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55 results for “co-evolution”
Fig. 1 in Devonian pearls and ammonoid-endoparasite co-evolution
Fig. 1. Terminology and measurements. For more information on the specimens see Figs. 2 and 5.
Output data: China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts
<p>Outputs for Wang, J., Duan, Y., Wang, C., 2023. China’s energy-water-land system co-evolution under carbon neutrality goal and climate impacts. (In progress)</p> <p>Folder demeter contains the spatially downscaled land use/land cover datasets.<br> Folder tethys contains the spatially downscaled water withdrawal datasets.</p> <p>The sub-folder names correspond to the scenarios described in the paper.</p> <p>For landcover datasets, land type ratios in each grid are presented. Land types include water, forest, shrub, grass, urban, snow, sparse and crops.</p> <p>For water withdrawal datasets, “wd” = “water withdrawal spatially downscaled”, “twd” = “water withdrawal spatially and temporally downscaled”, “dom”=”domestic/municipal sector”, “elec”=”electricity sector”, ”irr”=”irrigation sector”, “liv”=”livestock sector”, “mfg”=”manufacturing/industry sector”, “min”=”mining/primary energy sector”, “nonag”=”non-agricultural sector”, “total”=”all sectors”.<br> </p>
Data from: Evolution and co-evolution of the suck behaviour, a postcopulatory female resistance trait that manipulates received ejaculate
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Co-evolution of cleaning and feeding morphology in the western Atlantic and eastern Pacific gobies
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Data from: Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants
Mutualisms may be "key innovations" that spur lineage diversification by augmenting niche breadth, geographic range, or population size, thereby increasing speciation rates or decreasing extinction rates. Whether mutualism accelerates diversification in both interacting lineages is an open question. Research suggests that plants that attract ant mutualists have higher diversification rates than non-ant associated lineages. We ask whether the reciprocal is true: does the interaction between ants and plants also accelerate diversification in ants, i.e. do ants and plants cooperate-and-radiate? We used a novel text-mining approach to determine which ant species associate with plants in defensive or seed dispersal mutualisms. We investigated patterns of lineage diversification across a recent ant phylogeny using BiSSE, BAMM, and HiSSE models. Ants that associate mutualistically with plants had elevated diversification rates compared to non-mutualistic ants in the BiSSE model, with a similar trend in BAMM, suggesting ants and plants cooperate-and-radiate. However, the best-fitting model was a HiSSE model with a hidden state, meaning that diversification models that do no account for unmeasured traits are inappropriate to assess the relationship between mutualism and ant diversification. Against a backdrop of diversification rate heterogeneity, the best-fitting HiSSE model found that mutualism actually decreases diversification: mutualism evolved much more frequently in rapidly diversifying ant lineages, but then subsequently slowed diversification. Thus, it appears that ant lineages first radiated, then cooperated with plants.
Positive/negative co-evolution samples with manual inspection results
<p><a href="https://zenodo.org/api/files/40580848-f439-4792-bb80-4681cabe81dd/dubbo_coevo_patches.txt">dubbo_coevo_patches.txt </a><br> Co-evolution patches in Duboo.<br> <br> <a href="https://zenodo.org/api/files/40580848-f439-4792-bb80-4681cabe81dd/kafka_coevo_patches.txt">kafka_coevo_patches.txt </a><br> Co-evolution patches in Kafka.</p> <p><a href="https://zenodo.org/api/files/74c28761-3ac1-4ee6-9782-b83ac008c098/negative-findings.xlsx">negative-findings.xlsx </a><br> Inspecting results of negative samples<br> <br> <a href="https://zenodo.org/api/files/74c28761-3ac1-4ee6-9782-b83ac008c098/negative.zip">negative.zip </a><br> Negative sample patches (not co-evolved in 20 days)<br> <br> <a href="https://zenodo.org/api/files/74c28761-3ac1-4ee6-9782-b83ac008c098/positive-findings.xlsx">positive-findings.xlsx </a><br> Inspecting results of positive samples<br> <br> <a href="https://zenodo.org/api/files/74c28761-3ac1-4ee6-9782-b83ac008c098/positive.zip">positive.zip </a><br> Positive sample patches (co-evolved in 2 days)</p> <p> </p> <p><strong>NOTE</strong><br> The item order in _coevo_patches.txt is: proj type prod_sha1 test_sha1 prod_path test_path.<br> The excel data is sorted in "natural sorting" algorithm, the default sorting algorithm in Windows file explorer.<br> It is recommended to use VS Code to browse the patch files.</p>
Phage-host co-evolution has led to distinct generalized transduction strategies
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Continuous presence of proto-cereals in Anatolia since 2.3 Ma, and their possible co-evolution with large herbivores and hominins
<p>pollen data from the published paper in Scientific Reports: https://www.nature.com/articles/s41598-021-86423-8</p>
ICSME 2024 Research Track: "What Happened to my Models?" History-Aware Co-Existence and Co-Evolution of Metamodels and Models
<p> </p> <h1>ICSME 2024 Research Track: “What Happened to my Models?” History-Aware Co-Existence and Co-Evolution of Metamodels and Models</h1> <p> </p> <p>This repository provides the dataset and results for the evaluation of the paper “What Happened to my Models?” of the ICSME 2024 Research track.<br>The dataset consists of the following files:</p> <ul> <li><strong>RQ1-Type-Refactors.zip </strong>contains the operations and refactoring performed on each of the given metamodels used by our approach in RQ1.</li> <li><strong>RQ1-Type-Results.zip</strong>: contains the group results of RQ1 as shown in our paper with additional metrics of other operations not highlighted in our paper due to space limitations.</li> <li><strong>RQ2-3-PlantUML-Models.zip</strong>: contains the 250 PlantUML models and the metamodel. This folder contains the co-evolved PlantUML models, the operations performed during the co-evolution, their metrics and the state of the models bore and after the co-evolution. </li> <li><strong>RQ2-3-PlantUML-Results.zip:</strong> contains the group results of RQ2 and RQ3 as shown in our paper with additional metrics of other operations not highlighted in our paper due to space limitations</li> <li><strong>RQ2-3-FHIR-Models.zip</strong>: contains the 1180 FHIR models and the metamodel. This folder contains the co-evolved FHIR models, the operations performed during the co-evolution, their metrics and the state of the models bore and after the co-evolution.</li> <li><strong>RQ2-3-Results.zip:</strong> contains the grouped results of RQ2 and RQ3 as presented in our paper.</li> <li><strong>Additionalnformation.pdf:</strong> contains additional information on how to read the files extracted by our approach, i.e., how to read the models and operations and how our executable refactoring catlaog works since we only focused on Property Refactorings in the paper.</li> <li><strong>Results.pdf</strong>: Contains an overview of the results (the results from our paper + additional results)</li> <li><strong>Tools.zip: </strong>Contains the tools used for the evalution. For an explaination how to use it read the <strong>Additionalnformation.pdf, </strong>see below<strong> </strong>or contact the authors</li> </ul> <p><strong>Running the tools:</strong></p> <p><em>Windows 10/11<br></em><em>JDK 20 or above</em></p> <p>The tools consist of two programs: </p> <ul> <li><strong>importer.jar<br></strong>This file is used to import a FHIR or PlantUML file into the server and co-evolve it.</li> <li><strong>server_FHIR_.jar<br></strong>The server stores the models and co-evolves them. The files provided already have the metamodels preloaded, that are used in RQ2 and RQ3, i.e., FHIR_STU3 contains the FHIR metamodel version DSTU2 and STU3 and our hybrid PlantUML, while FHIR_ synthetic contains the FHIR metamodel DSTU2 and our synthetically created one.</li> </ul> <p><strong>How to use the Tools</strong></p> <p>First, start the server by starting the jar. The server also has an experimental GUI mode that allows engineers to check the types and instances that were created. <em><strong>Note: </strong>This mode is currently under development and is still unstable. The mode <em>is accessible</em> by adding -gui as a parameter.</em></p> <p><em>java -jar server_FHIR_STU3.jar -gui</em></p> <p>Otherwise, just run the server normally:</p> <p><em>java -jar server_FHIR_STU3.jar</em></p> <p>After the server has booted up, it exports InstanceTypes and operations created for the FHIR and PlantUML metamodels. Next, you start the importer. The importer has two modes: the PlantUML mode, where it imports a PlantUML state machine and co-evolves it and the FHIR mode, where it imports an FHIR file and co-evolves it into either STU3 or our synthetic version (depending on which of the preloaded servers is running). Just run the tool by providing either FHIR or PlantUML, the imported file and the path where the output should be stored.</p> <p><strong><em>FHIR-Mode:</em></strong></p> <p><em>java -jar importer.jar FHIR C:\Users\Admin\Desktop\Aaron697_Brekke496_2fa15bc7-8866-461a-9000-f739e425860a.json C:\Users\Admin\Desktop\results</em></p> <p><strong>PlantUML Mode:</strong></p> <p><em>java -jar importer.jar PlantUML C:\Users\Admin\Desktop\branch.puml C:\Users\Admin\Desktop\results</em></p> <p><em><strong>Note: </strong></em><em>Please run both the tool and the server in a command line to receive additional information about the importing and co-evolution since the tool is otherwise without a user interface.</em></p> <p> </p>
Data from: Alteration of (frequency-dependent) fitness in time-shift experiments reveals cryptic co-evolution and uncoordinated stasis in a virtual Jurassic Park
Digital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent experimental platform for addressing topics in both short-term and long-term evolution, such as whether co-evolving multispecies communities are dominated more by biotic or abiotic factors, and whether evolutionary stasis affects performance as well as ecological profile. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths (Strong and Weak), along with unperturbed Control experiments. We performed several kinds of competition experiments using simplified versions of these communities to see whether long-term stability that was implied previously by ecological and phylogenetic metrics was also reflected in terms of performance, i.e. whether fitness was static over long periods of time. Results from Control and Weak treatment communities revealed almost completely transitive evolution, while Strong treatment communities showed higher incidences of intransitivity, with pre-treatment ecotypes often able to displace some of their post-recovery successors. However, pre-treatment carryovers more often had lower fitness in mixed communities than in their own fully native conditions. Replacement and invasion experiments pitting single ecotypes against pre-treatment reference communities showed that many of the invading ecotypes could measurably alter the fitnesses of one or more residents, usually with depressive effects, and that the strength of these effects increased over time even in the most stable communities. However, invaders taken from Strong treatment communities often had little to no effect on resident performance. While we detected periods of time when the fitness of a particular evolving ecotype remained static, this stasis was not permanent and was uncoordinated, never affecting an entire community at once. Our results lend support to the fitness-deterioration interpretation of the Red Queen hypothesis, and highlight community context-dependence in determining fitness, the shaping of communities by both biotic factors and abiotic forcing, and the illusory nature of evolutionary stasis. Our results also demonstrate the potential of digital evolution studies to illuminate many aspects of evolution in interacting multispecies communities.
Seasonality and strain specificity drive rapid co-evolution in a Ostreococcus-virus system from the Western Baltic Sea
<p>Marine viruses are a major driver of phytoplankton mortality and thereby influence biogeochemical cycling of carbon and other nutrients. Phytoplankton-targeting viruses are important components of ecosystem dynamics, but broad-scale experimental investigations of host-virus interactions remain scarce. Here, we investigated in detail a picophytoplankton (size 1 µm) host’s responses to infections by species-specific viruses from distinct geographical regions and different sampling seasons. Specifically, we used <em>Ostreococcus tauri </em>and<em> O. mediterraneus</em> and their viruses (size ca. 100 nm). <em>Ostreococcus</em> sp. are globally distributed and, like other picoplankton species, play an important role in coastal ecosystems at certain times of the year. Further,<em> Ostreococcus</em> sp. are model organisms, and the <em>Ostreococcus</em>-virus system is well-known in marine biology. However, only few studies have researched its evolutionary biology and the implications thereof for ecosystem dynamics. The <em>Ostreococcus</em> strains used here stem from different regions of the Southwestern Baltic Sea that vary in salinity and temperature and were obtained during several cruises spanning different sampling seasons. Using an experimental cross-infection set-up, we explicitly confirm species and strain specificity in <em>Ostreococcus</em> sp. from the Baltic Sea. Moreover, we found the timing of virus-host co-existence, was driver of infection patterns as well. In combination, these findings prove that host-virus co-evolution can be rapid in natural systems.</p>
Data from: Using text-mined trait data to test for cooperate-and-radiate co-evolution between ants and plants
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Data from: Alteration of (frequency-dependent) fitness in time-shift experiments reveals cryptic co-evolution and uncoordinated stasis in a virtual Jurassic Park
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Data from: Ancestral chytrid pathogen remains hypervirulent following its long co-evolution with amphibian hosts
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Data from: Co-evolution of cerebral and cerebellar expansion in cetaceans
Cetaceans possess brains that rank among the largest to have ever evolved, either in terms of absolute mass or relative to body size. Cetaceans have evolved these huge brains under relatively unique environmental conditions, making them a fascinating case study to investigate the constraints and selection pressures that shape how brains evolve. Indeed, cetaceans have some unusual neuroanatomical features, including a thin but highly folded cerebrum with low cortical neuron density, as well as many structural adaptations associated with acoustic communication. Previous reports also suggest that at least some cetaceans have an expanded cerebellum, a brain structure with wide-ranging functions in adaptive filtering of sensory information, the control of motor actions, and cognition. Here, we report that, relative to the size of the rest of the brain, both the cerebrum and cerebellum are dramatically enlarged in cetaceans and show evidence of co-evolution, a pattern of brain evolution that is convergent with primates. However, we also highlight several branches where cortico-cerebellar co-evolution may be partially decoupled, suggesting these structures can respond to independent selection pressures. Across cetaceans, we find no evidence of a simple linear relationship between either cerebrum and cerebellum size and the complexity of social ecology or acoustic communication, but do find evidence that their expansion may be associated with dietary breadth. In addition, our results suggest that major increases in both cerebrum and cerebellum size occurred early in cetacean evolution, prior to the origin of the major extant clades, and predate the evolution of echolocation.
Data from: The stable isotope ecology of mycalesine butterflies: implications for plant-insect co-evolution
One of the most dramatic examples of biome shifts in the geological record is the rapid replacement of C3 vegetation by C4 grasses in (sub-) tropical regions during the Late Miocene–Pliocene. Climate-driven biome shifts of this magnitude are expected to have a major impact on diversification and ecological speciation, especially in grazing taxa. Mycalesine butterflies are excellent candidates to explore the evolutionary impact of these C3/C4 shifts on insect grazer communities. Mycalesine butterflies feed on grasses as larvae, have radiated spectacularly and occur in almost all extant habitats across the Old World tropics. However, at present, we lack a comprehensive understanding of the larval ecology of these butterflies and this hampers investigations of co-evolutionary patterns among the geographically parallel radiations of mycalesine butterflies and the remarkable evolutionary history of their host plants. By conducting several experiments under defined environmental conditions, we demonstrate that the feeding history of mycalesine larvae on C3 and C4 grasses can be traced by analysing δ13C in the organic material of the adult exoskeleton, while values of δ18O in the adult reflect atmospheric humidity during larval development. To show the power of these isotopic proxies for ecological studies, we analysed the isotopic composition of organic material obtained from adult butterflies sampled in two extensive longitudinal surveys. We observed strong associations among the larval ecology, habitat preferences of the adult butterflies and patterns of seasonality, such that mycalesine species that inhabit open environments are more opportunistic in their host plant choice but utilize C3 grasses more frequently during the dry season. Crucially, the ability to process the less palatable C4 grasses appears to be phylogenetically clustered within mycalesine species, suggesting that novel feeding adaptations may have evolved in response to the ecological dominance of C4 grasses in open savanna habitats.
Data from: Concurrent co-evolution of intra-organismal cheaters and resisters
The evolution of multicellularity is a major transition that is not yet fully understood. Specifically, we do not know if there are any mechanisms by which multicellularity can be maintained without a single cell bottleneck or other relatedness enhancing mechanisms. Under low relatedness, cheaters can evolve that benefit from the altruistic behaviour of others without themselves sacrificing. If these are obligate cheaters, incapable of co-operating, their spread can lead to the demise of multicellularity. One possibility, however, is that co-operators can evolve resistance to cheaters. We tested this idea in a facultatively multicellular social amoeba, Dictyostelium discoideum. This amoeba usually exists as a single cell but, when stressed, thousands of cells aggregate to form a multicellular organism in which some of the cells sacrifice for the good of others. We used lineages that had undergone experimental evolution at very low relatedness, during which time obligate cheaters evolved. Unlike earlier experiments, which found resistance to cheaters that were prevented from evolving, we competed cheaters and non-cheaters that evolved together, and cheaters with their ancestors. We found that non-cheaters can evolve resistance to cheating before cheating sweeps through the population and multicellularity is lost. Our results provide insight into cheater-resister co-evolutionary dynamics, in turn providing experimental evidence for the maintenance of at least a simple form of multicellularity by means other than high relatedness.
Data from: Modelling the co-evolution of indirect genetic effects and inherited variability
When individuals interact, their phenotypes may be affected by genes in their social partners, a phenomenon known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, competition not only affects trait levels of individuals, but also inflates variation of trait values among individuals. Variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, models of IGE and inherited variability do not allow for such relationship. Models of trait levels show IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to inherited variability. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of genetic and environmental effects of the focal individual and of the difference in trait values between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait which is measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. Our simulations show that the model results in increased variability of body weight with increase of competition. When competition decreases, variability becomes significantly smaller. Our findings suggest we may have been overlooking an entire level of genetic variation in variability, the one due to IGEs.
[DATA] The co-evolution of direct, indirect and generalized reciprocity
<p>The data for the project <em>"The Co-evolution of Direct, Indirect, and Generalized Reciprocity"</em> were generated through simulation code that models evolutionary processes. These data can be used to create all the figures in the manuscript.</p> <p>The code for the evolutionary simulations as well as the analysis code are available on GitHub. The repository can be found here: https://github.com/Saptarshi07/Direct-Indirect-Generalized-Reciprocity/.</p> <div> </div>
Data from: Gene duplication and co-evolution of G1/S transcription factors specificity in fungi are essential for optimizing cell fitness
Transcriptional regulatory networks play a central role in optimizing cell survival. How DNA binding domains and cis-regulatory DNA binding sequences have co-evolved to allow the expansion of transcriptional networks and how this contributes to cellular fitness remains unclear. Here we experimentally explore how the complex G1/S transcriptional network evolved in the budding yeast Saccharomyces cerevisiae by examining different chimeric transcription factor (TF) complexes. Over 300 G1/S genes are regulated by either one of the two TF complexes, SBF and MBF, which bind to specific DNA binding sequences, SCB and MCB, respectively. Our data suggests that whilst SBF is the likely ancestral regulatory complex, the ancestral DNA binding element is more MCB-like. G1/S network expansion took place by both cis- and trans- co-evolutionary changes in closely related but distinct regulatory sequences. Replacement of the endogenous SBF DNA-binding domain (DBD) with that from more distantly related fungi leads to a contraction of the G1/S network in budding yeast, which also correlates with increased defects in cell growth, cell size, and proliferation. This indicates that expansion of the G1/S network in budding yeast may represent an evolutionary product of selection for cell cycle fitness.
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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.