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20 results for “Migration Flows”
MCMC simulations from the posterior distributions of European migration flows
<p>This folder contains three RData files each containing MCMC simulations from the posterior distributions of a Bayesian hierarchal model used to estimate European migration flows, developed as part of the project Quantifying Migration Scenarios for Better Policy (QuantMig, <a href="https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.quantmig.eu%2F&data=05%7C01%7CP.W.Smith%40soton.ac.uk%7Cc166e7bff7f840a7983b08db94af1244%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C638267252014422806%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=yMDYBngYz%2BnzvXmNj6MqseYwso0ICNbREE8TmqQ%2BRJ0%3D&reserved=0">www.quantmig.eu</a>); see Aristotelous, Smith and Bijak (2022) for details. The first set of estimates are disaggregated by origin, destination and time, a breakdown which we denote as ODT. The second and third sets of estimates are again disaggregated by origin, destination and time, but they are additionally disaggregated by other factors. The second set is further disaggregated by age and sex and the third by just birth region. We respectively denote these breakdowns as ODAST and ODBT. Also, included in this folder is an R script to calculate summaries of these posterior distributions (means, and lower and upper quartiles) and output them to csv files, which are also in the folder. For further details, see deliverable_6_4_v1_2.pdf also in the folder.</p>
Replication data for: Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020
<h3>Data and code for performing analyses and plotting figures for "Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020"</h3> <p>The code and data can also be found at https://github.com/MPIDR/Global-flows-and-rates-of-international-migration-of-scholars/</p> <p><strong>Abstract</strong>: A lack of comprehensive migration data is a major barrier for understanding the causes and consequences of migration processes, including for specific groups like high-skilled migrants. We leverage large-scale bibliometric data from Scopus and OpenAlex to trace the global movements of scholars. Based on our empirical validations, we develop pre-processing steps and offer best practices for the measurement and identification of migration events. We have prepared a publicly accessible dataset that shows a high level of correlation between the counts of scholars in Scopus and OpenAlex for most countries. Although OpenAlex has more extensive coverage of non-Western countries, the highest correlations with Scopus are observed in Western countries. We share aggregated yearly estimates of international migration rates and of bilateral flows for 210 countries and areas worldwide for the period 1998-2020 and describe the data structure and usage notes. We expect that the publicly shared dataset will enable researchers to further study the causes and the consequences of migration of scholars to forecast the future mobility of global academic talent.</p>
MIrreM Public Database on Irregular Migration Flow Estimates and Indicators
<p><span>This <em>Public Database on Irregular Migration Flow Estimates and Indicators</em>, in short MIrreM D5.2, is a MIrreM project deliverable under work package 5.</span><strong><span> </span></strong><span>This database provides an </span><span>inventory and critical appraisal of available estimates and indicators related to irregular migration flows. More specifically, <span>the database contains the country-level data collected by MIrreM’s national rapporteurs, as well as EU-level data from sources other than Eurostat. The datasets include </span>meta-level information on sources and methodology and a quality assessment based on MIrreM’s criteria. </span></p> <p><span>Users of this database are advised to consult the following <strong>companion document</strong> (henceforth, MIrreM Working Paper No. 9/2024) for a full discussion of the context, the underlying concepts, and the methodology used: </span></p> <p><span>Siruno, L., Leerkes, A., Hendow, M. & Brunovská, E. 2024. Working Paper on Irregular Migration Flows. MIrreM Working Paper No. 9. Krems: University for Continuing Education Krems (Danube University Krems). <a href="https://doi.org/10.5281/zenodo.%2010702228"><span>https://doi.org/10.5281/zenodo.</span> 10702228</a>.</span></p> <p><span>The MIrreM project is a follow-up to CLANDESTINO, which covered the period 2000-2007. MIrreM extends this to the subsequent period 2008-2023. The data covered in this database reflect what is available within this period. Most of the data was collected between June and October 2023, and thus in some cases, the data are only until 2022 pending complete reports for 2023. </span></p>
Flow velocity measurements over a migrating train of dunes in a flume in the laboratory
<p>Acoustic Doppler Velocimeter (ADV) measurements conducted over a migrating train of dunes in a flume in the laboratory. The files with an .ntk extension are the raw data as measured and recorded by the instrument (Nortek Vectrino Profiler) and those with an extension .mat are the raw data as exported from the original software into a MatLab readable file format. <br> The data was used to create a streamwise flow velocity profile in the publication associated with this dataset. <br> File names have a nominal distance to the bed in mm expressed by the numbers at the end of the name. For example, 00_10 indicates measurements from 0 to 10 mm. However, as the measurements were conducted over a migrating train of dunes, those numbers are not as precise. However, the instrument records the distance to the bed and it is available inside the files. The distance inside the files is the one used to create the figure for the publication. <br> <br> In the upcoming publication the data was used to plot figure 4(d)<br> <br> The figure is available as 4D in the preprint found in this link: https://www.researchsquare.com/article/rs-1370465/v1</p> <p> </p>
Data from: Neuronal migration depends on blood flow in the adult mammalian brain
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Data from: Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish
As anthropogenic impacts accelerate changes to landscapes across the globe, understanding how genetic population structure is influenced by habitat features and dispersal is key to preserving evolutionary potential at the species level. Furthermore, knowledge of these interactions is essential to identifying potential constraints on local adaptation and for the development of effective management strategies. We examined these issues in Brook Trout (Salvelinus fontinalis) populations residing in the Upper Hudson River watershed of New York State by investigating the spatial genetic structure of over 350 fish collected from 14 different sampling locations encompassing three river systems. Population genetic analyses of microsatellite data suggest that fish in the area exhibit varying degrees of introgression from nearby State-directed supplementation activities. Levels of introgression in these populations correlate with water-way distance to stocking sites, although genetic population structure at the level of individual tributaries as well as their larger, parent river systems is also detectable and is dictated by migration and influenced by habitat connectivity. These findings represent a significant contribution to the current literature surrounding Brook Trout migration and dispersal, especially as it relates to larger interconnected systems. This work also suggests that stocking activities may have far-reaching consequences that are not directly limited to the immediate area where stocking occurs. The framework and data presented here may aid in the development of other local aquatic species-focused conservation plans that incorporate molecular tools to answer complex questions regarding diversity mapping, and genetically important conservation units.
Data from: Identifying loci under selection against gene flow in isolation with migration models
When divergence occurs in the presence of gene flow, there can arise an interesting dynamic in which selection against gene flow, at sites associated with population-specific adaptations or genetic incompatibilities, can cause net gene flow to vary across the genome. Loci linked to sites under selection may experience reduced gene flow and may experience genetic bottlenecks by the action of nearby selective sweeps. Data from histories such as these may be poorly fitted by conventional neutral model approaches to demographic inference, which treat all loci as equally subject to forces of genetic drift and gene flow. To allow for demographic inference in the face of such histories, as well as the identification of loci affected by selection, we developed an isolation-with-migration model that explicitly provides for variation among genomic regions in migration rates and/or rates of genetic drift. The method allows for loci to fall into any of multiple groups, each characterized by a different set of parameters, thus relaxing the assumption that all loci share the same demography. By grouping loci, the method can be applied to data with multiple loci and still have tractable dimensionality and statistical power. We studied the performance of the method using simulated data, and we applied the method to study the divergence of two subspecies of European rabbits (Oryctolagus cuniculus).
Data from: Combined genetic and telemetry data reveal high rates of gene flow, migration, and long-distance dispersal potential in Arctic ringed seals (Pusa hispida)
Ringed seals (Pusa hispida) are broadly distributed in seasonally ice covered seas, and their survival and reproductive success is intricately linked to sea ice and snow. Climatic warming is diminishing Arctic snow and sea ice and threatens to endanger ringed seals in the foreseeable future. We investigated the population structure and connectedness within and among three subspecies: Arctic (P. hispida hispida), Baltic (P. hispida botnica), and Lake Saimaa (P. hispida saimensis) ringed seals to assess their capacity to respond to rapid environmental changes. We consider (a) the geographical scale of migration, (b) use of sea ice, and (c) the amount of gene flow between subspecies. Seasonal movements and use of sea ice were determined for 27 seals tracked via satellite telemetry. Additionally, population genetic analyses were conducted using 354 seals representative of each subspecies and 11 breeding sites. Genetic analyses included sequences from two mitochondrial regions and genotypes of 9 microsatellite loci. We found that ringed seals disperse on a pan-Arctic scale and both males and females may migrate long distances during the summer months when sea ice extent is minimal. Gene flow among Arctic breeding sites and between the Arctic and the Baltic Sea subspecies was high; these two subspecies are interconnected as are breeding sites within the Arctic subspecies.
Data from: Fine-grained adaptive divergence in an amphibian: genetic basis of phenotypic divergence and the role of non-random gene flow in restricting effective migration among wetlands
Adaptive ecological differentiation among sympatric populations is promoted by environmental heterogeneity, strong local selection and restricted gene flow. High gene flow, on the other hand, is expected to homogenize genetic variation among populations and therefore prevent local adaptation. Understanding how local adaptation can persist at the spatial scale at which gene flow occurs has remained an elusive goal, especially for wild vertebrate populations. Here, we explore the roles of natural selection and nonrandom gene flow (isolation by breeding time and habitat choice) in restricting effective migration among local populations and promoting generalized genetic barriers to neutral gene flow. We examined these processes in a network of 17 breeding ponds of the moor frog Rana arvalis, by combining environmental field data, a common garden experiment and data on variation in neutral microsatellite loci and in a thyroid hormone receptor (TRβ) gene putatively under selection. We illustrate the connection between genotype, phenotype and habitat variation and demonstrate that the strong differences in larval life history traits observed in the common garden experiment can result from adaptation to local pond characteristics. Remarkably, we found that haplotype variation in the TRβ gene contributes to variation in larval development time and growth rate, indicating that polymorphism in the TRβ gene is linked with the phenotypic variation among the environments. Genetic distance in neutral markers was correlated with differences in breeding time and environmental differences among the ponds, but not with geographical distance. These results demonstrate that while our study area did not exceed the scale of gene flow, ecological barriers constrained gene flow among contrasting habitats. Our results highlight the roles of strong selection and nonrandom gene flow created by phenological variation and, possibly, habitat preferences, which together maintain genetic and phenotypic divergence at a fine-grained spatial scale.
Data from: Estimates of gene flow and dispersal in wild riverine Brook Trout (Salvelinus fontinalis) populations reveal ongoing migration and introgression from stocked fish
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Data from: Genomics and telemetry suggest a role for migration harshness in determining overwintering habitat choice, but not gene flow, in anadromous Arctic Char
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Data from: Fine-grained adaptive divergence in an amphibian: genetic basis of phenotypic divergence and the role of non-random gene flow in restricting effective migration among wetlands
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Data from: Combined genetic and telemetry data reveal high rates of gene flow, migration, and long-distance dispersal potential in Arctic ringed seals (Pusa hispida)
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Data from: Identifying loci under selection against gene flow in isolation with migration models
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Data from: Female-biased dispersal and non-random gene flow of MC1R variants do not result in a migration load in barn owls
Non-random gene flow is a widely neglected force in evolution and ecology. This genotype-dependent dispersal is difficult to assess, yet can impact the genetic variation of natural populations and their fitness. In this work, we demonstrate a high immigration rate of barn owls (Tyto alba) inside a Swiss population surveyed during 15 years. Using 10 microsatellite loci as an indirect method to characterize dispersal, two third of the genetic tests failed to detect a female-biased dispersal, and Monte-Carlo simulations confirmed a low statistical power to detect sex-biased dispersal in case of high dispersal rate of both sexes. The capture-recapture data revealed a female-biased dispersal associated with an excess of heterozygote for the melanocortin-1 receptor gene (MC1R), which is responsible for their ventral rufous coloration. Thus, female homozygotes for the MC1R_white allele might be negatively selected during dispersal. Despite the higher immigration of females that are heterozygote at MC1R, non-random gene flow should not lead to a migration load regarding this gene because we did not detect an effect of MC1R on survival and reproductive success in our local population. The present study highlights the usefulness of using multiple methods to correctly decrypt dispersal and gene flow. Moreover, despite theoretical expectations, we show that non-random dispersal of particular genotypes does not necessarily lead to migration load in recipient populations.
Pulses of RhoA Signaling Stimulate Actin Polymerization and Flow in Protrusions to Drive Collective Cell Migration
<p>In animals, cells often move as collectives to shape organs, close wounds, or—in the case of disease—metastasize. To accomplish this, cells need to generate force to propel themselves forward. The motility of singly migrating cells is driven largely by an interplay between Rho GTPase signaling and the actin network. Whether cells migrating as collectives use the same machinery for motility is unclear. Using the zebrafish posterior lateral line primordium as a model for collective cell migration, we find that active RhoA and myosin II cluster on the basal sides of the primordium cells and are required for primordium motility. Positive and negative feedbacks cause RhoA and myosin II activities to pulse. These pulses of RhoA signaling stimulate actin polymerization at the tip of the protrusions and myosin II-dependent actin flow and protrusion retraction at the base of the protrusions, and deform the basement membrane underneath the migrating primordium. This suggests that RhoA-induced actin flow on the basal sides of the cells constitutes the motor that pulls the primordium forward, a scenario that likely underlies collective migration in other—but not all—contexts.</p>
Data from: Female-biased dispersal and non-random gene flow of MC1R variants do not result in a migration load in barn owls
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Data from: Response of seaward migrating European eel (Anguilla anguilla) to manipulated flow fields
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Migration flow and complex network
<p>Data is collected from Baidu Map (http://qianxi.baidu.com/). The migration scale index data, produced by the map service company of Baidu through the GPS location in mobile phone, record the number of migrants between any two cities. It visualises the migration flows in particular time periods. Although, it cannot capture all migrants, it is useful to conduct comparisons among different cities.</p>
RhoA-ROCK competes with YAP to regulate amoeboid breast cancer cell migration in response to lymphatic-like flow
GEO Series GSE191142. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
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