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opencc-zeroNov 2023View details →

Data for: The pace of mitochondrial molecular evolution varies with seasonal migration distance

This repository contains data associated with "The pace of mitochondrial molecular evolution varies with seasonal migration distance." This study demonstrates relationships between traits (migration distance, mass, population genetic parameters representing genetic diversity) and molecular evolutionary rates (dS and dN/dS). The main conclusions are based on models from the program Coevol. The files included here are input files necessary to run models with Coevol, as well as selected Coevol output files used for figure generation associated with the manuscript. We also include a copy of a GitHub repository of manuscript code. Other necessary data for replicating analyses in the manuscript are included in the manuscript supplement.

publicFeb 2024View details →

Data from: Recovery from infection is more likely to favor the evolution of migration than social escape from infection

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publicAug 2025View details →

Joint evolution of the biogeography and phenology of seasonal migration

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publicOct 2025View details →

Code from: Evolution of phenotypic plasticity owing to migration

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publicNov 2023View details →

Data for: The pace of mitochondrial molecular evolution varies with seasonal migration distance

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publicDec 2019View details →

The migration pattern of a monogamous shorebird challenges existing hypotheses explaining the evolution of differential migration

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publicNov 2024View details →

Chromosomal evolution, environmental heterogeneity, and migration drive spatial patterns of species richness in Calochortus (Liliaceae)

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publicSep 2025View details →

Evolution of population-specific migration routes in the great reed warbler Acrocephalus arundinaceus: Evidence of a novel spring migration strategy

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opencc-zeroDec 2021View details →

Elevational niche-shift migration: Why the degree of elevational change matters for the ecology, evolution, and physiology of migratory birds to ornithology

Elevational migration can be defined as roundtrip seasonal movement that involves upward and downward shifts in elevation. These shifts incur physiological challenges that are proportional to the degree of elevational change. Larger shifts in elevation correspond to larger shifts in partial pressure of oxygen, air density, temperature, and UV exposure. Although most avian examples of elevational migration involve subtle shifts that would have minimal impacts on physiology, shifts of any magnitude have previously been considered under the broad umbrella of 'elevational migration'. Here, we consider extreme seasonal elevational movements (≥2000 m), sufficient to shift the elevational dimension of the eco-climatic niche. Migratory bird populations typically maintain inter-seasonal stability in the temperature, precipitation, and elevational aspects of their climatic niches, a tendency that likely reflects genetic physiological specialization on environmental conditions such as atmospheric pressure. A shift of ≥2000 m involves a ≥20% change in air density and oxygen partial pressure, sufficient to incur functionally impactful declines in arterial blood-oxygen saturation and require compensatory shifts in respiratory physiology. We refer to this phenomenon as elevational niche-shift migration (ENSM). In this review, we analyzed >4 million occurrence records to identify 105 populations, representing 92 bird species, that undergo complete or partial ENSM. We identified key ecological and evolutionary questions regarding causes and consequences of ENSM. Our synthesis reveals that ENSM has evolved independently in at least 29 avian families spanning 10 orders. Nonetheless, ENSM is rare relative to other forms of seasonal migration, consistent with the general tendency of seasonal niche conservatism by migratory species and evolutionarily conserved elevational range limits. For many migratory species and populations, within-species patterns of migratory connectivity are not sufficiently understood to determine ENSM status. ENSM is distinguished by its scale within the broader phenomenon of elevational migration. Critical examination of ENSM illustrates fundamental constraints on the ecology and evolution of migration systems, topographical influences on geographic patterns of migratory connectivity, and the remarkable metabolic flexibility of certain bird species that allows them to occupy disparate elevations across different seasons.

opencc-zeroDec 2012View details →

Data from: Gene trees, species trees and Earth history combine to shed light on the evolution of migration in a model avian system

The evolution of migration in birds has fascinated biologists for centuries. In this study, we performed phylogenetic-based analyses of Catharus thrushes, a model genus in the study of avian migration, and their close relatives. For these analyses, we used both mitochondrial and nuclear genes, and the resulting phylogenies were used to trace migratory traits and biogeographic patterns. Our results provide the first robust assessment of relationships within Catharus and relatives and indicate that both mitochondrial and autosomal genes contribute to overall support of the phylogeny. Measures of phylogenetic informativeness indicated that mitochondrial genes provided more signal within Catharus than did nuclear genes, whereas nuclear loci provided more signal for relationships between Catharus and close relatives than did mitochondrial genes. Insertion and deletion events also contributed important support across the phylogeny. Across all taxa included in the study, and for Catharus, possession of long-distance migration is reconstructed as the ancestral condition, and a North American (north of Mexico) ancestral area is inferred. Within Catharus, sedentary behaviour evolved after the first speciation event in the genus and is geographically and temporally correlated with Central American distributions and the final closure of the Central American Seaway. Migratory behaviour subsequently evolved twice in Catharus and is geographically and temporally correlated with a recolonization of North America in the late Pleistocene. By temporally linking speciation events with changes in migratory condition and events in Earth history, we are able to show support for several competing hypotheses relating to the geographic origin of migration.

opencc-by-4.0Mar 2024View details →

A Meta-Model to Support the Migration and Evolution of CI/CD Pipelines

<h1>Reproducibility Package for “A Meta-Model for Reengineering CI/CD Pipelines”</h1> <h2>Abstract</h2> In modern industrial software development, DevOps has become the leading approach for managing highly iterative software production processes. DevOps integrates development and operations activities, with Continuous Integration, Continuous Delivery, and Continuous Deployment (CI/CD) playing a crucial role in ensuring the iterative delivery of high-quality software. CI/CD relies on pipelines composed of various automated activities, often implemented using commercial tools. However, due to the rapid evolution of these tools, CI/CD pipelines frequently require migration to newer versions or entirely different platforms. Since this migration process is predominantly manual, it is both time-consuming and error-prone. To assist software engineers in this challenge, we propose a novel Model-Driven Engineering (MDE) approach to automate the migration of CI/CD pipelines. Inspired by the traditional reengineering horseshoe model, our method abstracts existing CI/CD pipeline artifacts into an intermediate meta-model representation. Using this meta-model, we can generate semantically equivalent pipelines for different CI/CD tools. Our main contribution is a meta-model designed to represent the structure of existing CI/CD pipelines, building the foundation for MDE-based migration. <h2>Contents of the Reproducibility Package</h2> This package is provided inside the <code>reproducibility.zip</code> file, organized into the following folders: <h3>1. <code>devops2</code> – CI/CD Meta-Model</h3> <ul> <li>Our CI/CD meta-model, built using the Eclipse Modeling Framework (EMF).</li> <li>Requirements: Eclipse Modeling Framework (EMF).</li> <li>Usage: Import into EMF or any Ecore-compatible library..</li> </ul> <h3>2. <code>org.xtext.example.mydsl11</code> – Xtext-Based GitHub Actions Parser</h3> <ul> <li>An Xtext-based DSL for parsing GitHub Actions configuration files.</li> <li>Used in an initial version of our research; the PyEcore parser (included below) provides better results.</li> <li>Requirements: Eclipse Modeling Framework (EMF) and Xtext.</li> <li>Usage: Import into EMF with Xtext installed.</li> </ul> <h3>3. <code>GitHubActionsDataset</code> – Dataset of GitHub Actions Configurations</h3> <ul> <li>A collection of 200 randomly selected GitHub Actions configuration files used to validate our initial GitHub Actions parser.</li> </ul> <h3>4. <code>org.xtext.example.mydsl13</code> – Xtext-Based CircleCI Parser</h3> <ul> <li>An Xtext-based DSL for parsing CircleCI configuration files.</li> <li>Requirements: Eclipse Modeling Framework (EMF) and Xtext.</li> <li>Usage: Import into EMF with Xtext installed.</li> </ul> <h3>5. <code>org.eclipse.acceleo.module.sample7</code> – Acceleo-Based Code Generator</h3> <ul> <li>An Acceleo-based generator that translates our meta-model into GitHub Actions configurations.</li> <li>Requirements: Eclipse Modeling Framework (EMF) and Acceleo.</li> <li>Usage: Import into EMF with Acceleo installed.</li> </ul> <h3>6. <code>codegeneration</code> – Example Configuration Files</h3> <ul> <li>Example configurations used to validate the syntactical correctness of our models.</li> <li>Requirements: Eclipse Modeling Framework (EMF) and Acceleo.</li> <li>Usage: Import into EMF with Acceleo installed.</li> </ul> <h3>7. <code>modelequivalence</code> – Validation of Model Equivalence</h3> <ul> <li>Contains CircleCI scripts used for validating model equivalence, including: <ul> <li>Their representations in our meta-model.</li> <li>The corresponding GitHub Actions configurations generated from these models.</li> </ul> </li> <li>Requirements: Eclipse Modeling Framework (EMF) or any other Ecore-compatible library.</li> <li>Usage: Import into EMF or any Ecore-compatible library.</li> </ul> <h3>8. <code>casestudy</code> – Migration Case Study (CircleCI → GitHub Actions)</h3> <ul> <li>A case study demonstrating how our meta-model supports migration from CircleCI to GitHub Actions.</li> <li>Requirements: Eclipse Modeling Framework (EMF) and Acceleo.</li> <li>Usage: Import into EMF with Acceleo installed.</li> </ul> <h3>9. <code>pyecoreparser</code> – PyEcore-Based Parser (GitHub Actions & Travis CI)</h3> <ul> <li>A PyEcore-based parser for extracting CI/CD configurations from GitHub Actions and Travis CI, converting them into our meta-model.</li> <li>Includes: <ul> <li>The 200 GitHub Actions and Travis CI configuration files used for validation.</li> <li>The 10 randomly selected GitHub Actions and Travis CI configuration files used for comparison with manual modeling.</li> <li>A README file with installation instructions and usage guidelines.</li> </ul> </li> <li>Requirements: Python, PyEcore library, PyYAML library.</li> <li>Usage: Follow the README file for setup and usage instructions.</li> </ul> <h3>10. <code>Mapping</code> – Platform-to-Meta-Model Mapping</h3> <ul> <li>A mapping that aligns different CI/CD platforms with our meta-model.</li> </ul> <h3>11. <code>automaticmanualvalidation</code> – Automatic vs. Manual Model Validation</h3> <ul> <li>A set of 20 pipelines (10 from GitHub Actions, 10 from Travis CI) modeled in two ways: <ul> <li>Automatically using the PyEcore parser.</li> <li>Manually by the authors for comparison.</li> </ul> </li> <li>Requirements: Eclipse Modeling Framework (EMF) or any other Ecore-compatible library.</li> <li>Usage: Import into EMF or any Ecore-compatible library.</li> </ul>

opencc-by-4.0Oct 2024View details →

Evolution and stability of social learning in animal migration - Figure genation

Code and Data to generate figures in article "Evolution and stability of social learning in animal migration" (n.d.)   Run Article_Figures.m to generate all plots. See README for details.

opennotspecifiedFeb 2022View details →

Figure 3 in Phylogeny, migration and geographic range size evolution of Anax dragonflies (Anisoptera: Aeshnidae)

Figure 3. Maximum likelihood ancestral state reconstruction of migratory behaviour and geographical range of Anax on a Bayesian tree from five gene regions. The fraction of the circle that is shaded indicates the likelihood that the ancestor was migratory.

opennotspecifiedFeb 2022View details →

Figure 2 in Phylogeny, migration and geographic range size evolution of Anax dragonflies (Anisoptera: Aeshnidae)

Figure 2. Bayesian time-calibrated tree of five gene regions with placement of fossil taxa. Clades with dragonflies have at least one migratory taxon. Monophyletic species are condensed to show relationships. Posterior Probabilities> 0.90 not shown. *Outgroups include species from Aeshna, Oplonaeschna, Anaciaeschna and Gynacantha. See the Supporting Information (Table S1) for more details.

opencc-by-4.0Mar 2022View details →

Perylenetetracarboxylic Acid Nanosheets with Internal Electric Fields and Anisotropic Charge Migration for Photocatalytic Hydrogen Evolution

Source data for Perylenetetracarboxylic Acid Nanosheets with Internal Electric Fields and Anisotropic Charge Migration for Photocatalytic Hydrogen Evolution

opencc-zeroMay 2024View details →

Data from: Evolution of leap-frog migration: A test of alternative hypotheses

Leap-frog migration is a common migration pattern in birds where the breeding and wintering latitudes between populations are in reversed latitudinal sequence. Competition for wintering and breeding sites has been suggested to be an ultimate factor and several competitor-based hypotheses have been proposed to explain this pattern. If wintering sites close to the breeding sites are favored, competitive exclusion could force subdominant individuals to winter further away. Competitive exclusion could be mediated either through body size or by prior occupancy. The alternative "spring predictability" hypothesis assumes competition for sufficiently close wintering areas, allowing the birds to use autocorrelated weather cues to optimally time spring migration departure. To test predictions and assumptions of these hypotheses, we combined morphometrics, migration and weather data from four populations of common ringed plover breeding along a latitudinal (56-68°N) and climatic gradient (temperate to Arctic). Critical for our evaluation was that two populations were breeding on the same latitude in subarctic Sweden and had the same distance to the closest potential wintering site, but differ in breeding phenology, and wintered in West Africa and Europe, respectively. Thus, while breeding on the same latitude, their winter distribution overlapped with that of an Arctic and temperate population, respectively. Body size was largest within the temperate population, but there was no size difference between the two subarctic. Populations wintering in Europe arrived there before populations wintering in Africa. The largest variation in arrival of meteorological spring occurred at the temperate breeding site, while there was almost no difference among the other sites. In general, temperatures at the northernmost wintering area correlated well with each breeding site prior to breeding site-specific spring arrival. Based on these observations, we conclude that competitive exclusion through body-size related dominance cannot explain leap-frog migration. Furthermore, the assumptions on which the 'spring predictability' hypothesis is based did not match the observed wintering ranges either. However, we could not reject the hypothesis that competitive exclusion mediated by prior occupancy in the wintering area could lead to leap-frog migration, and therefore this hypothesis should be retained as working hypothesis for further work.

opencc-zeroSep 2021View details →

Evolution of chain migration in an aerial insectivorous bird, the common swift Apus apus

Spectacular long-distance migration has evolved repeatedly in animals enabling exploration of resources separated in time and space. In birds, these patterns are largely driven by seasonality, cost of migration, and asymmetries in competition leading most often to leap-frog migration, where northern breeding populations winter furthest to the south. Here we show that the highly aerial common swift Apus apus, spending the non-breeding period on the wing, instead exhibits a rarely-found chain migration pattern, where the most southern breeding populations in Europe migrate to wintering areas furthest to the south in Africa, while the northern populations winter to the north. The swifts concentrated in three major areas in sub-Saharan Africa during the non-breeding period, with substantial overlap for nearby breeding populations. We found that the southern breeding swifts were larger, raised more young, and arrived to the wintering areas with higher seasonal variation in greenness (Normalized Difference Vegetation Index, NDVI) earlier than the northern breeding swifts. This unusual chain migration pattern in common swifts is largely driven by differential annual timing and we suggest it evolves by prior occupancy and dominance by size in the breeding quarters and by prior occupancy combined with diffuse competition in the winter.