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2,911 results for “dispersal”
FIGURE 3 in A new Megatheriinae skull (Xenarthra, Tardigrada) from the Pliocene of Northern Venezuela - implications for a giant sloth dispersal to Central and North America
FIGURE 3. Skulls of 1: Eremotherium laurillardi, 2: Eremotherium eomigrans, 3: AMU-CURS 184, cf. Proeremotherium sp., and 4: Proeremotherium eljebe (AMU-CURS 126, type), compared in (from top to bottom) dorsal, lateral and palatal views. In light grey are the upper dental series alveoli contours of each skull; black arrows shows the outline and extension of the posterior palatal notch, and up to where it reaches in relation to the dental series (in 1 the dotted line is used because that part of the palatal notch was mechanically broken).
FIGURE 2 in A new Megatheriinae skull (Xenarthra, Tardigrada) from the Pliocene of Northern Venezuela - implications for a giant sloth dispersal to Central and North America
FIGURE 2. Skulls of AMU-CURS 184 and AMU-CURS 126 (Proeremotherium eljebe type specimen). AMU-CURS 184 in 1, dorsal; 3, lateral, and 5, palatal views. Proeremotherium eljebe in 2, dorsal; 4, lateral, and 6, palatal views.
FIGURE 1. Location map showing the locality where the AMU-CURS 184 in A new Megatheriinae skull (Xenarthra, Tardigrada) from the Pliocene of Northern Venezuela - implications for a giant sloth dispersal to Central and North America
FIGURE 1. Location map showing the locality where the AMU-CURS 184 specimen was recovered from San Gregorio Fm. outcrops.
Data and code for: A supergene controlling social structure in Alpine ants also affects the dispersal ability and fecundity of each sex
<p>Social organisation, dispersal and fecundity co-evolve, but whether they are genetically linked remains little known. Supergenes are prime candidates for coupling adaptive traits and mediating sex-specific trade-offs. Here, we test whether a supergene that controls social structure in <em>Formica selysi</em> also influences dispersal-related traits and fecundity within each sex. In this ant species, single-queen colonies contain only the ancestral supergene haplotype <em>M</em> and produce<em> MM</em> queens and <em>M</em> males, while multi-queen colonies contain the derived haplotype <em>P</em> and produce <em>MP </em>queens, <em>PP</em> queens, and <em>P</em> males. By combining multiple experiments, we show that the <em>M </em>haplotype induces phenotypes with higher dispersal potential and higher fecundity, for both sexes. Specifically, <em>MM</em> queens, <em>MP</em> queens, and <em>M </em>males are more aerodynamic and more fecund than <em>PP </em>queens and <em>P</em> males, respectively. Differences between <em>MP</em> and <em>PP</em> queens from the same colonies reveal a direct genetic effect of the supergene on dispersal-related traits and fecundity. The derived haplotype <em>P</em>, associated with multi-queen colonies, produces queens and males with reduced dispersal abilities and lower fecundity. More broadly, similarities between the <em>Formica </em>and <em>Solenopsis</em> systems reveal that supergenes play a major role in linking behavioural, morphological, and physiological traits associated with intraspecific social polymorphisms.</p>
Particle Dispersion Model Dataset
<p>Data repository for the paper:</p> <p>Dispersion Model for Level Control of Bubbling Fluidized Beds with Particle Cross-Flow</p> <p>Chemical Engineering Research and Design 2025</p>
CLDF dataset derived from Grollemund et al.'s "Bantu expansion shows habitat alters the route and pace of human dispersals" from 2015
<p>Cite the source of the dataset as:</p> <blockquote> <p>Grollemund, Rebecca, Branford, Simon, Bostoen, Koen, Meade, Andrew, Venditti, Chris, & Pagel, Mark (2015) Bantu expansion shows habitat alters the route and pace of human dispersals. Proc Natl Acad Sci USA. doi:10.1073/pnas.1503793112.</p> </blockquote>
Imaging the sediment cover offshore central Chile with surface-wave dispersion and P-wave conversion using DAS
<p>This repository contains codes and data used to reproduce the figures in the paper <em>Vernet, C. et al, "Imaging the sediment cover offshore central Chile with surface-wave dispersion and P-wave conversion using distributed acoustic sensing", 2025, (<a href="https://doi.org/10.1029/2024JB030507">https://doi.org/10.1029/2024JB030507</a>).</em></p>
Data from: Evolution of dispersal, habit, and pollination in Africa pushed Apocynaceae diversification after the Eocene-Oligocene climate transition
<p>Apocynaceae (the dogbane and milkweed family) is one of the ten largest flowering plant families, with approximately 5,350 species and diverse morphology and ecology, ranging from large trees and lianas that are emblematic of tropical rainforests, to herbs in temperate grasslands, to succulents in dry, open landscapes, and to vines in a wide variety of habitats. Despite a specialized and conservative basic floral architecture, Apocynaceae are hyperdiverse in flower size, corolla shape, and especially derived floral morphological features. These are mainly associated with the development of corolline and/or staminal coronas and a spectrum of integration of floral structures culminating with the formation of a gynostegium and pollinaria—specialized pollen dispersal units. To date, no detailed analysis has been conducted to estimate the origin and diversification of this lineage in space and time. Here, we use the most comprehensive time-calibrated phylogeny of Apocynaceae, which includes approximately 20% of the species covering all major lineages, and information on species number and distributions obtained from the most up-to-date monograph of the family to investigate the biogeographical history of the lineage and its diversification dynamics. South America, Africa, and Southeast Asia (potentially including Oceania), were recovered as the most likely ancestral area of extant Apocynaceae diversity; this tropical climatic belt in the equatorial region retained the oldest extant lineages and these three tropical regions likely represent museums of the family. Africa was confirmed as the cradle of pollinia-bearing lineages and the main source of Apocynaceae intercontinental dispersals. We detected 12 shifts toward accelerated species diversification, of which 11 were in the APSA clade (apocynoids, Periplocoideae, Secamonoideae, and Asclepiadoideae), eight of these in the pollinia-bearing lineages and six within Asclepiadoideae. Wind-dispersed comose seeds, climbing growth form, and pollinia appeared sequentially within the APSA clade and probably work synergistically in the occupation of drier and cooler habitats. Overall, we hypothesize that temporal patterns in diversification of Apocynaceae was mainly shaped by a sequence of morphological innovations that conferred higher capacity to disperse and establish in seasonal, unstable, and open habitats, which have expanded since the Eocene-Oligocene climate transition.</p>
Figs 3–4 in Dispersal History Of An Invasive Rodent In Hungary - Subfossil Finds Of Rattus Rattus
Figs 3–4. Skull (ventral view) of one of the black rats from site: 3 = Budapest, District XVII, Péceli Road (Roman Period); 4 = Dusnok–Szúnyogosi dűlő (Roman Period). Scale bars 10 mm
Fig. 1 in Dispersal History Of An Invasive Rodent In Hungary - Subfossil Finds Of Rattus Rattus
Fig. 1. Investigated archaeological sites in Hungary with small mammal fauna. = open air sites with using flotation method, black rat absence; = open air/cave sites with using flotation method,
Desiccation stress acts as cause as well as cost of dispersal in Drosophila melanogaster
<p>Environmental stress is one of the important causes of biological dispersal. At the same time, the process of dispersal itself can incur and/or increase susceptibility to stress for the dispersing individuals. Therefore, in principle, stress can serve as both a cause and a cost of dispersal. We studied these potentially contrasting roles of a key environmental stress (desiccation) using Drosophila melanogaster. By modulating water and rest availability, we asked whether: (a) dispersers are individuals that are more susceptible to desiccation stress, (b) dispersers pay a cost in terms of reduced resistance to desiccation stress, (c) dispersal evolution alters the desiccation cost of dispersal, and (d) females pay a reproductive cost of dispersal. We found that desiccation was a clear cause of dispersal in both sexes, as both male and female dispersal propensity increased with increasing duration of desiccation. However, the desiccation cost of dispersal was male-biased, a trend unaffected by dispersal evolution. Instead, females paid a fecundity cost of dispersal. We discuss the complex relationship between desiccation and dispersal, which can lead to both positive and negative associations. Furthermore, the sex differences highlighted here may translate into differences in movement patterns, thereby giving rise to sex-biased dispersal patterns.</p>
Simulation outputs used in "Individual variation in dispersal, and its sources, shape the fate of pushed vs. pulled range expansions"
<p>Simulation outputs used in "Individual variation in dispersal, and its sources, shape the fate of pushed vs. pulled range expansions" (by Maxime Dahirel, Chloé Guicharnaud and Elodie Vercken)</p> <p>This is a copy for archiving purposes of the saved outputs from a NetLogo simulation model of range expansions, used in the analyses described in the following GitHub repository: https://github.com/mdahirel/pushed-pulled-2020-heritability-IBM (Zenodo archive: https://doi.org/10.5281/zenodo.5830993)</p> <p>This .csv file is the final output of the "generate_simulations" code in that repo, and feeds into in the "analyse_simulations" and "supplementary" codes. It is meant to be copied in the NetLogo_output folder of the aforementioned repo after download, in case one:</p> <p>- wants to check our analysis code</p> <p>- and does not want/ have time to re-run the simulations from scratch</p> <p>For any other information, including on the contents of the csv, please see the aforementioned repository</p> <p> </p>
Data for 'Selfish migrants: How a meiotic driver is selected to increase dispersal'
<p>Data for 'Selfish migrants: How a meiotic driver is selected to increase dispersal'</p> <p>Please refer to the README for information.</p>
Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks
<p>This Data set contain 29 table of weighted interaction network between plants (columns) and frugivore birds from the Brazilian Atlantic Forest used in the manuscript "Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks" published in Oikos Journal.</p>
Supplementary material for: Phylogeny and biogeography of the ancient spider family Filistatidae (Araneae) is consistent both with long-distance dispersal and vicariance following continental drift
<p>Raw data and input files for phylogenetic and biogeographic analysis of the article "<strong>Phylogeny and biogeography of the ancient spider family Filistatidae (Araneae) is consistent both with long-distance dispersal and vicariance following continental drift</strong>".</p> <p><strong>Supplementary material S1. </strong>Matrix of phenotypic characters in .ss format.</p> <p><strong>Supplementary material S2. </strong>Alignment of COI sequences in fasta format..</p> <p><strong>Supplementary material S3. </strong>Alignment of H3 sequences in fasta format.</p> <p><strong>Supplementary material S4. </strong>Alignment of 16S sequences in fasta format before trimming with gblocks.</p> <p><strong>Supplementary material S5. </strong>Alignment of 28S sequences in fasta format before trimming with gblocks.</p> <p><strong>Supplementary material S6. </strong>Input for running parsimony analysis using TNT (phenotypic data only).</p> <p><strong>Supplementary material S7. </strong>Input for running Bayesian inference using MrBayes (phenotypic data only).</p> <p><strong>Supplementary material S8. </strong>Input for running parsimony analysis using TNT (sequence data only).</p> <p><strong>Supplementary material S9. </strong>Input for running Bayesian inference using MrBayes (sequence data only).</p> <p><strong>Supplementary material S10. </strong>Input for running parsimony analysis using TNT (total evidence).</p> <p><strong>Supplementary material S11. </strong>Input for running Bayesian inference using MrBayes (total evidence).</p> <p><strong>Supplementary material S12. </strong>Input for running parsimony analysis using TNT (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S13. </strong>Input for running Bayesian inference using MrBayes (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S14. </strong>Input for running Bayesian inference using MrBayes (total evidence) and estimating node ages using tip-dating.</p> <p><strong>Supplementary material S15. </strong>Input for running Bayesian inference using Beast (sequence data only) and estimating node ages using node-dating.</p> <p><strong>Supplementary material S16. </strong>Raw geographic distances among areas in each time slice and dispersal probability matrices for each biogeographic model.</p> <p><strong>Supplementary material S17. </strong>Inputs for estimating ancestral ranges and performing biogeographic stochastic maps for our dataset.</p> <p><strong>Supplementary material S18. </strong>Consensus tree found with parsimony analysis using TNT (phenotypic data only).</p> <p><strong>Supplementary material S19. </strong>Consensus tree found with Bayesian inference using MrBayes (phenotypic data only).</p> <p><strong>Supplementary material S20. </strong>Consensus tree found with parsimony analysis using TNT (sequence data only).</p> <p><strong>Supplementary material S21. </strong>Consensus tree found with Bayesian inference using MrBayes (sequence data only).</p> <p><strong>Supplementary material S22. </strong>Consensus tree found with parsimony analysis using TNT (total evidence).</p> <p><strong>Supplementary material S23. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence).</p> <p><strong>Supplementary material S24. </strong>Consensus tree found with parsimony analysis using TNT (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S25. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence, dataset with reduced number of terminals).</p> <p><strong>Supplementary material S26. </strong>Consensus tree found with Bayesian inference using MrBayes (total evidence) and with node ages estimated using tip-dating.</p> <p><strong>Supplementary material S27. </strong>Maximum clade credibility tree found with Bayesian inference using Beast (sequence data only) and with node ages estimated using node-dating.</p>
Data from: Seed fate in ant-mediated dispersal: Seed dispersal effectiveness in the Ectatomma ruidum (Formicidae) - Zanthoyxlum ekmanii (Rutaceae) system
<p>Plants are often dispersal limited relying on passive or active agents to find suitable microhabitats for germination. Seeds of pioneer tree species, for example, require light gaps for growth but have short median dispersal distances and often do not provide a food reward to encourage animal dispersal. Zanthoxylum ekmanii seeds are frequently moved by ants but evaluating the effectiveness of ant-mediated seed removal requires knowledge of the species moving the seeds, how far they are moved, and the deposition site. To assess the effectiveness of ants as seed dispersers of Z. ekmanii, we utilized the seed dispersal effectiveness framework. We tracked the movement of seeds from caches on the forest floor, revealing that foragers of Ectatomma ruidum moved 32.8% of seeds an average first distance of 99.8 cm with 68.3% of those seeds taken into a colony. The quality of deposition location was assessed using a seedling emergence study where freshly germinated seeds were buried at different depths. Seedlings were primarily able to emerge from the shallowest depths. Wax castings of E. ruidum colonies demonstrated that seeds brought into the colony were deposited in chambers that had larvae present and experienced more damage than seeds unhandled by ants. Foragers, however, did not have a strong enough bite force to rupture Z. ekmanii seeds likely because their muscle morphology is not structured to maximize force generation. Overall, E. ruidum may help fine tune deposition location, incorporating seeds into the topsoil, though few seeds will likely emerge if soil bioturbation is low.</p>
Morphological adaptations linked to flight efficiency and aerial lifestyle determine natal dispersal distance in birds
<p>Natal dispersal—the movement from birthplace to breeding location—is often considered the most significant dispersal event in an animal's lifetime. Natal dispersal distances may be shaped by a variety of intrinsic and extrinsic factors, and remain poorly quantified in most groups, highlighting the need for indices that capture variation in dispersal among species.</p> <p>In birds, it is hypothesized that dispersal distance can be predicted by flight efficiency, which can be estimated using wing morphology. However, the use of morphological indices to predict dispersal remains contentious and the mechanistic links between flight efficiency and natal dispersal are unclear.</p> <p>Here, we use phylogenetic comparative models to test whether hand-wing index (HWI, a morphological proxy for wing aspect ratio) predicts natal dispersal distance across a global sample of 114 bird species. In addition, we assess whether HWI is correlated with flight usage in foraging and daily routines.</p> <p>We find that HWI is a strong predictor of both natal dispersal distance and a more aerial lifestyle.</p> <p>Our results support the use of HWI as a valid proxy for relative natal dispersal distance, and also suggest that evolutionary adaptation to aerial lifestyles is a major factor connecting flight efficiency with patterns of natal dispersal.</p>
Fig. 3 in Fossil Ovibos Moschatus (Artiodactyla, Bovidae) From Buryn, With Reference To Muskox Dispersal In The Late Pleistocene Of Ukraine
Fig. 3. Last Glacial maximum distribution of Ovibos moschatus (after Kahlke, 2014, with modifications). Previously known localities with fossil muskox remains within the territory of Ukraine are indicated by circles. The find described herein is indicated by square.
Fig. 2 in Fossil Ovibos Moschatus (Artiodactyla, Bovidae) From Buryn, With Reference To Muskox Dispersal In The Late Pleistocene Of Ukraine
Fig. 2. Skull fragment of muskox from the Buryn district local history museum in dorsal (A), ventra (B), lateral (C), and posterior view (D). Scale bar equals 10 cm in A and B, 5 cm in C and D.
Fig. 4 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals
Fig. 4. Geographical and palaeogeographical locations of the studied area with arrows indicating dispersals of different species of the genus Praepusa from the Eastern Paratethys westward: 1 — Praepusa vindobonensis: Western Kazakhstan and Austria, Middle Miocene, early Sarmatian (16.5–11.2 Ma); 2 — Pr. vindobonensis (= tarchankutica): Ukraine and Moldova, Middle Miocene, middle Sarmatian (13.6–12.3 Ma); 3 — Pr. pannonica: Moldova and Hungary, Middle Miocene, early-middle Sarmatian (12.3–11.2 Ma). 4 — Pr. magyaricus: Vienna Basin, middle Sarmatian, Middle Miocene (13.6–12.3 Ma); 5 — Pr. boeska: The Netherlands and Belgium, Late Miocene — Early Pliocene (11.6–3.2 Ma).
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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.