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Figure 6 in First European evidence for transcontinental dispersal of Crocodylus (late Neogene of southern Italy)
Figure 6. Pectoral girdle elements probably belonging to the same specimen: A, right scapula (RGM 455328); B, right coracoid (RGM 455327). Both in lateral view; scale bar equals 10 mm.
Figure 7 in First European evidence for transcontinental dispersal of Crocodylus (late Neogene of southern Italy)
Figure 7. Vertebrae in right lateral view. A, centrum of cervical vertebra (RGM 453472) separated from the missing neural arch at the level of the open neurocentral suture and showing a long hypapophysis; B, dorsal or lumbar vertebra (DSTF GH2); C, caudal vertebra (RGM 215348). Scale bar equals 10 mm.
Figure 5. A, B in First European evidence for transcontinental dispersal of Crocodylus (late Neogene of southern Italy)
Figure 5. A, B, the lower jaw (RGM 335893) shows no sign of third and fourth confluent alveoli. A, dorsal view; B, detail of the third and fourth alveoli, on the left of the image; C, isolated tooth (RGM 454950) in mesial view; D, isolated tooth (RGM 454280) in labial view. Scale bar equals 10 mm.
Fig. 1-6 in Swimming zooids: an unusual dispersal strategy in the ctenostome bryozoan, Hislopia
Fig. 1-6: (1) Two normal, developing adventitious buds in series (arrows) of the undescribed Thai Hislopia, Scale bar = 0.25 mm. (2) Hislopia zooid with two young nautizooid buds (arrows). Scale bar = 0.25 mm. (3) Hislopia zooid with two nautizooid buds almost ready for release. Scale bar = 0.25 mm. (4) Single Hislopia zooid dissected from a colony, with five nautizooid buds distributed in seemingly random locations around the margin. Scale bar = 0.25 mm. (5) Nautizooid bud, already feeding, ready to break away from the colony. Scale bar = 0.25 mm. (6) Free-swimming nautizooid. Scale bar = 0.25 mm.
Fig. 8 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 8. Scanning electron microscopy. Polymerurus insularis sp. nov. A–B, D. Paratype (ZUEC GCH 59). C, E. Paratype (ZUEC GCH 60). A–B. Posterior dorsal view. C. Detail of the furca base in posterior dorsolateral view. D–E. Details of the furcal rami. Abbreviations: fb = furca base; fr = furcal rami; sc-4 = Type 4 scales; sc-5 = Type 5 scales. Scale bars = 10 µm.
Fig. 4 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 4. Light microscopy – DIC. Polymerurus insularis sp. nov. Posterior region of the body. A. Paratype (ZUEC GCH 56). B, D. Holotype (ZUEC GCH 55). C. Paratype (ZUEC GCH 57). A–B. Posterior dorsal view. C. Posterior dorsolateral view. D. Posterior ventral view. Abbreviations: fr = furcal rami; sc-1 = Type 1 scales; sc-2 = Type 2 scale; sc-3 = Type 3 scales; sc-4 = Type 4 scales. Scale bars = 40 µm.
Fig. 5 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 5. Close-up of the different types of scales described forPolymerurus insularis sp. nov.A–C. Paratype (ZUEC GCH 59). D, F. Holotype (ZUEC GCH 55). E. Paratype (ZUEC GCH 56). A–C. Scanning electron microscopy. D–F. Light microscopy – DIC. A. Detail of a section of the dorsal middle trunk, showing the most common type of scale, Type 1, with emphasis on its characteristic shape. B. Detail of a section of the dorsal posterior trunk, showing Type 2 and Type 3 scales. C–E. Detail of the transition between the dorsal posterior trunk and the dorsal furca base, showing the particular scale covering of this region. F. Detail of the transition between the ventral posterior trunk and the ventral furca base, showing the particular scale covering this region. Abbreviations: sc-1 = Type 1 scales; sc-2 = Type 2 scale; sc-3 = Type 3 scales; sc-4 = Type 4 scales; sc-5 = Type 5 scales; sc-6 = Type 6 scales; sc-7 = Type 7 scales; sc-8 = Type 8 scales; svs = small ventral pair of spines. Scale bars: A–C = 5 µm; D = 10 µm; E = 15 µm; F = 10 µm.
Fig. 3 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 3. Light microscopy – DIC. Polymerurus insularis sp. nov., holotype (ZUEC GCH 55). A–C. Correspond to the most anterior third of the specimen. A. Anterior dorsal region. B. Anterior internal region. C. anterior ventral region. D–F. Correspond to the trunk. D. Dorsal trunk. E. Internal trunk. F. Ventral trunk. G–I. Correspond to the posterior third of the specimen. G. Dorsal posterior third. H. Internal posterior third. I. Ventral posterior third. Abbreviations: ce = cephalion; ct = cephalic bristles; eg = egg; hy = hypostomium; i = intestine; is = interciliary spines; lc = locomotory cilia; lce = lateral cephalic expansions; mo = mouth; ne = nephridia; pl = pleurae; ph = pharynx; PhIJ = pharyngealintestinal junction; sc-1 = Type 1 scales; sc-2 = Type 2 scale; sc-3 = Type 3 scales; sc-4 = Type 4 scales; vs = Type 1 ventral scale. Scale bars = 20 µm.
Fig. 1 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 1. Sampling location, at the state of Pernambuco, Fernando de Noronha archipelago, Brazil A. Brazil. B. Fernando de Noronha Archipelago. C. Xaréu açude. Images provided by Google Earth (A–B) and Prof Dr Felipe Toledo, University of Campinas (C).
Fig. 6 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 6. Schematic illustration of dorsal and ventral posterior regions and type scales of Polymerurus insularis sp. nov. A–B. Paratype (ZUEC GCH 56). A. Dorsal view of the posterior end. Some Type 1 scales are faded for a better visualization of Types 2, 3 and 5 scales. B. Ventral view of the posterior end. C. Each type of scale, individually depicted (not to scale). Abbreviations: ff = furcal furrow; fr = furcal rami; lc = locomotory cilia; is = interciliary spines; sc-1 = Type 1 scales; sc-2 = Type 2 scale; sc-3 = Type 3 scales; sc-4 = Type 4 scales; sc-5 = Type 5 scales; sc-6 = Type 6 scales; sc-7 = Type 7 scales; sc-8 = Type 8 scales. Scale bars = 40 µm.
Fig. 9 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 9. Maximum Likelihood tree based on multigene approach with 18S and 28S sequences. Highlighted branches correspond to the Polymerurus Remane, 1927 species sequences. Values on the branches correspond, respectively, to: SH-aLRT support (%) / aBayes support / ultrafast bootstrap support (%).
Fig. 2 in Long distance dispersal and pseudo-cryptic species in Gastrotricha: first description of a new species (Chaetonotida, Chaetonotidae, Polymerurus) from an oceanic island with volcanic rocks
Fig. 2. Light microscopy – DIC. Polymerurus insularis sp. nov., holotype (ZUEC GCH 55). Full body view. A. Dorsal view. B. Internal view. C. Ventral view. Scale bars = 30 µm.
Data and materials for "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript"
<p>Data and sripts for the "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript" manuscript, sent to BMC Bioinformatics</p>
Data for: Eco-evolutionary consequences of dispersal syndromes during colonization in a passerine bird
<p>In most animal species, dispersing individuals possess phenotypic attributes that mitigate the costs of colonization and/or increase settlement success in new areas ('dispersal syndromes'). This phenotypic integration likely affects population dynamics and the direction of selection, but data are lacking for natural populations. Using an approach that combines population dynamics, quantitative genetics and phenotypic selection analyses, we reveal the existence of dispersal syndromes in a pied flycatcher (<em>Ficedula</em> <em>hypoleuca</em>) population in The Netherlands: immigrants were larger, tended to have darker plumage, bred earlier and produced larger clutches than local recruits, and some of these traits were genetically correlated. Over time, the phenotypic profile of the population gradually changed: each generation advanced arrival and breeding and exhibited longer wings as the result of direct and indirect selection on these correlated traits. Although phenotypic attributes of immigrants were favored by selection during the early phase of colonization, observed phenotypic changes were similar for immigrants and local recruits. We propose that immigrants facilitated initial population establishment but that temporal changes likely resulted from climate change-induced large-scale selection. This study highlights that newly established populations are of non-random composition and that phenotypic architecture affects evolutionary population trajectories. </p>
Code and data from: A hierarchical approach for estimating state-specific mortality and state transition in dispersing animals with incomplete death records
<p>Unbiased mortality estimates are fundamental for testing ecological and evolutionary theory as well as for developing effective conservation actions. However, mortality estimates are often confounded by dispersal, especially in studies where dead-recovery is not possible. In such instances, missing individuals (i.e. individuals with unobserved time of death) may have died or permanently emigrated from a study area, making inferences about their fate difficult. Mortality before and during dispersal, as well as the decision to disperse, usually depend on a suite of individual, social, and environmental covariates, which in turn can be used to draw conclusions about the fate of missing individuals.<br>Here, we propose a Bayesian hierarchical model that takes into account time-varying covariates to estimate transitions between life-history states and mortality in each state using mark-resighting data with missing individuals. Specifically, our framework estimates mortality rates in two states (resident and dispersing state) by treating the fate of missing individuals as a latent (i.e. unobserved) variable that is statistically inferred based on information from individuals with a known fate and given the individual, social, and environmental conditions at the time of disappearance. Our model also estimates rates of state transition (i.e. emigration) to assess whether a missing individual was more likely to have died or survived due to unobserved emigration from the study area. <br>We used simulations to check the validity of our model and assessed its performance with data of varying degrees of uncertainty. Our modeling framework provided accurate mortality and emigration estimates for simulated data of different sample sizes, proportions of missing individuals, and resighting intervals. Variation in sample size appeared to affect the precision of estimated parameters the most.<br>Our approach offers a solution to estimating unbiased mortality of both resident and dispersing individuals as well as the probability of emigration using mark-resighting data with incomplete death records. Conditional on the availability of data on known-fate individuals and relevant time-varying covariates, our model can reconstruct the fate (death or emigration) of missing individuals. The modularity of our framework allows mortality analyses to be tailored to a variety of species-specific life histories.</p>
Phonon dispersion and eigenvectors of Cd2Re2O7
<p>This dataset includes the raw data in YAML format obtained from the Phononpy calculations for the tetragonal Cd2Re2O7. One can use this dataset for visualizing the phonon spectra, and the phonon displacement pattern at any q-point (for example, the N point).</p>
Data from: Timing and probability of arrival for sea lice dispersing between salmon farms
<p>Sea lice are a threat to the health of both wild and farmed salmon and an economic burden for salmon farms. With a free-living larval stage, sea lice can disperse tens of kilometers in the ocean between salmon farms, leading to connected sea lice populations that are difficult to control in isolation. In this paper, we develop a simple analytical model for the dispersal of sea lice between two salmon farms. From the model we calculate the arrival time distribution of sea lice dispersing between farms, as well as the level of cross-infection of sea lice. We also use numerical flows from a hydrodynamic model, coupled with a particle tracking model, to directly calculate the arrival time of sea lice dispersing between two farms in the Broughton Archipelago, BC, in order to fit our analytical model and find realistic parameter estimates. Using the parametrized analytical model we show that there is often an intermediate inter-farm spacing that maximizes the level of cross-infection between farms, and that increased temperatures will lead to increased levels of cross-infection.</p>
Non-reproductive dispersal: An important driver of migratory range dynamics and connectivity
<p>Dispersal is the primary ecological process underpinning spatial dynamics in motile species by generating flux in reproductive locations over time. In migratory species, dispersal can also occur around non-breeding ranges, but this form currently lacks a unifying theoretical framework. We present a novel conceptual model for dispersal in migrants that builds upon existing literature, differentiating 'reproductive' dispersal (i.e. changes in breeding locations) from 'non-reproductive' dispersal, which we define as movements resulting in inter-annual or inter-generational changes in non-breeding locations. Crucially, unlike reproductive dispersal where movement outcomes are naturally propagated between generations, the outcomes of non-reproductive dispersal can be non-heritable even if dispersers survive to reproduce. We simulate a non-social migratory population with a genetically-determined migratory programme to model how heritability of this program influences both migratory connectivity and range shift propensity. When exposed to spatially-uncoupled shifts in habitable ranges (i.e. seasonal climate niches shifting at different rates), long-term persistence of simulated populations required changes in migratory programmes to arise through heritable forms of non-reproductive dispersal (e.g. mutations in migratory gene complexes). By contrast, non-heritable dispersal mechanisms (e.g. weather drift, navigation errors) did not drive long-term shifts in non-breeding ranges, despite being a major component of realised dispersal and migratory connectivity patterns. Migratory connectivity metrics conflate these heritable and non-heritable drivers of non-reproductive dispersal and therefore have limited power in predicting spatial population responses to environmental change. Our models provide a framework for improving our understanding of spatial dynamics in migratory populations and highlight the importance of teasing apart the genetic or cultural mechanisms that drive inter-generational migratory variability in order to evaluate and predict range plasticity in migrants.</p>
Data from: Dispersal and establishment traits provide a colonization advantage for a polyploid apomictic plant
<p><span><strong>Premise</strong>: Apomictic plants (reproducing asexually through seed) often have larger ranges and occur at higher latitudes than closely related sexuals, a pattern known as geographical parthenogenesis (GP). Explanations for GP include differences in colonizing ability due to reproductive assurance and direct/indirect effects of polyploidy (most apomicts are polyploid) on ecological tolerances. While life history traits associated with dispersal and establishment also contribute to the potential for range expansion, few studies compare these traits in related apomicts and sexuals. </span></p> <p><span><strong>Methods</strong>: We investigated differences in early life history traits between diploid-sexual and polyploid-apomictic <em>Townsendia hookeri </em>(Asteraceae), which displays a classic pattern of GP. Using lab and greenhouse experiments, we measured seed dispersal traits, germination success, and seedling size and survival in sexual and apomictic populations from across the range. </span></p> <p><span><strong>Key Results</strong>: While theory predicts that trade-offs between dispersal and establishment traits should be common, this was largely not the case in <em>T. hookeri</em>. Apomictic seeds had both lower terminal velocity (staying aloft longer when dropped) and higher germination success than sexual seeds. While there were no differences in seedling size between reproductive types, apomicts did, however, have slightly lower seedling survival than sexuals. </span></p> <p><span><strong>Conclusions</strong>: These differences in early life history traits, combined with reproductive assurance conferred by apomixis, suggest that apomicts achieve a greater range through advantages in their ability to both spread and establish. </span></p>
Priority effects determine how dispersal affects biodiversity in seasonal metacommunities
<p><span>The arrival order of species frequently determines the outcome of their interactions. This phenomenon, called the priority effect, is ubiquitous in nature and determines local community structure, but we know surprisingly little about how it influences biodiversity across different spatial scales. Here, we use a seasonal metacommunity model to show that biodiversity patterns and the homogenizing effect of high dispersal depend on the specific mechanisms underlying priority effects. When priority effects are only driven by positive frequency dependence, dispersal-diversity relationships are sensitive to initial conditions but generally show a hump-shaped relationship: biodiversity declines when dispersal rates become high and allow the dominant competitor to exclude other species across patches. When spatiotemporal variation in phenological differences alters species' interaction strengths (trait-dependent priority effects), local, regional, and temporal diversity are surprisingly insensitive to variation in dispersal, regardless of the initial numeric advantage. Thus, trait-dependent priority effects can strongly reduce the effect of dispersal on biodiversity, preventing the homogenization of metacommunities. Our results suggest an alternative mechanism that maintains local and regional diversity without environmental heterogeneity, highlighting that accounting for the mechanisms underlying priority effects is fundamental to understanding patterns of biodiversity.</span></p>
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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)
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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.