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83 results for “Landscape Evolution”
Neogene–Quaternary uplift and landscape evolution in northern Greenland recorded by subglacial valley morphology: Datasets
<p>This dataset contains a csv file of subglacial valley morphology derived from radio-echo sounding datasets in northern Greenland, and an ESRI shapefile of the interpreted channel network. For further documentation of the data please view the README.txt file.</p> <p>RADAR-DERIVED VALLEY MORPHOLOGY</p> <ul> <li><strong>northern_Greenland_valley_morphology.csv</strong>: location and morphology of subglacial valleys in northern Greenland, as imaged by airborne radio-echo sounding datasets.</li> </ul> <p>SUBGLACIAL VALLEY NETWORK</p> <ul> <li><strong>northern_Greenland_valley_network.shp (and ancillary files: .cpg, .dbf, .prj, .qpj, .shx)</strong>: ESRI shapefile of the interpreted valley network in the northern Greenland subglacial drainage catchment.</li> </ul>
Range expansion can promote the evolution of plastic generalism in coarse-grained landscapes
<p>Phenotypic plasticity is one way for organisms to deal with variable environments through generalism. However, plasticity is not found universally and its evolution may be constrained by costs and other limitations such as complexity: the need for multiple mutational steps before the adaptation is realized. Theory predicts that greater experienced heterogeneity, such as organisms may encounter when spatial heterogeneity is fine-grained relative to dispersal, should favor the evolution of a broader niche. Here we tested this prediction via simulation. We found that, contrary to classical predictions, coarse-grained landscapes can be the most favorable for the evolution of plasticity, but only when populations encountered those landscapes through range expansion. During these range expansions, coarse-grained landscapes select for each step in the complex mutational pathway to plastic generalism by blocking the dispersal of specialists. These circumstances provide ecological opportunities for innovative mutations that change the niche. Our results indicate a new mechanism by which range expansion and spatially structured landscapes interact to shape evolution, and reveal that the environments in which a complex adaptation has the highest fitness may not be the most favorable for its evolution.</p>
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>
Evolution of the correlated genomic variation landscape across a divergence continuum in the genus Castanopsis
<p>The heterogeneous landscape of genomic variation has been well documented in population genomic studies. However, disentangling the intricate interplay of evolutionary forces influencing the genetic variation landscape over time remains challenging. In this study, we assembled a chromosome-level genome for <em>Castanopsis eyrei</em> and sequenced the whole genomes of 276 individuals from 12 <em>Castanopsis</em> species, spanning a broad divergence continuum. We found highly correlated genomic variation landscapes across these species. Furthermore, variations in genetic diversity and differentiation along the genome were strongly associated with recombination rates and gene density. These results suggest that long-term linked selection and conserved genomic features have contributed to the formation of a common genomic variation landscape. By examining how correlations between population summary statistics change throughout the species divergence continuum, we determined that background selection alone does not fully explain the observed patterns of genomic variation; the effects of recurrent selective sweeps must be considered. We further revealed that extensive gene flow has significantly influenced patterns of genomic variation in <em>Castanopsis</em> species. The estimated admixture proportion correlated positively with recombination rate and negatively with gene density, supporting a scenario of selection against gene flow. Additionally, putative introgression regions exhibited strong signals of positive selection, an enrichment of functional genes, and reduced genetic burdens, indicating that adaptive introgression has played a role in shaping the genomes of hybridizing species. This study provides insights into how different evolutionary forces have interacted in driving the evolution of the genomic variation landscape.</p>
Data for: Co-evolution of dormancy and dispersal in spatially autocorrelated landscapes
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Evolution of the correlated genomic variation landscape across a divergence continuum in the genus Castanopsis
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Range expansion can promote the evolution of plastic generalism in coarse-grained landscapes
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Habitat transitions alter the adaptive landscape and shape phenotypic evolution in needlefishes (Belonidae)
<p class="Normal1">Habitat occupancy can have a profound influence on macroevolutionary dynamics, and a switch in major habitat type may alter the evolutionary trajectory of a lineage. In this study we investigate how evolutionary transitions between marine and freshwater habitats affect macroevolutionary adaptive landscapes, using needlefishes (Belonidae) as a model system. We examined the evolution of body shape and size in marine and freshwater needlefishes and tested for phenotypic change in response to transitions between habitats. Using micro-computed tomographic (µCT) scanning and geometric morphometrics, we quantified body shape, size, and vertebral counts of 31 belonid species. We then examined the pattern and tempo of body shape and size evolution using phylogenetic comparative methods. Our results show that transitions from marine to freshwater habitats have altered the adaptive landscape for needlefishes and expanded morphospace relative to marine taxa. We provide further evidence that freshwater taxa attain reduced sizes either through dwarfism (as inferred from axial skeletal reduction) or developmental truncation (as inferred from axial skeletal loss). We propose that transitions to freshwater habitats produce morphological novelty in response to novel prey resources and changes in locomotor demands. We find that repeated invasions of different habitats have prompted predictable changes in morphology.</p>
Model inputs and results from FastScape landscape evolution model runs for southern Africa
<p>These are the input files and results for the models presented in the revised version of the paper "Constraining plateau uplift in southern Africa by combining thermochronology, sediment flux, topography, and landscape evolution modeling" submitted to JGR:Solid Earth in October 2020 and revised in May 2017. The corresponding code needed to run the inputs can be found here: http://doi.org/10.5281/zenodo.4150333. The readme.txt file contained here explains the included data and results, as well as simple instructions for how to run the models.</p>
Data and code for the GECCO 2024 paper: "Understanding fitness landscapes in morpho-evolution via local optima networks"
<p>The LON and algorithm run data is available in data/ </p> <p>To run the LON extraction:</p> <p>From gymrem2d-lons/ModularER_2D, run python3 setup.py</p> <p>Direct encoding: python3 lons.py --file direct.cfg</p> <p>LSystem: python3 lons.py --file lsystem.cfg </p> <p>CPPN: python3 lons.py --file cppn.cfg</p> <p> </p>
Data from "Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family."
<p>This data accompanies the paper entitled Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family.</p> <p>The zip archive contains: </p> <p>1- Starting configurations of the proteins after equilibration in PDB format and trajectories of unrestrained molecular dynamics simulations with the positions of the proteins every 100 ps in XTC gromacs format are provided for all systems. </p> <p>2- The free energy profiles and histograms are provided for all umbrella sampling simulations and the scripts used to run it with gromacs.</p>
Data from: Landscape evolution drives continental diversification in Neotropical freshwater fishes of the family Erythrinidae (Teleostei, Characiformes)
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Habitat transitions alter the adaptive landscape and shape phenotypic evolution in needlefishes (Belonidae)
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Data from: Urban landscapes can change virus gene flow and evolution in a fragmentation-sensitive carnivore
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Data for: Rapid evolution of recombination landscapes during the divergence of cichlid ecotypes in Lake Masoko
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Data from: Evolution across the adaptive landscape in a hyperdiverse beetle radiation
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Data from: Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes)
Morphological, lineage and ecological diversity can vary substantially even among closely related lineages. Factors that influence morphological diversification, especially in functionally relevant traits, can help to explain the modern distribution of disparity across phylogenies and communities. Multivariate axes of feeding functional morphology from 75 species of Neotropical cichlid and a stepwise-AIC algorithm were used to estimate the adaptive landscape of functional morphospace in Cichlinae. Adaptive landscape complexity and convergence, as well as the functional diversity of Cichlinae, were compared with expectations under null evolutionary models. Neotropical cichlid feeding function varied primarily between traits associated with ram feeding vs. suction feeding/biting and secondarily with oral jaw muscle size and pharyngeal crushing capacity. The number of changes in selective regimes and the amount of convergence between lineages was higher than expected under a null model of evolution, but convergence was not higher than expected under a similarly complex adaptive landscape. Functional disparity was compatible with an adaptive landscape model, whereas the distribution of evolutionary change through morphospace corresponded with a process of evolution towards a single adaptive peak. The continentally distributed Neotropical cichlids have evolved relatively rapidly towards a number of adaptive peaks in functional trait space. Selection in Cichlinae functional morphospace is more complex than expected under null evolutionary models. The complexity of selective constraints in feeding morphology has likely been a significant contributor to the diversity of feeding ecology in this clade.
Data from: Adaptive evolution and segregating load contribute to the genomic landscape of divergence in two tree species connected by episodic gene flow
Speciation often involves repeated episodes of genetic contact between divergent populations before reproductive isolation (RI) is complete. Whole-genome sequencing (WGS) holds great promise for unravelling the genomic bases of speciation. We have studied two ecologically divergent, hybridizing species of the 'model tree' genus Populus (poplars, aspens, cottonwoods), Populus alba and P. tremula, using >8.6 million single nucleotide polymorphisms (SNPs) from WGS of population pools. We used the genomic data to (i) scan these species' genomes for regions of elevated and reduced divergence, (ii) assess key aspects of their joint demographic history based on genomewide site frequency spectra (SFS) and (iii) infer the potential roles of adaptive and deleterious coding mutations in shaping the genomic landscape of divergence. We identified numerous small, unevenly distributed genome regions without fixed polymorphisms despite high overall genomic differentiation. The joint SFS was best explained by ancient and repeated gene flow and allowed pinpointing candidate interspecific migrant tracts. The direction of selection (DoS) differed between genes in putative migrant tracts and the remainder of the genome, thus indicating the potential roles of adaptive divergence and segregating deleterious mutations on the evolution and breakdown of RI. Genes affected by positive selection during divergence were enriched for several functionally interesting groups, including well-known candidate 'speciation genes' involved in plant innate immunity. Our results suggest that adaptive divergence affects RI in these hybridizing species mainly through intrinsic and demographic processes. Integrating genomic with molecular data holds great promise for revealing the effects of particular genetic pathways on speciation.
Data from: Ecological opportunity and the evolution of habitat preferences in an arid-zone bird: implications for speciation in a climate-modified landscape
Bioclimatic models are widely used to investigate the impacts of climate change on species distributions. Range shifts are expected to occur as species track their current climate niche yet the potential for exploitation of new ecological opportunities that may arise as ecosystems and communities remodel is rarely considered. Here we show that grasswrens of the Amytornis textilis-modestus complex responded to new ecological opportunities in Australia's arid biome through shifts in habitat preference following the development of chenopod shrublands during the late Plio-Pleistocene. We find evidence of spatially explicit responses to climatically driven landscape changes including changes in niche width and patterns of population growth. Conservation of structural and functional aspects of the ancestral niche appear to have facilitated recent habitat shifts, while demographic responses to late Pleistocene climate change provide evidence for the greater resilience of populations inhabiting the recently evolved chenopod shrubland communities. Similar responses could occur under future climate change in species exposed to novel ecological conditions, or those already occupying spatially heterogeneous landscapes. Mechanistic models that consider structural and functional aspects of the niche along with regional hydro-dynamics may be better predictors of future climate responses in Australia's arid biome than bioclimatic models alone.
Evaluation of Machine Learning-Assisted Directed Evolution Across Diverse Combinatorial Landscapes
<p>Refer to the <a href="https://github.com/fhalab/SSMuLA">SSMuLA Github repository</a> for the associated code</p> <p>See our <a href="https://doi.org/10.1101/2024.10.24.619774">paper</a> titled "Evaluation of Machine Learning-Assisted Directed Evolution Across Diverse Combinatorial Landscapes"</p> <p> </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.