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85 results for “evolutionary integration”
Data for: Morphological covariance and onset of foot prehensility as indicators of integrated evolutionary dynamics in the herons (Ardeidae)
<p>The ultimate form an organism attains is based, in part, on the rate and timing of developmental trajectories and on compensatory relationships between morphological traits. For example, there is often an inverse correlation between the relative size of an organism's head and the length of its legs. Avian examples with disproportionately small heads and long legs include ostriches (Struthionidae), flamingos (Phoenicopteridae), cranes (Gruidae), stilts (Recurvirostridae), and storks (Ciconiidae). To determine whether a possible compensatory relationship exists between relative head size and hind-limb length in a typically long-legged family of birds—the Ardeidae—we measured skull dimensions (length, width, and height of cranium, and total skull length, including culmen) and skeletal hind-limb dimensions (femur, tibiotarsus, and tarsometatarsus) of the 12 North American species (north of Mexico) and of 12 additional taxa, including the morphologically divergent Agamia and Cochlearius. Our analyses reveal a negative allometric relationship between head size and leg length. For example, <em>Ardea</em> species exhibit the smallest relative head sizes and the longest legs, while <em>Butorides</em>, <em>Nycticorax</em>, <em>Nyctanassa</em>, and <em>Cochlearius</em> have among the largest heads relative to hind-limb length. Furthermore, both positive and negative allometries occur in paired comparisons between the three hind-limb bones, resulting in tall morphotypes having disproportionately short femurs while small morphotypes exhibit long femurs; this relationship has implications for foraging behavior. Moreover, long legs of <em>Ardea</em> apparently derive from an extended growth period, or hypermorphosis, while relatively short legs of <em>Butorides</em> result from growth truncation. The latter are thus morphologically paedomorphic features that, paradoxically, permit a functional precociality of the hind limbs: early onset of prehensile ability of the feet for grasping branches, which nestlings retain into adulthood, later expressed in foraging mode. This developmentally accelerated prehensile function in small species may be attributed, in part, to selection for predator avoidance in the early nestling stage.</p>
The cichlid pharyngeal jaw novelty enhances evolutionary integration in the feeding apparatus
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An integrative phylogenomic approach illuminates the evolutionary history of Old World tree frogs (Anura: Rhacophoridae)
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Evolutionary modularity, integration and disparity in an accretionary skeleton: Analysis of venerid Bivalvia
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Data from: Phylogenomic approach to integrative taxonomy resolves a century-old taxonomic puzzle and the evolutionary history of the Acromyrmex octospinosus species complex
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Data from: Exceptional fossils from Peru and an integrative phylogeny reconcile the evolutionary timing and mode of Gavialis and its kin
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Unraveling the evolutionary history of the snakefly family Inocelliidae (Insecta: Raphidioptera) through integrative phylogenetics
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Global integration of phylogenomic data and fine-scale partitioning strategies refine the evolutionary tree of Adephaga beetles (Insecta: Coleoptera)
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Data from: Morphological integration during postnatal ontogeny: Implications for evolutionary biology
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Data for: Morphological covariance and onset of foot prehensility as indicators of integrated evolutionary dynamics in the herons (Ardeidae)
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Data from: Integrative taxonomy recognizes evolutionary units despite widespread mitonuclear discordance: evidence from a rotifer cryptic species complex
Mitonuclear discordance across taxa is increasingly recognized as posing a major challenge to species delimitation based on DNA sequence data. Integrative taxonomy has been proposed as a promising framework to help address this problem. However, we still lack compelling empirical evidence scrutinizing the efficacy of integrative taxonomy in relation to, for instance, complex introgression scenarios involving many species. Here, we report remarkably widespread mitonuclear discordance between about 15 mitochondrial and four nuclear Brachionus calyciflorus groups identified using different species delimitation approaches. Using coalescent-, Bayesian admixture-, and allele sharing-based methods with DNA sequence or microsatellite data, we provide strong evidence in support of hybridization as a driver of the observed discordance. We then describe our combined molecular, morphological, and ecological approaches to resolving phylogenetic conflict and inferring species boundaries. Species delimitations based on the ITS1 and 28S nuclear DNA markers proved a more reliable predictor of morphological variation than delimitations using the mitochondrial COI gene. A short-term competition experiment further revealed systematic differences in the competitive ability between two of the nuclear-delimited species under six different growth conditions, independent of COI delimitations; hybrids were also observed. In light of these findings, we discuss the failure of the COI marker to estimate morphological stasis and morphological plasticity in the B. calyciflorus complex. By using B. calyciflorus as a representative case, we demonstrate the potential of integrative taxonomy to guide species delimitation in the presence of mitonuclear phylogenetic conflicts.
Data from: Towards robust evolutionary inference with integral projection models
Integral projection models (IPMs) are extremely flexible tools for ecological and evolutionary inference. IPMs track the distribution of phenotype in populations through time, using functions describing phenotype-dependent development, inheritance, survival and fecundity. For evolutionary inference, two important features of any model are the ability to (i) characterize relationships among traits (including values of the same traits across ages) within individuals, and (ii) characterize similarity between individuals and their descendants. In IPM analyses, the former depends on regressions of observed trait values at each age on values at the previous age (development functions), and the latter on regressions of offspring values at birth on parent values as adults (inheritance functions). We show analytically that development functions, characterized this way, will typically underestimate covariances of trait values across ages, due to compounding of regression to the mean across projection steps. Similarly, we show that inheritance, characterized this way, is inconsistent with a modern understanding of inheritance, and underestimates the degree to which relatives are phenotypically similar. Additionally, we show that the use of a constant biometric inheritance function, particularly with a constant intercept, is incompatible with evolution. Consequently, current implementations of IPMs will predict little or no phenotypic evolution, purely as artefacts of their construction. We present alternative approaches to constructing development and inheritance functions, based on a quantitative genetic approach, and show analytically and through an empirical example on a population of bighorn sheep how they can potentially recover patterns that are critical to evolutionary inference.
Enhancing Change Impact Prediction by Integrating Evolutionary Coupling with Software Change Relationships
<div> <div><strong>Replication Package For Paper: Enhancing Change Impact Prediction by Integrating Evolutionary Coupling with Software Change Relationships</strong></div> <br> <div>IMPER is a change <strong>IM</strong>pact <strong>P</strong>rediction method that integrates <strong>E</strong>volutionary coupling with software change <strong>R</strong>elationships. The approach consists of following four main steps:</div> <br> <div><em>Step 1</em>: Relevant Transaction Filtering. Filtering the relevant transaction set based on the given query $<em>Q</em>$.</div> <div><em>Step 2</em>: Association Rule Generation. Generating association rules and obtaining the impact candidate set.</div> <div><em>Step 3</em>: Spatial-Temporal Window Processing. Considering the temporal and spatial change relationships to obtain the impact candidate set.</div> <div><em>Step 4</em>: Candidates Integrating and Ranking. Making a union of these two sets to find the final impact set.</div> <br> <div>The repo provides files for the paper replication. It includes::</div> </div> <div> </div> <div><strong>git_repo.zi</strong>p: Git repository used in the study.</div> <div><em><strong>***-rec-database-1107.tar.gz</strong>:</em> Neo4j dataset containing entity-level software relationship graphs and change information (changed classes, member member methods, member member variables, and files) from over 19,003 versions of six well-maintained projects.</div> <div><strong><em>code_entiy_genealogy</em></strong>: Data for code entity genealogy.<br> <div><em><strong>imper_jar.zip</strong>:</em> Tool for the study, including: 1) Generating qualified queries; 2) Change prediction using four approaches (ROSE, TARMAQ, IMPER, IMPER-ST); 3) Evaluation. The tool outputs evaluation results for each query and average metrics (MAP, Precision, Recall, and F1-score).</div> <div><strong><em>evaluation_metrics_details.zip</em></strong>: Detailed evaluation metric results for different projects.</div> <div><strong><em>Imper_evaluation_results.xlsx</em></strong>: Summary of evaluation metric results for all projects.</div> <div> </div> <br> <div>Users are suggested to refer to the research paper for more detials.</div> <br> <div>This project is still in an early stage of development, and we are improving the implementation and documentation. Please feel free to contact ******(author) for the replication package.</div> <br><strong>Environment</strong><br> <div>- java 11+</div> <div>- <a href="https://neo4j.com/download-center/#community">neo4j 4.2</a> </div> <div>- memory 64G+</div> <br><strong>Quick Start</strong>:<br>To begin our study, follow these steps. Note that only one project can be analyzed at a time.</div> <div><br><strong><em>Step 1: Database Setup</em></strong></div> <div> </div> <div>Copy the relevant database to the folder `data` (in the root path of the Neo4j database), copy the plugins to the plugin folder, and open the database using Neo4j 4.2 (Recommended).</div> <div><br><strong><em>Step 2: Configure application-dev.yml</em></strong></div> <div> </div> <div>Adjust the application-dev.yml file in the folder `imper_jar` to match your configuration. If you're using an existing database, simply configure the database address, username, and password. <div> <p> </p> </div> </div> <div><strong><em>Step 3: Run imper-study.jar</em></strong></div> <div><br>Command: `<em>java -jar imper-study.jar -imp -config ./application-dev.yml -rd /home/user/code_rec -pj commons-io -fi commons-io_file(Map)_1031.txt -mi commons-io_functionInfo(Map).txt -tw 35 -mc 20 -od /home/user/code_rec</em>`.</div> <div><br> <div>-imp: Used to run IMPER</div> <div>-config: Path of `<em>application-dev.yml</em>`.</div> <div>-rd: Root path of code entiy genealogy, e.g., `<em>/home/user/code_rec</em>`.</div> <div>-pj: Project name, e.g., `<em>commons-io</em>`.</div> <div>-fi: the code entiy genealogy (file), e.g., `<em>commons-io_file(Map)_1031.txt</em>` (the absolute path is `<em>/home/user/code_rec/commons-io/commons-io_file(Map)_1031.txt</em>`).</div> <div>-mi: the code entiy genealogy (method), e.g., `<em>commons-io_functionInfo(Map).txt</em>` (the absolute path is `<em>/home/user/code_rec/commons-io/commons-io_functionInfo(Map).txt</em>`).</div> <div>-tw: Time window (half), e.g., <em>-tw 35 (the time window size is 70).</em></div> <div>-mc: Maxium commit size in the time window.</div> <div>-od: Output root path for evaluation results (MAP, Precison, Recall and F1-score), e.g., `<em>/home/user/code_rec</em>`.</div> </div>
Figure 26 in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 26. Photos in life of L. cf. gutturalis from (A) Jinka, South West Region, (B) Dolo Mena, Oromia Region, and (C–D) Debre Markos, Amhara Region, Ethiopia, and Lygodactylus sp. from (E–F) Maasai Mara, Rift Valley Province, Kenya and (G–H) Dodoma, Dodoma Region, Tanzania. Photos by Tim Spawls (A–B), Tomáš Mazúch (C–D), and Steve Spawls (E–H).
Figure 25. A in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 25. A, Dorsal and ventral views of head, showing gular ornamentation and pholidosis variation in L. gamblei sp. nov. B, Specimens of L. gamblei sp. nov. in lateral view, showing its characteristic scapular pattern. Red points denote males and blue points denote females. Photos by J.L.R.
Figure 24 in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 24. Holotype of L. gamblei sp. nov. (UTEP 22587) from Manono, Tanganyika Province, DRC. A, Dorsal and ventral view of body. B, Details of the cloacal region. C, Detailed view of head in ventral, dorsal, and lateral views (from top to bottom). Photos by J.L.R.
Figure 23. A–B in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 23. A–B, Holotype (UTEP 22577) and (C–D) paratype (UTEP 22596) of L. leopardinus sp. nov. in life and photo of habitat from (E) type locality at Balolombo Village, Busira River, Équateur Province, DRC. F–G, Holotype (UTEP 22587) and (H–I) paratype (UTEP 22584) of L. gamblei sp. nov. in life and photo of habitat from (J) type locality at Manono, Tanganyika Province, DRC. Photographs by E.G.
Figure 22 in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 22. Holotype of L. leopardinus sp. nov. (UTEP 22577) from Balolombo Village, Busira River, Équateur Province, DRC. A, Dorsal and ventral view of body. B, Details of right manus and (C) pes. D, Detailed view of head in ventral, dorsal, and lateral views (from top to bottom). Photos by J.L.R.
Figure 21 in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 21. Holotype of L. mirabundus sp. nov. (UTEP 22585) from Katako Kombe, Sankuru Province, DRC. A, Dorsal and ventral view of body. B, Details of cloacal region and (C) right pes. D, Detailed view of head in dorsal, ventral, and lateral views (from top to bottom). Photos by J.L.R.
Figure 19 in Integrative revision of the Lygodactylus gutturalis (Bocage, 1873) complex unveils extensive cryptic diversity and traces its evolutionary history
Figure 19. Holotype of L. karamoja sp. nov. (UTEP 22590) from Agoro Town, Imatong Foothills, Northern Region, Uganda. A, Dorsal and ventral view of body, (B) details of cloacal section, (C) regenerated tail tip, and (D) left pes. E, Detailed view of head in dorsal, ventral, and lateral views (from top to bottom). Photos by J.L.R.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.