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87 results for “dispersal evolution”
Morphological cladogenesis and terminal dwarfing in extinct Late Miocene through Pliocene menardiform globorotalids: New complementary data to «Evolutionary prospection in the Neogene planktic foraminifer Globorotalia menardii and related forms from ODP Hole 925B (Céara Rise, western tropical Atlantic): evidence for gradual evolution superimposed by long distance dispersal ?, Swiss J. Palaeontology, 135:205-248»
<p>A complementary morphometric data set is provided to the study of Knappertsbusch (2016) about the shell evolution of menardiform globorotalids (Neogene planktic foraminifera) at ODP Hole 925B from Céara Rise in the the western tropical Atlantic. The new measurements confirm splitting of extinct <em>Globorotalia multicamerata</em> from the <em>G. menardii</em> stock via the intermediate form <em>G. limbata</em> between about 6 Ma to 5 Ma ago. After splitting both <em>G. limbata</em> and <em>G. multicamerata</em> show gradual divergence from <em>G. menardii</em> in several shell parameters illustrating morphological cladogenesis. Between 2.88 Ma and 2.59 Ma the same parameters show a concerted trend towards reduced values indicating pre-extinction dwarfing. A comparison with published literature data of Delta<sup>18</sup>O trends between species, that populated the mixed layer (<em>Globigerinoides sacculifer</em>) and the thermocline layer (<em>Neogloboquadrina dutertrei</em>) at this location during those times suggests, that both divergence and subsequent dwarfing trends were probably the results of changes in upper watermass stratification.</p> <p>The complementary data set is provided in six zipped archives APPENDIX A, B, C, D, E and F (zipped with free software 7-Zip 22.00 (x64), 2022-06-15 from 1999-2022 Igor Pawlow), together with a description of the data in file Report_925B_suppl_1.pdf.</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>
FIGURE 8 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 8. Reconstruction of?A. nikolovi sp. nov. from Bulgaria. Artwork by Velizar Simeonovski, Chicago. The reconstruction was developed by a regressive estimate of the coloration of the modern A. melanoleuca, based on the variation of the coloration of Ursus arctos. Ursus arctos is used for calibration because the variation of its coloration (geographic, ecological, and individual) provides the most comprehensive model for the evolution of the coloration in Ursidae genera.
FIGURE 6 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 6. Lower teeth of Agriarctos and Ailurarctos. A, cf. Agriarctos sp. from Gau-Weinheim, m1 and m2 (reversed), from Weitzel and Tobien (1952) and Tobien (1955); B, cf. Ag. depereti from Gau-Weinheim, m1, from Weitzel and Tobien (1952); C, Agriarctos depereti from Melchingen, from top to bottom m1 and m2 (both reversed), from Schlosser (1902), Depéret and Llueca (1928); D, cf. Ag.?depereti from Dorn-Dürkheim 1, from top to bottom m1 and m2 (both reversed), from Roth and Morlo (1997); E, Ai. lufengensis p4, V6892.13 (reversed); F, Ag. vighi, HSGI Ob/ 5691 from Rózsaszentmárton, m1 (reversed), photos courtesy of J. Wagner; G1, Ag. gaali V.60.1751 from Hatvan, from top to bottom p3 and p4, photos courtesy of J. Wagner; G2, Ag. gaali V.60.1751 from Hatvan, from top to bottom m1 and m2, photos courtesy of J. Wagner; H1, Ai. yuanmouensis, from top to bottom m1 (YICRA YV2509.5, reversed) and m2 (YICRA YV2509.4, reversed); H2, Ai. yuanmouensis, from top to bottom m2 (YICRAYV2509.2) and m2 (YICRAYV2509.3, reversed); I1, Ai. lufengensis, from top to bottom m1 (IVPP V6892.9), m3 (IVPP V6892.11, reversed), and m3 (IVPP V6892.10); I2, Ai. lufengensis, from top to bottom m1 (IVPP V25032), m2 (IVPP V6892.10); J1, A. melanoleuca from top to bottom m1 and m2 (IOZ32755, reversed); J2, A. melanoleuca from top to bottom p4 and m3 (IOZ32755, reversed). Not to scale.
FIGURE 3 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 3. Upper dentition (PA) of?Agriarctos nikolovi in comparison with other representatives of Ailuropodini. A, cf. Ag. depereti, uncatalogued cast of MHNL AA52bis in the collection of the University of Vienna; B,?Ag. nikolovi NMNHS FM3546-a (reversed for comparison); C, Ai. yuanmouensis, YICRA YV2509.1 (reversed); D, Ai. lufengensis, IVPP V6892.12; E, A. microta, IVPP V14564; F1-3, A. melanoleuca, IOZ32756, IOZ26449, IOZ32755. Not to scale.
FIGURE 2 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 2. Teeth of?Ag. nikolovi: A, NMNHS FM3546-b, upper canine in labial and lingual views; B, NMNHS FM3546-a, P4 in buccal, occlusal, and lingual views.
FIGURE 5 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 5. Upper teeth of Agriarctos and Ailurarctos. A1, cf. Ag. depereti from Soblay, from top to bottom P4, M1, and M2, from Viret (1949); A2, cf. Ag. depereti from Soblay, from top to bottom P4, M1, and M2, cast from University of Vienna, MC AA 52bis; B, cf. Ag. depereti from Dorn-Dürkheim 1, from top to bottom P4 uncatalogued cast of MHNL AA52bis (reversed), M1 (reversed), and M2, uncatalogued casts of MHNL AA50-51 (reversed), all in the collection of the University of Vienna, modified from Roth and Morlo (1997); C, Ai. yuanmouensis, from top to bottom P4, M1, and M2 (YICRA YV2509.1, reversed); D1, Ai. lufengensis, from top to bottom P4 (IVPP V6892.12), M1 (IVPP V6892.2, reversed), and M2 (IVPP V6892.6, reversed); D2, Ai. lufengensis, from top to bottom P4 (IVPP V6892.1, reversed), M1 (IVPP V6892.3), and M2 (IVPP V6892.6); D3, Ai. lufengensis, from top to bottom P4 (IVPP V6892.8), P2 (left, IVPP V6892.7) and P3 (right, IVPP V6892.7), and M2 (IVPP V6892.5, reversed); E, A. melanoleuca P4, M1 and M2 (IOZ32755, reversed). Not to scale.
FIGURE 7 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 7. Proposed dispersal route of Ailuropodini. The red area indicates the possible distribution of the ancestor of Ailuropodini. Background from Geomapapp.
Data for: Co-evolution of dormancy and dispersal in spatially autocorrelated landscapes
<p>The evolution of dispersal can be driven by spatial processes, such as landscape structure, and temporal processes, such as disturbance. Dormancy, or dispersal in time, is generally thought to evolve in response to temporal processes. In spite of broad empirical and theoretical evidence of trade-offs between dispersal and dormancy, we lack evidence that spatial structure can drive the evolution of dormancy. Here, we develop a simulation-based model of the joint evolution of dispersal and dormancy in spatially heterogeneous landscapes. We show that dormancy and dispersal are each favored under different landscape conditions, but not simultaneously under any of the conditions we tested. We further show that, when dispersal distances are short, dormancy can evolve directly in response to landscape structure. In this case, selection is primarily driven by benefits associated with avoiding kin competition. Our results are similar in both highly simplified and realistically complex landscapes.</p>
Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)
<p>Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)</p> <p>DATA DOI: https://doi.org/10.5281/zenodo.8322080</p> <p>Associated article DOI: https://doi.org/10.1002/ece3.10588</p> <p>Ryan C. Burner, Jorg Stephan, Juha Siitonen, Tord Snall, et al. 2023</p> <p>ryan.c.burner@gmail.com</p> <p>This data release contains data files needed to run the Hmsc models described in the associated publication. It is a subset of the complete beetle capture and environmental covariate dataset maintained by Juha Siitonen (see associated manuscript for references to prior publications). It contains the following four files:</p> <p>1) Species_detections.csv</p> <p>This site_year x species table has detection/non-detection (1/0) values for each species at each site_year. Beetles were trapped at about 142 sites in Finland forests. Includes only beetle species (n = 212) which are considered saproxylic and which were detected at >=5 sites in the dataset, and for which trait information was available. Species names are as originally identified in the source dataset (see early publications by Juha Siitonen). Row names ('Row_ID'), which consist of [site]_[year], correspond to 'Row_ID' in the 'Site_covariates.csv' file. Species (column) names correspond to species row naes in 'Species_traits.csv'</p> <p>2) Site_covariates.csv</p> <p>This table has one row for each 'Row_ID' (n = 142) corresponding to rows in 'Species_data.csv'. Covariate columns have been scaled and centered for modeling. Columns are as follows:</p> <p>rowID - [site]_[year] of sampling<br> Year - year of sampling<br> Site - site name/number<br> climID - unique ID for each grid cell from which climate data were extracted<br> lat_WGS84 - latitude (WGS84)<br> lon_WGS84 - longitude (WGS84)<br> VD10 - scaled and centered total pooled volume of local standing and fallen dead trees (originally in m3/ha, before scaling) with a minimum diameter of 10 cm, estimated using transects<br> agedomin - scaled and centered mean age of the five oldest trees in the stand<br> OldFor_1km - scaled and centered volume of living wood in those forests older than 100 years within a one km radius around each site<br> MeanTemp - scaled and centered mean temperature during the trapping period, from mean of all ERA5 hourly estimates of 2m temperature (see manuscript for details)<br> TotalPrecip - scaled and centered total precipitation during the trapping period, from ERA5 summed across all hourly estimates of total precipitation (see manuscript for details)<br> globRad_WHm2 - scaled and centered total solar radiation during the trapping period, summed across all daily values, based on site slope and aspect, calculated using GIS (see manuscript for details). Units were Wh/m2 prior to scaling and centering.<br> log_Nr_traps - scaled and centered log-transformed number of traps used at each capture site </p> <p><br> 3) Species_traits.csv</p> <p>Trait data, based on trait values in Hagge et al. (2021 - see manuscript for full reference), for beetle species included in model (see species data information, above). In some cases traits are from synonyms used in Hagge that differ from taxonomy of this dataset. Traits have been scaled and centered. Row names are species names that match columns in 'Species_detections.csv'. Columns as follows:</p> <p>wing_length - scaled and centered (log(wing length divided by body length))<br> wing_load - scaled and centered (log(mass / wing area / body length))<br> wing_aspect - scaled and centered (log(wing aspect ratio)</p> <p><br> 4) Phylotree.csv</p> <p>A phylogenetic tree for the species in this dataset, written in the Newick (also known as New Hampshire) format. The tree is based on the species-level insect tree in Chesters et al. (2017) (see manuscript for full citation) but has missing species added randomly to the correct genus (when present) or family or (occassionally) order.</p>
Data for: Co-evolution of dormancy and dispersal in spatially autocorrelated landscapes
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Data from: Spatial sorting caused by downstream dispersal: Implication for morphological evolution in isolated populations of fat minnow inhabiting small streams flowing through terraced rice paddies
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Data from: Evolution of dispersal, habit, and pollination in Africa pushed Apocynaceae diversification after the Eocene-Oligocene climate transition
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The degree of spatial variation relative to temporal variation influences evolution of dispersal
In the face of ongoing global climate an land use change, organisms have multiple possibilities to cope with the modification of their environment. The two main possibilities are to either adapt locall or disperse to a more suitable habitat. The evolution of both local adaptation and dispersal interacts and can be influenced by the spatial and temporal variation (of e.g. temperature or precipitation). In an individual based model (IBM), we explore evolution of phenotypes in landscapes with varying degree of spatial relative to global temporal variation in order to examine it's influence on the evolution of dispersal, niche optimum and niche width. The relationship between temporal and spatial variation did neither influence the evolution of local adaptation in the niche optimum nor of niche widths. Dispersal probability is highly influenced by the spatio-temporal relationship: with increasing spatial variation, dispersal probability decreases. Additionally, the shape of the distribution of the trait values over patch attributes switches from hump- to U-shaped. At low spatial variance more individuals emigrate from average habitats, at high spatial variance more from extreme habitats. The comparatively high dispersal probability in extreme patches of landscapes with a high spatial variation can be explained by evolutionary succession of two kinds of adaptive response. Early in the simulations, extreme patches in landscapes with a high spatial variability act as sink habitats, where population persistence depends on highly dispersive individuals with a wide niche. With ongoing evolution, local adaptation of the remaining individuals takes over, but simultaneously a possible bet-hedging strategy promotes higher dispersal probabilities in those habitats. Here, in generations that experience extreme shifts from the temporal mean of the patch attribute, the expected fitness becomes higher for dispersing individuals than for philopatric individuals. This means under certain circumstances, both local adaptation and high dispersal probability can be selected for.
The combined role of dispersal and niche evolution in the diversification of Neotropical lizards
<p>Ecological requirements and environmental conditions can influence diversification across temporal and spatial scales. Understanding the role of ecological niche evolution under phylogenetic contexts provides insights on speciation mechanisms and possible responses to future climatic change. Large-scale phyloclimatic studies on the megadiverse Neotropics, where biomes with contrasting vegetation types occur in narrow contact, are rare. We integrate ecological and biogeographic data with phylogenetic comparative methods, to investigate the relative roles of biogeographic events and niche divergence and conservatism on the diversification of the lizard genus <i>Kentropyx</i> Spix, 1825 (Squamata: Teiidae), distributed in South American rainforests and savannas. Using five molecular markers, we estimated a dated species tree, which recovered three clades coincident with previously proposed species groups diverging during the mid-Miocene. Biogeography reconstruction indicates a role of successive dispersal events from an ancestral range in the Brazilian Shield and western Amazonia. Ancestral reconstruction of climatic tolerances and niche overlap metrics indicate a trend of conservatism during the diversification of groups from the Amazon Basin and Guiana Shield, and a strong signal of niche divergence in the Brazilian Shield savannas. Our results suggest that climatic-driven divergence at dynamic forest-savanna borders might have resulted in adaptation to new environmental niches, promoting habitat shifts and shaping speciation patterns of Neotropical lizards. Dispersal and ecological divergence could have a more important role in Neotropical diversification than previously thought.</p>
Infrequent oceanic long-range dispersal and evolution of a top terrestrial arthropod predator in the sub-Antarctic
<p>The UNESCO world heritage sub-Antarctic terrestrial ecosystems are unique. They have been isolated for over 30 million years by constant circum-polar currents and winds, and shaped by climatic cycles that surpass the tolerance limits of many species. Despite this recognition, surprisingly little is known about how these ecosystems acquired their native terrestrial fauna and how it changed over deep time scales. Here the patterns and timing of colonization and speciation in the largest and dominant arthropod predators in the Eastern sub-Antarctic – spiders of the genus Myro – are demonstrated for the first time. Our results indicate that this lineage originated from Australia before the Plio-Pleistocenic glacial cycles and underwent an adaptive radiation on the Crozet archipelago. We discuss the gain and loss of pre-adaptations acting as filter that enabled only one of four Myro species native to the Crozet islands to repeatedly disperse via the Antarctic circum-polar current, resulting in an outstanding distribution range over 9000 kilometres. The results highlight the outstanding role of the volcanic Crozet archipelago for the evolution of arthropod life in the sub-Antarctic, and the potential of terrestrial macro-invertebrates to achieve rare but ecologically influential trans-oceanic dispersal events over thousands of kilometres under hostile conditions.</p>
Microsatellite genotype data from: Male-biased dispersal in a fungus-gardening ant symbiosis (Matthews et al, Ecology and Evolution)
<p>For nearly all organisms, dispersal is a fundamental life history trait that can shape their ecology and evolution. Variation in dispersal capabilities within a species exists and can influence population genetic structure and ecological interactions. In fungus-gardening (attine) ants, co-dispersal of ants and mutualistic fungi is crucial to the success of this obligate symbiosis. Female-biased dispersal (and gene flow) may be favored in attines because virgin queens carry the responsibility of dispersing the fungi, but a paucity of research has made this conclusion difficult. Here, we investigate dispersal of the fungus-gardening ant <i>Trachymyrmex septentrionalis</i> using a combination of maternally- (mitochondrial DNA) and biparentally-inherited (microsatellites) markers. We found three distinct, spatially isolated mitochondrial DNA haplotypes; two were found in the Florida panhandle and the other in the Florida peninsula. In contrast, biparental markers illustrated significant gene flow across this region and minimal spatial structure. The differential patterns uncovered from mitochondrial DNA and microsatellite markers suggest that most long-distance ant dispersal is male-biased and that females (and concomitantly the fungus) have more limited dispersal capabilities. Consequently, the limited female dispersal is likely an important bottleneck for the fungal symbiont. This bottleneck could slow fungal genetic diversification, which has significant implications for both ant hosts and fungal symbionts regarding population genetics, species distributions, adaptive responses to environmental change, and coevolutionary patterns.</p>
FIGURE 4 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 4. Dental ratio of P4 of Ailuropodini. Abbreviations: L, length; W, width, in mm.
FIGURE 1 in A late Turolian giant panda from Bulgaria and the early evolution and dispersal of the panda lineage
FIGURE 1. Location of Ognyanovo in Bulgaria.
Scaling the high latitudes: evolution, diversification, and dispersal of Coryphella nudibranchs across the Northern Hemisphere
<p>Supplementary material for the paper </p> <p>Irina A. Ekimova, Dimitry M. Schepetov, Brenna Green, Maria V. Stanovova, Tatiana I. Antokhina, Terrence Gosliner, Manuel Antonio E. Malaquias, Ángel Valdés,<br>Scaling the high latitudes: evolution, diversification, and dispersal of Coryphella nudibranchs across the Northern Hemisphere,<br>Molecular Phylogenetics and Evolution, 2024, 108214,https://doi.org/10.1016/j.ympev.2024.108214</p> <p>Table S1. Specimens used in the present study with information on vouchers and GB accession numbers.</p> <p>Table S2. Best-fit models for each gene dataset and fragment length (bp)</p> <p>Table S3. Results of model test in ancestral area reconstruction analysis implemented in RASP</p> <p>Table S4. Distribution and ecological traits of <em>Coryphella</em> species.</p> <p>Table S5. Results of population analyses: pairwise Gst, Dst and Fst for <em>Coryphella verrucosa</em> populations.</p> <p>Table S6. Morphological traits of all currently accepted <em>Coryphella</em> species</p> <p>Data S1. Protocols for DNA extraction, amplification, sequencing</p> <p>Data S2. Unedited ML and BI concatenated trees, alignment without <em>Coryphella verta</em></p> <p>Data S3. Unedited ML and BI concatenated trees, alignment with <em>Coryphella verta</em></p> <p>Figure S1. Molecular phylogenetic hypothesis based on the Maximum Likelihood analysis, concatenated dataset of five markers (COI + 16S + H3 + 28S + 18S), the dataset includes tropical Atlantic <em>Coryphella verta</em>. Species-level clades and outgroups are collapsed to a single branch. Numbers above branches indicate posterior probabilities from Bayesian Inference, numbers below branches – bootstrap support from Maximum Likelihood.</p> <p>Figure S2. Molecular phylogenetic hypothesis based on the Maximum Likelihood analysis, concatenated dataset of four markers (COI + 16S + H3 + 28S). Numbers above branches bootstrap support from Maximum Likelihood.</p> <p>Figure S3. Molecular phylogenetic hypothesis based on the Bayesian Inference, concatenated dataset of four markers (COI + 16S + H3 + 28S). Numbers above branches indicate posterior probabilities from Bayesian Inference.</p> <p>Figure S4. Results of phylogeographic analysis of trans-Arctic <em>C. verrucosa</em> <em>(a)</em>, <em>C. nobilis</em> <em>(b)</em>, <em>C. amabilis / C. gracilis</em> <em>(c)</em>, based on the Coalescent approach from BEAST for the COI dataset using the tentative group-specific divergence rates of 6.1% My−1 for gastropods. Coding of each collection locality is given on the upper left, same localities were tested in the Ancestral area reconstruction analysis (AAR). For respective deep nodes the results of AAR are given, and divergent time estimates are displayed on respective nodes with error bars for node ages of 95% highest posterior density intervals. Colored dots in respective terminals indicate the collection locality for each specimen. Grey-shaded blocks indicate interglacial periods HOL (Holocene, Marine Isotope Stage 1 (M1)): 0-10 Kya, LIG (Last Intergracial, M5): 115-130 Kya, LBI (La Bouchet Interglacial (M7): 190-205 and 230-242 Kya, PI (Purfleet Interglacial, M9): 300-337 Kya, HI (Hoxonian Interglacial, M11): 374-424 Kya, M13 (Marine Isotope stage 13): 474-524 Kya. X-axis shows dating in Kya on A, B and in Mya on C.</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)
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.