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28 results for “migration rate”
Data for Daudin, Frank & Rapoport « Can internal migration foster the convergence in regional fertility rates? Evidence from 19th century France », Economic Journal (2019), n°620, May, p.1618-1692.
<p>Data for Guillaume Daudin, Raphaël Franck and Hillel Rapoport « Can internal migration foster the convergence in regional fertility rates? Evidence from 19th century France » avec Raphaël Franck et Hillel Rapoport, Economic Journal (2019), n°620, May, p.1618-1692.</p> <p>Downloading the data will provide you with a .zip file.</p> <p>To understand what is going on, please refer to the paper, its git depository and especially this file : https://github.com/gdaudin/migrations/blob/master/R%C3%A9capitulatif%20des%20do%20-%20Migration.pdf</p> <p>All the migration "matrices" are in Stata format (.dta). They are presented as a list of directed pairs of departments (x gender (variable sexe) and x year (variable annee)).</p> <p>"Matrice_complete_1901+1911.dta" are the migration matrices in the source.<br>"Matrices_TRA_Recens.dta" are the main estimated migration matrices.</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>
Divorce rate in birds increases with male promiscuity and migration distance
<p>Socially monogamous birds may break up their partnership by a so-called 'divorce' behaviour. Divorce rate immensely varies across avian taxa that have a predominantly monogamous social mating system. Although a range of factors associated with divorce have been tested, broad-scale drivers of divorce rate remain contentious. Moreover, the impact of sexual roles in divorce still needs further investigation due to the conflicting interest of males and females. Here we applied phylogenetic comparative methods to analyse one of the largest datasets ever compiled that included divorce rates from published studies of 186 avian species from 25 orders and 61 families. We tested correlations between divorce rate and a group of factors: 'promiscuity' of both sexes (propensity of polygamy), migration distance, and adult mortality. Our results showed that only male promiscuity, but not female promiscuity, had a positive relationship with divorce rate. Furthermore, migration distance was positively correlated with divorce rate, while adult mortality rate showed no direct relationship with divorce rate. These findings indicated that divorce might not be a simple adaptive (by sexual selection) or non-adaptive strategy (by accidental loss of a partner), but could be a mixed response to sexual conflict and stress from the ambient environment.</p>
Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest
<p>Migrants from protected areas may buffer the risk of harvest-induced evolutionary changes in exploited populations that face strong selective harvest pressures in both terrestrial and marine ecosystems. Understanding the mechanisms favouring genetic rescue through migration could help ensure sustainable harvest outside protected areas and conserve genetic diversity inside those areas. We developed a stochastic individual-based metapopulation model to evaluate the potential for migration from protected areas to mitigate the evolutionary consequences of selective harvest. We parameterized the model with detailed data from individual monitoring of two populations of bighorn sheep subjected to trophy hunting. We tracked horn length through time in a metapopulation including large protected and trophy-hunted populations connected through male breeding migrations. We quantified and compared declines in horn length and rescue potential under various combinations of migration rate, hunting rate in hunted areas and temporal overlap in timing of harvest and migrations, which affects the migrants' survival and chances to breed within exploited areas. Our simulations suggest that the effects of size-selective harvest on male horn length in hunted populations can be dampened or avoided if harvest pressure is low, migration rate is substantial, and migrants have a low risk of being shot. Intense size-selective harvest impacts the phenotypic and genetic diversity in horn length, and population structure through changes in proportions of large-horned males, sex ratio and age structure. When hunting pressure is high and overlaps with male migrations, effects of selective removal also emerge in the protected population, so that instead of a genetic rescue of hunted populations, our model predicts undesirable effects inside protected areas. Our results stress the importance of a metapopulational approach to management, to promote genetic rescue from protected areas and limit ecological and evolutionary impacts of harvest on both harvested and protected populations.</p>
Divorce rate in birds increases with male promiscuity and migration distance
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Code and initial metapopulation data for model construction and simulation analyses for: Genetic rescue from protected areas is modulated by migration, hunting rate and timing of harvest
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Files for phylogenetics, structure, and migration rate analyses for the bivalve Aequiyoldia eightsii
<p><span><span><span>The Antarctic Circumpolar Current (ACC) dominates the open-ocean circulation of the Southern Ocean, and both isolates and connects the Southern Ocean biodiversity. However, the impact on biological processes of other Southern Ocean currents is less clear. Adjacent to the West Antarctic Peninsula (WAP), the ACC flows offshore in a northeastward direction, whereas the Antarctic Peninsula Coastal Current (APCC) follows a complex circulation pattern along the coast, with topographically-influenced deflections depending on the area. Using genomic data, we estimated genetic structure and migration rates between populations of the benthic bivalve </span><i><span>Aequiyoldia eightsii</span></i><span> from the shallows of southern South America and the WAP to test the role of the ACC and the APCC in its dispersal. We found strong genetic structure across the ACC (between southern South America and Antarctica) and moderate structure between populations of the West Antarctic Peninsula. Migration rates along the WAP were consistent with the APCC being important for species dispersal. Along with supporting current knowledge about ocean circulation models at the WAP, migration from the tip of the Antarctic Peninsula to the Bellingshausen Sea highlights the complexities of Southern Ocean circulation. This study provides novel biological evidence of a role of the APCC as a driver of species dispersal and highlights the power of genomic data for aiding in the understanding of complex oceanographic processes.</span></span></span></p>
Data for Aeolian Ripple Migration and Associated Creep Transport Rates
<p><strong>Overview:</strong></p> <p>The attached spreadsheet, "AeolianRippleMigration_ShermanEtAl2019.csv," summarizes the ripple migration and related data acquired from the wind tunnel and field experiment literature and from the field experiments at Jericoacoara, Ceará, Brazil (2008) and Oceano, California, USA (2015), associated with the article "Aeolian Ripple Migration and Associated Creep Transport Rates" by Douglas J. Sherman, Pei Zhang, Raleigh L. Martin, Jean T. Ellis, Jasper F. Kok, Eugene J. Farrell, and Bailiang Li.</p> <p><strong>Notes for data sources:</strong></p> <p>"a" - indicates that the data from a particular study were included in our final analyses</p> <p>"b" - indicates an estimate of threshold shear velocity (calculated as per Lorenz et al., 2011) with A = 0.1</p> <p>"c" - the value for ripple height in this study is the average of about 200 measurements for ripples in equilibrium or near-equilibrium with the wind field</p> <p>"d" - the data from this study were digitized as depicted in terms of ust/ust_th and u_r/(gd)^0.5 (see "Key to variables" below)</p> <p>"e" - Shear velocity (ust) values are from Martin & Kok, 2017. Median grain diameter (d) and threshold shear velocity (ust_th) values are from Martin & Kok, 2018 (see Table 2: "Date interval")</p> <p><br> <strong>Key to variables [units]:</strong></p> <p>Source - literature origin of previous studies or field location of observations for this study</p> <p>Note - annotation for additional information about study (see above "Notes for data sources")</p> <p>StudyType - classified as "field" or "wind tunnel"</p> <p>Date - date of observation for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>StartTime - start time of observation window (local time) for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>EndTime - end time of observation window (local time) for observations at Jericoacoara and Oceano ( "N/A" for other sites)</p> <p>u_r [mm/s] - calculated ripple migration speed ( "N/A" for Zhu et al, 2011, see "u_r_alt" below)</p> <p>sigma_u_r [mm/s] - uncertainty in ripple migration speed. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p> <p>u_r_alt - dimensionless proxy values for ripple migration speed for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as u_r/(gd)^1/2, where "g" is gravitational acceleration and "d" is median surface grain diameter </p> <p>ust [m/s] - shear velocity ( "N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>d [mm] - median surface grain diameter ("N/A" if not reported for literature studies)</p> <p>ust_th [m/s] - threshold shear velocity ("N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>ust_over_ust_th - dimensionless proxy values for shear velocity for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as ust/ust_th</p> <p>length [m] - ripple wavelength ("N/A" if not reported or measured)</p> <p>height [mm] - ripple amplitude ("N/A" if not reported or measured)</p> <p>sigma_height [mm] - uncertainty in ripple amplitude. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p>
Data for Aeolian Ripple Migration and Associated Creep Transport Rates
<p><strong>Overview:</strong></p> <p>The attached spreadsheet, "AeolianRippleMigration_ShermanEtAl2019.csv," summarizes the ripple migration and related data acquired from the wind tunnel and field experiment literature and from the field experiments at Jericoacoara, Ceará, Brazil (2008) and Oceano, California, USA (2015), associated with the article "Aeolian Ripple Migration and Associated Creep Transport Rates" by Douglas J. Sherman, Pei Zhang, Raleigh L. Martin, Jean T. Ellis, Jasper F. Kok, Eugene J. Farrell, and Bailiang Li.</p> <p><br> <strong>Notes for data sources:</strong></p> <p>"a" - indicates that the data from a particular study were included in our final analyses</p> <p>"b" - indicates an estimate of threshold shear velocity (calculated as per Lorenz et al., 2011) with A = 0.1</p> <p>"c" - the value for ripple height in this study is the average of about 200 measurements for ripples in equilibrium or near-equilibrium with the wind field</p> <p>"d" - the data from this study were digitized as depicted in terms of ust/ust_th and u_r/(gd)^0.5 (see "Key to variables" below)</p> <p>"e" - Shear velocity (ust) values are from Martin & Kok, 2017. Median grain diameter (d) and threshold shear velocity (ust_th) values are from Martin & Kok, 2018 (see Table 2: "Date interval")</p> <p><br> <strong>Key to variables [units]:</strong></p> <p>Source - literature origin of previous studies or field location of observations for this study</p> <p>Note - annotation for additional information about study (see above "Notes for data sources")</p> <p>StudyType - classified as "field" or "wind tunnel"</p> <p>Date - date of observation for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>StartTime - start time of observation window (local time) for observations at Jericoacoara and Oceano ("N/A" for other sites)</p> <p>EndTime - end time of observation window (local time) for observations at Jericoacoara and Oceano ( "N/A" for other sites)</p> <p>u_r [mm/s] - calculated ripple migration speed ( "N/A" for Zhu et al, 2011, see "u_r_alt" below)</p> <p>sigma_u_r [mm/s] - uncertainty in ripple migration speed. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p> <p>u_r_alt - dimensionless proxy values for ripple migration speed for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as u_r/(gd)^1/2, where "g" is gravitational acceleration and "d" is median surface grain diameter </p> <p>ust [m/s] - shear velocity ( "N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>d [mm] - median surface grain diameter ("N/A" if not reported for literature studies)</p> <p>ust_th [m/s] - threshold shear velocity ("N/A" for Zhu et al, 2011, see "ust_over_ust_th" below)</p> <p>ust_over_ust_th - dimensionless proxy values for shear velocity for Zhu et al, 2011 (marked as "N/A" for other sites) calculated as ust/ust_th</p> <p>length [m] - ripple wavelength ("N/A" if not reported or measured)</p> <p>height [mm] - ripple amplitude ("N/A" if not reported or measured)</p> <p>sigma_height [mm] - uncertainty in ripple amplitude. Calculated as fixed percentage for Jericoacoara and as standard error for Oceano. For literare-derived values, "N/A" indicates lack of uncertainty estimates. For Oceano, "N/A" indicates inability to calculate standard error for certain measurement intervals containing only a single observation.</p> <p><br> <strong>References:</strong></p> <p>Andreotti, B.; Claudin, P.; Pouliquen, O. Aeolian Sand Ripples : Experimental Study of Fully Developed States. 2006, 028001, 1-4.</p> <p>Borsy, Z. A homokfodrok. Fldrajzi rtesito 1973, 22, 109-115.</p> <p>Cheng, H.; Liu, C.; Zou, X.; Li, J.; He, J.; Liu, B.; Wu, Y.; Kang, L.; Fang, Y. Aeolian creeping mass of different grain sizes over sand beds of varying length. Journal of Geophysical Research: Earth Surface 2015, 120, 1404-1417.</p> <p>Cornish, V. On the formation of sand-dunes. The Geographical Journal 1897, 9, 278-302.</p> <p>Kindle, E.M. Recent and fossil ripple-mark; Canada Department of Mines, Geological Survey: 1917; pp 9-29.</p> <p>Ling, Y.-q.; Qu, J.-j.; Li, C.-z. Study on sand ripple movement with close shoot method. Journal of Desert Research 2003, 23, 118-120.</p> <p>Lorenz, R.D. Observations of wind ripple migration on an Egyptian seif dune using an inexpensive digital timelapse camera. Aeolian Research 2011, 3, 229-234.</p> <p>Martin, R.L.; Kok, J.F. Aeolian saltation fieldwork 30-minute wind and saltation values (Dataset). Zenodo, https://doi.org/10.5281/zenodo.291798: 2017.</p> <p>Martin, R.L., Kok, J.F. Distinct Thresholds for the Initiation and Cessation of Aeolian Saltation From Field Measurements. Journal of Geophysical Research - Earth Surface 2018, 123, 1546–1565. https://doi.org/10.1029/2017JF004416</p> <p>Seppälä, M.; Lindé, K. Wind tunnel studies of ripple formation. Geografiska Annaler: Series A, Physical Geography 1978, 60, 29-42.</p> <p>Sharp, R.P. Wind ripples. The Journal of Geology 1963, 71, 617-636.</p> <p>Stone, R.O.; Summers, H.J. Study of Subaqueous and Subaerial Sand Ripples; University of Southern California: Los Angeles, 1972.</p> <p>Zhu, W. Investigations on the formation and evolution of aeolian sand ripples. Lanzhou University, 2011.</p>
Output and data used in publication "Glacial isostatic adjustment modulates lateral migration rate and morphology of the Red River (North Dakota, USA, and Manitoba Canada)" in GRL
<p>Here we provide the output sea level used to calculate change in slope along studied rivers as well as locations of meanders and cutoffs. Please see the read.me file and publication for details. </p>
Files for phylogenetics, structure, and migration rate analyses for the bivalve Aequiyoldia eightsii
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Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates
We propose a two-step procedure for estimating multiple migration rates in an approximate Bayesian computation (ABC) framework, accounting for global nuisance parameters. The approach is not limited to migration, but generally of interest for inference problems with multiple parameters and a modular structure (e.g. independent sets of demes or loci). We condition on a known, but complex demographic model of a spatially subdivided population, motivated by the reintroduction of Alpine ibex (Capra ibex) into Switzerland. In the first step, the global parameters ancestral mutation rate and male mating skew have been estimated for the whole population in Aeschbacher et al. (Genetics 2012; 192: 1027). In the second step, we estimate in this study the migration rates independently for clusters of demes putatively connected by migration. For large clusters (many migration rates), ABC faces the problem of too many summary statistics. We therefore assess by simulation if estimation per pair of demes is a valid alternative. We find that the trade-off between reduced dimensionality for the pairwise estimation on the one hand and lower accuracy due to the assumption of pairwise independence on the other depends on the number of migration rates to be inferred: the accuracy of the pairwise approach increases with the number of parameters, relative to the joint estimation approach. To distinguish between low and zero migration, we perform ABC-type model comparison between a model with migration and one without. Applying the approach to microsatellite data from Alpine ibex, we find no evidence for substantial gene flow via migration, except for one pair of demes in one direction.
Data from: Do the high energy lifestyles of shorebirds result in high maximal metabolic rates? - Basal and maximal metabolic rates in least and pectoral sandpipers during migration
Shorebirds have high resting and field metabolic rates relative to many other bird groups, and this is posited to be related to their high-energy lifestyle. Maximum metabolic outputs for cold or exercise are also often high for bird groups with energetically demanding lifestyles. Moreover, shorebirds demonstrate flexible basal and maximal metabolic rates, which vary with changing energy demands throughout the annual cycle. Consequently, shorebirds might be expected to have high maximum metabolic rates, especially during migration periods. We captured least (Calidris minutilla) and pectoral (C. melanotos) sandpipers during spring and fall migration in southeastern South Dakota and measured maximal exercise metabolic rate (MMR; least sandpipers only), summit metabolic rate (Msum, maximal cold-induced metabolic rate) and basal metabolic rate (BMR, minimum maintenance metabolic rate) with open-circuit respirometry. BMR for both least and pectoral sandpipers exceeded allometric predictions by 3-14%, similar to other shorebirds, but Msum and MMR for both species were either similar to or lower than allometric predictions, suggesting that the elevated BMR in shorebirds does not extend to maximal metabolic capacities. Old World shorebirds show the highest BMR during the annual cycle on the Arctic breeding grounds. Similarly, least sandpiper BMR during migration was lower than on the Arctic breeding grounds, but this was not the case for pectoral sandpipers, so our data only partially support the idea of similar seasonal patterns of BMR variation in New World and Old World shorebirds. We found no correlations of BMR with either Msum or MMR for either raw or mass-independent data, suggesting that basal and maximum aerobic metabolic rates are modulated independently in these species.
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.
Migration Rates of Sutured vs Non-sutured Esophageal Stent Placement
ClinicalTrials.gov study NCT05082948. IPD Sharing: NO. Countries: 1. Publications: 1.
A narrow window for geographic cline analysis using genomic data: effects of age, drift, and migration on error rates
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Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates
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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: Do the high energy lifestyles of shorebirds result in high maximal metabolic rates? - Basal and maximal metabolic rates in least and pectoral sandpipers during migration
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Data from: Faster spring migration in northern wheatears is not explained by an endogenous seasonal difference in refueling rates
A widespread phenomenon in migrant birds is that they travel faster in spring than in autumn. During migration birds spend most time at stopover sites and, correspondingly, the faster spring migration is mainly explained by shorter stopovers in spring than autumn. Because a main purpose of stopovers is to replenish the fuel used in flight, a higher rate of fuel deposition (FDR) in spring is thought to explain the shorter stopovers and hence shorter total duration of migration in spring. Critical migratory processes, including the onset and extent of pre-migratory fueling, are endogenously regulated. It is therefore not unlikely that refueling at stopover sites is, at least partly, also under endogenous control. We here tested whether there is an endogenous seasonal difference in food intake and FDR, which could contribute to shorter stopovers and hence faster migration in spring. We measured daily food intake and daily FDR in two subspecies of the northern wheatear Oenanthe oenanthe, temporarily confined at stopover under identical constant indoor conditions in spring and autumn. The two wheatear subspecies differed markedly in absolute food intake and FDR. Within subspecies, however, food intake and FDR did not differ between spring and autumn, indicating that faster spring migration in northern wheatears is not explained by an endogenously controlled seasonal difference in birds' motivation to refuel. To further substantiate this claim, similar measurements should be taken at other locations along northern wheatears' migration routes. Comparable experiments in other species could test the generality of our results.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.