Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
173
datasets available to search
ShareScore release 0.9.0
Dataset results
173 results for “evolutionary dynamics”
Data from: Eco-evolutionary dynamics in metacommunities: ecological inheritance, helping within species, and harming between species
Understanding selection on intra- and inter-specific interactions that take place in dispersal-limited communities is a challenge for ecology and evolutionary biology. The problem is that local demographic stochasticity generates eco-evolutionary dynamics that are generally too complicated to make tractable analytical investigations. Here, we circumvent this problem by approximating the selection gradient on a quantitative trait that influences local community dynamics, assuming that such dynamics are deterministic with a stable fixed point. We nonetheless incorporate unavoidable kin selection effects arising from demographic stochasticity. Our approximation reveals that selection depends on how an individual expressing a trait-change influences: (1) its own fitness and the fitness of its current relatives; and (2) the fitness of its downstream relatives through modifications of local ecological conditions (i.e., through ecological inheritance). Mathematically, the effects of ecological inheritance on selection are captured by dispersal-limited versions of press-perturbations of community ecology. We use our approximation to investigate the evolution of helping within- and harming between-species when these behaviours influence demography. We find that altruistic helping evolves more readily when intra-specific competition is for material resources rather than for space because in this case, the costs of kin competition tend to paid by downstream relatives. Similarly, altruistic harming between species evolves when it alleviates downstream relatives from inter-specific competition. Beyond these examples, our approximation can help better understand the influence of ecological inheritance on a variety of eco-evolutionary dynamics in metacommunities, from consumer-resource and predator-prey coevolution to selection on mating systems with demographic feedbacks.
Supplementary material from "Evolutionary dynamics of sustainability ideas in China: inferences from ecological and economic concepts usage in People's Daily"
<p>Previous cultural evolutionary analyses have exploited the use of neutral models, or random copying models, analogous to neutral genetic drift, as null models to distinguish the unbiased copying and biased transmission of neutral cultural traits, but the dynamics and underlying mechanism of non-neutral cultural traits have not yet been explored. Adopting an ecological perspective, we define ecological and economic concepts as non-neutral cultural traits constitute a complex ecosystem of meaning representing sustainability ideas. We analyse the frequency distribution, turnover and innovation rates of nearly 4000 concepts appearing in <i>People's Daily</i> from 1946 to 2015. The results reveal that, ecological concepts show stronger tendency towards random copying than economic concepts. The popular ecological and economic concepts may experience conformist bias and anti-conformist bias respectively. Semantic and pragmatic differences of popular concepts affect the variability which indicate stronger cultural drift in the ontological domain. The frequency change in popular concepts also suggests positive selection due to political strategy and governmental policy.</p>
Supplementary material 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Detailed design of the Field Experiment
Supplementary material 2 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Brief description of the Field Experiment
Figure 1 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 1 A. Conceptual diagram of the mechanistic approach of the planned Research Unit. B. Conceptual scheme of the proposed evolutionary niche shifts in plant monocultures and mixtures. This idea feeds into our understanding of how evolutionary history influences the ecological interactions of species that compete for growth factors, ultimately defining biotope space (gray rectangle; Hutchinson 1978). Graphically depicted, species (ellipses) in mixture will show increasing niche differentiation over time due to competition (niche overlap). Thus, history of selection in diverse communities is expected to result in greater interspecific differences (less overlap of ellipses) and more specialization (smaller ellipses) than a history of isolation (monocultures). In monocultures, species will experience strong selection pressure by accumulating soil-borne pathogens, and species may invest energy in chemical and morphological defense traits (depicted by ellipses shifting towards the same corner of the habitat space). Plants in mixtures together may exploit more available biotope space than single monocultures, causing increasing diversity effects on ecosystem functions over time. However, there is limited support for this assumption for traits related to light (e.g., Lipowsky et al. 2015, Roscher et al. 2015) and resource use (Jesch et al. 2018) so far.
Figure 4 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 4 Experimental design and hypotheses of the Ecotron Experiment. Briefly, four treatments will be established based on monoliths from a selection of the 9-year old Trait-Based Experiment (TBE; Ebeling et al. 2014) and from bare ground plots of the Jena Experiment as well as two seed sources: the respective plots and the original seed material that was used for the set-up of the TBE. (1) With plot-specific plant history and with plot-specific soil history; (2) without plot-specific plant history and with plot-specific soil history; (3) with plot-specific plant history and without plot-specific soil history; and (4) without plot-specific plant history and without plot-specific soil history. We expect the biodiversity–ecosystem function relationships to differ among the four treatments (see main text for details).
Figure 3 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 3 Hypothesized slope of BEF relationships in the different treatments of the Field Experiment (see main text for details). Note that the 'with plant history, with soil history' only serves as a control in the Field Experiment, and effects of plant history can only be tested in the planned Ecotron Experiment. Redrawn after Vogel et al. (2019). '+', with; '-', without.
Supplementary material 4 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Detailed design of the Ecotron Experiment
Supplementary material 5 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Brief description of the Ecotron Experiment
Figure 2 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Figure 2 Structure of the proposed Research Unit. Three complementary experimental approaches are envisaged to study long-term biodiversity-ecosystem function (BEF) relationships, and how these are influenced by plant history and soil history. BEF patterns are studied in the Field Experiment with long-term plant diversity plots and manipulations of soil-history effects. BEF mechanisms are studied in the Ecotron Experiment and in Microcosm Experiments. In the Ecotron Experiment, plant history and soil history are independently crossed and detailed process measurements are possible. The Microcosm Experiments zoom in on focal interactions. In the Field Experiment and in the Ecotron Experiment, studies are conducted at the community level as well as at the plant individual level (magnifier; see detailed design of studies in the Appendices). Subprojects' (SPs') participation in experiments are illustrated with lines. The SPs of the proposed Research Unit fall into two tightly linked main categories (in gray) with two research areas each that aim at exploring variation in community assembly processes, micro-evolutionary changes, and resulting differences in biotic interactions as determinants of the long-term BEF relationship. Subprojects under "Microbial community assembly" (blue) and "Assembly and functions of animal communities" (red) mostly focus on plant diversity effects on the assembly of communities and their feedback effects on biotic interactions and ecosystem functions, while subprojects under "Mediators of plant-biotic interactions" (orange) and "Intraspecific diversity and micro-evolutionary changes" (green) mostly focus on plant diversity effects on plant trait expression and micro-evolution. PIs with requested personnel are underlined.
Supplementary material 3 from: Eisenhauer N, Bonkowski M, Brose U, Buscot F, Durka W, Ebeling A, Fischer M, Gleixner G, Heintz-Buschart A, Hines J, Jesch A, Lange M, Meyer S, Roscher C, Scheu S, Schielzeth H, Schloter M, Schulz S, Unsicker S, van Dam NM, Weigelt A, Weisser WW, Wirth C, Wolf J, Schmid B (2019) Biotic interactions, community assembly, and eco-evolutionary dynamics as drivers of long-term biodiversity–ecosystem functioning relationships. Research Ideas and Outcomes 5: e47042. https://doi.org/10.3897/rio.5.e47042
Plant species lists of the Field Experiment and the Ecotron Experiment
Data from: The evolutionary dynamics of sexually antagonistic mutations in pseudoautosomal regions of sex chromosomes
Sex chromosomes can evolve gene contents that differ from the rest of the genome, as well as larger sex differences in gene expression compared with autosomes. This probably occurs because fully sex-linked beneficial mutations substitute at different rates from autosomal ones, especially when fitness effects are sexually antagonistic (SA). The evolutionary properties of genes located in the recombining pseudo-autosomal region (PAR) of a sex chromosome have not previously been modelled in detail. Such PAR genes differ from classical sex-linked genes by having two alleles at a locus in both sexes; in contrast to autosomal genes, however, variants can become associated with gender. The evolutionary fates of PAR genes may therefore differ from those of either autosomal or fully sex-linked genes. Here, we model their evolutionary dynamics by deriving expressions for the selective advantages of PAR gene mutations under different conditions. We show that, unless selection is very strong, the probability of invasion of a population by an SA mutation is usually similar to that of an autosomal mutation, unless there is close linkage to the sex-determining region. Most PAR genes should thus evolve similarly to autosomal rather than sex-linked genes, unless recombination is very rare in the PAR.
Data from: Co-evolutionary dynamics between a defensive microbe and a pathogen driven by fluctuating selection
Open the record for dataset details and reuse information.
Data from: Inference of Japanese encephalitis virus ecological and evolutionary dynamics from passive and active virus surveillance
Open the record for dataset details and reuse information.
Data from: Evolutionary dynamics of the cryptocurrency market
Open the record for dataset details and reuse information.
Data from: Co-evolutionary dynamics between public good producers and cheats in the bacterium Pseudomonas aeruginosa
Open the record for dataset details and reuse information.
Data from: Mechanical sensitivity reveals evolutionary dynamics of mechanical systems
Open the record for dataset details and reuse information.
Data from: Evolutionary dynamics of separate and combined exposure of Pseudomonas fluorescens SBW25 to antibiotics and bacteriophage
Open the record for dataset details and reuse information.
Data from: Estimating dispersal and evolutionary dynamics in diploporan blastozoans (Echinodermata) across the Great Ordovician Biodiversification Event
Open the record for dataset details and reuse information.
Data from: Evolutionary dynamism in bryophytes: phylogenomic inferences confirm rapid radiation in the moss family Funariaceae
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.