waves for a class of nonlocal dispersal bistable epidemic models

Impinging jet ventilation: Mitigating influenza transmission through partition and exhaust layout optimization

This paper investigates the transmission characteristics of cough droplets from infected individuals in office environments under the influence of an impinging jet ventilation (IJV) system based on the Eulerian–Lagrangian model. The accuracy of the dispersed phase model and the IJV system simulation was validated by analyzing a single droplet evaporation model, publicly available jet experimental results, and previously simulated results. The effects of different exhaust locations, the relative positioning of the IJV system to the infected individual, and the application of partitions on the spatial propagation characteristics of droplets are explored. The results indicate that partitions exhibit a significant ability to obstruct and capture droplets. Under static conditions, they are capable of capturing over 36% of droplets generated by coughing, although this efficiency may be slightly influenced by the ventilation system. The IJV system notably affects droplet movement, with droplets progressively converging toward the upper-left corner of the room as the airflow develops. The positioning of the exhausts, in combination with the IJV system, is crucial in impeding and removing droplets. Taking into account variations in the infected individual's position, a centrally located exhaust arrangement might provide the more effective inhibition of virus droplet dispersion.

Prospects for an Evangelical Rule of Life: A Case-Study in Living as a Dispersed Community of Missional Discipleship

From 2020 to 2023, I spent 3 years as the Prior of the Community of St Cuthbert based at St Nics Church in central Durham. St Nics is a classic UK evangelical city-centre church with a beloved history of Bible teaching, market-square engagement, and mission. In 2019 the church leadership discerned an opportunity to refresh the church’s (and wider) practice of discipleship by launching the Community of St Cuthbert, and I was recruited as its Prior. This article gives an account of some of the strengths and weaknesses of this endeavour, focused particularly on four issues: the importance of a clear, positive and upbuilding ‘rule of life’ statement; the core issue of how a Rule of Life can facilitate widespread missional discipleship in a dispersed community model; the importance of a clear marker of membership in the Community (and the difficulties around developing one); and the potential (albeit largely unrealised) to use the Community of St Cuthbert model as a way of establishing new worshipping communities. My own retrospective reflection as Prior concludes with two convictions that may be of relevance to those considering such a ‘Community’: the nature and challenge of keeping the focus on God rather than on policing practices; and the ways in which such a re-energising of discipleship can offer an evangelical contribution to the life of the whole church, rather than being limited to self-described evangelical churches.

Macro‐evolutionary dynamics dominated by dispersal promote the formation of regional biodiversity hotspot‐insights from hawkmoths (Lepidoptera: Sphingidae) in South China

AbstractAimRapid loss in global insect diversity has generated substantial public worry due to their critical ecological roles. However, there is controversy about the effectiveness of the global‐scale hotspots in guiding the conservation of diversity at the regional scale. Even worse, little is known about the knowledge of insect distributional dynamics in many understudied regions, such as East and Southeast Asia. Here, to guide for setting regional‐scale conservation priorities for insect diversity, we explore hawkmoths (Lepidoptera: Sphingidae) for their distributional dynamics and identify regional hotspots requiring protection.LocationSouth China (including Guangdong, Guangxi, Hainan, Hong Kong and Macau) and northern Vietnam (17°~26.5° N, 102°~117.5° E).MethodsSpecies distribution models were generated for 194 hawkmoth species based on 3597 occurrence records to predict their distributions. We calculated the spatial patterns of taxonomic and phylogenetic diversity and identified regional hotspots. Furthermore, the potential assembly mechanisms underlying insect diversity were explored by analysing the rates of speciation, extinction and dispersal between phyloregions.Results(a) The coastal regions of South China and northern Vietnam represent a regional hotspot of hawkmoths in East and Southeast Asia, with significantly higher α‐diversity than that in inland regions. (b) Dispersal played a more important role than local speciation and extinction in the formation of regional hawkmoth hotspots.Main ConclusionsIn this study, the ‘Out‐of‐the‐tropics model’ can explain the formation of the hawkmoth regional hotspots and the enhanced version of the ‘Pure dispersal model’ can explain the formation of the hotspots in Hainan Island. Compared with the local speciation and extinction, dispersal is the main driving factor that promoted the formation of the regional biodiversity hotspot of hawkmoths in South China. The case of Hainan Island suggests that protection within hotspots needs to account for specific regional macro‐evolutionary dynamics rather than indiscriminate coverage of identified hotspots.

Larval dispersal predictions are highly sensitive to hydrodynamic modelling choices

AbstractLarval dispersal is a critical ecological process in marine ecosystems, responsible for connecting and replenishing populations in patchy habitat. Because empirical measurements of larval dispersal are very challenging, coupled biological and oceanographic simulations (“biophysical models”) of larval dispersal are commonly used to answer ecological questions and support conservation management decisions. In the process of creating biophysical models, a series of choices must be made that do not have a single correct answer—sometimes because the oceanographic or ecological processes are uncertain; sometimes because trade-offs are required between different goals (e.g. computational time versus spatial resolution). In this paper, we demonstrate that larval dispersal estimates at management scales are strongly affected by these choices. Using three different hydrodynamic models of the Great Barrier Reef, we estimated the dispersal of crown-of-thorns starfish larvae in the spawning seasons between 2018 and 2021. Despite sharing similar physical forcings and using similar models of larval behaviour, we find that the different hydrodynamic models produce divergent predictions of larval dispersal between the reefs. If used to support crown-of-thorns starfish control decisions, these different predictions would recommend different priority reefs. Our results caution against the use of single models of larval dispersal, and suggest that multi-model ensembles may offer a valuable new perspective on dispersal patterns in marine environments.

Study design and the sampling of deleterious rare variants in biobank-scale datasets.

One key component of study design in population genetics is the "geographic breadth" of a sample (i.e., how broad a region across which individuals are sampled). How the geographic breadth of a sample impacts observations of rare, deleterious variants is unclear, even though such variants are of particular interest for biomedical and evolutionary applications. Here, in order to gain insight into the effects of sample design on ascertained genetic variants, we formulate a stochastic model of dispersal, genetic drift, selection, mutation, and geographically concentrated sampling. We use this model to understand the effects of the geographic breadth of sampling effort on the discovery of negatively selected variants. We find that samples which are more geographically broad will discover a greater number variants as compared geographically narrow samples (an effect we label "discovery"); though the variants will be detected at lower average frequency than in narrow samples (e.g. as singletons, an effect we label "dilution"). Importantly, these effects are amplified for larger sample sizes and moderated by the magnitude of fitness effects. We validate these results using both population genetic simulations and empirical analyses in the UK Biobank. Our results are particularly important in two contexts: the association of large-effect rare variants with particular phenotypes and the inference of negative selection from allele frequency data. Overall, our findings emphasize the importance of considering geographic breadth when designing and carrying out genetic studies, especially at biobank scale.

FedSR: Federated Learning for Image Super-Resolution via detail-assisted contrastive learning

Federated learning (FL) is a distributed learning paradigm that collaboratively learns a global model from multiple decentralized clients without sharing raw data, providing an effective solution for privacy preservation. However, current FL works primarily focus on high-level visual tasks (e.g., classification), the exploration for image super-resolution (SR), a fundamental low-level visual task, is rarely addressed. In this study, we propose Federated Image Super-Resolution (FedSR), a novel FL approach for image SR task, aiming to generate high-quality images while preserving data privacy. Specifically, we introduce a detail-assisted contrastive loss at the decentralized client, aligning the shallow representations by rectifying the relationship of low-level features between local clients and global server. In addition, we develop a hierarchical aggregation policy at the central server to better integrate dispersed client models into the global model, with the aggregation weight determined based on the layer-wise similarity between the updated local models and the historical global model. Extensive experiments conducted on general SR benchmarks and facial image datasets demonstrate the superiority of our FedSR in terms of image quality and model performance. Notably, FedSR can be seamlessly integrated with various prevalent image SR methods, including CNN-based and Transformer-based architectures.

Quantification of volcanic degassing and analysis of uncertainties using numerical modeling: the case of Stephanos crater (Nisyros Island, Greece)

Nisyros Island (Greece) is affected by widespread gas emissions from fumarolic fields located at the bottom of hydrothermal craters in the southern part of its caldera. This morphology and the current low gas fluxes make Nisyros an ideal site for testing the limits of physics-based gas dispersal models in confined and low-emission conditions. Here, we focused our attention on the local scale volcanic gas dispersion from the Stephanos hydrothermal crater. In April 2023, a 1-week survey was carried out to measure weather data, CO2 and H2S gas fluxes, air concentrations from portable gas stations, and chemical composition of fumarolic gases and to acquire thermal images of the crater floor. These data were used as inputs and boundary conditions for numerical simulations using a DISGAS-2.6.0 model in order to quantify the present-day volcanic degassing and its associated uncertainties, accounting for the meteorological variability. Model results are provided in terms of H2S probabilistic exceedance and persistence maps, showing gas concentrations within the crater that fall below the thresholds indicated for the occurrence of serious respiratory problems. Since DISGAS-2.6.0 does not account for chemical reactions, this study represents a good opportunity to discuss the methodological limits of simulating the dispersion of H2S which is challenging due to its rapid degradation and dilution in the atmosphere. In this regard, we also provided an empirical law of the H2S depletion in low-emission conditions that takes into account the uncertainties related to the field measurements.

Structural model of bifraction ceramic dispersions

Structural model of bifraction ceramic dispersions

Deep learning insights into distinct patterns of polygenic adaptation across human populations.

Response to spatiotemporal variation in selection gradients resulted in signatures of polygenic adaptation in human genomes. We introduce RAISING, a two-stage deep learning framework that optimizes neural network architecture through hyperparameter tuning before performing feature selection and prediction tasks. We tested RAISING on published and newly designed simulations that incorporate the complex interplay between demographic history and selection gradients. RAISING outperformed Phylogenetic Generalized Least Squares (PGLS), ridge regression and DeepGenomeScan, with significantly higher true positive rates (TPR) in detecting genetic adaptation. It reduced computational time by 60-fold and increased TPR by up to 28% compared to DeepGenomeScan on published data. In more complex demographic simulations, RAISING showed lower false discoveries and significantly higher TPR, up to 17-fold, compared to other methods. RAISING demonstrated robustness with least sensitivity to demographic history, selection gradient and their interactions. We developed a sliding window method for genome-wide implementation of RAISING to overcome the computational challenges of high-dimensional genomic data. Applied to African, European, South Asian and East Asian populations, we identified multiple genomic regions undergoing polygenic selection. Notably, ∼70% of the regions identified in Africans are unique, with broad patterns distinguishing them from non-Africans, corroborating the Out of Africa dispersal model.