7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth’s biodiversity

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed. We present a general, spatially explicit, eco-evolutionary engine with a modular implementation that enables the modeling of multiple macroecological and macroevolutionary processes and feedbacks across representative spatiotemporally dynamic landscapes. Modeled processes can include species’ abiotic tolerances, biotic interactions, dispersal, speciation, and evolution of ecological traits. Commonly observed biodiversity patterns, such as α, β, and γ diversity, species ranges, ecological traits, and phylogenies, emerge as simulations proceed. As an illustration, we examine alternative hypotheses expected to have shaped the latitudinal diversity gradient (LDG) during the Earth’s Cenozoic era. Our exploratory simulations simultaneously produce multiple realistic biodiversity patterns, such as the LDG, current species richness, and range size frequencies, as well as phylogenetic metrics. The model engine is open source and available as an R package, enabling future exploration of various landscapes and biological processes, while outputs can be linked with a variety of empirical biodiversity patterns. This work represents a key toward a numeric, interdisciplinary, and mechanistic understanding of the physical and biological processes that shape Earth’s biodiversity.

          Abstract

          This study describes a novel mechanistic engine that predicts a realistic global latitudinal diversity gradient, species richness distribution and phylogenies. This approach is a step towards the interdisciplinary numeric understanding of the physical and biological processes that have shaped Earth’s biodiversity.

          Related collections

          Most cited references182

          • Record: found
          • Abstract: found
          • Article: not found

          Trends, rhythms, and aberrations in global climate 65 Ma to present.

          Since 65 million years ago (Ma), Earth's climate has undergone a significant and complex evolution, the finer details of which are now coming to light through investigations of deep-sea sediment cores. This evolution includes gradual trends of warming and cooling driven by tectonic processes on time scales of 10(5) to 10(7) years, rhythmic or periodic cycles driven by orbital processes with 10(4)- to 10(6)-year cyclicity, and rare rapid aberrant shifts and extreme climate transients with durations of 10(3) to 10(5) years. Here, recent progress in defining the evolution of global climate over the Cenozoic Era is reviewed. We focus primarily on the periodic and anomalous components of variability over the early portion of this era, as constrained by the latest generation of deep-sea isotope records. We also consider how this improved perspective has led to the recognition of previously unforeseen mechanisms for altering climate.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            On the Relationship between Abundance and Distribution of Species

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist.

              A recent increase in studies of β diversity has yielded a confusing array of concepts, measures and methods. Here, we provide a roadmap of the most widely used and ecologically relevant approaches for analysis through a series of mission statements. We distinguish two types of β diversity: directional turnover along a gradient vs. non-directional variation. Different measures emphasize different properties of ecological data. Such properties include the degree of emphasis on presence/absence vs. relative abundance information and the inclusion vs. exclusion of joint absences. Judicious use of multiple measures in concert can uncover the underlying nature of patterns in β diversity for a given dataset. A case study of Indonesian coral assemblages shows the utility of a multi-faceted approach. We advocate careful consideration of relevant questions, matched by appropriate analyses. The rigorous application of null models will also help to reveal potential processes driving observed patterns in β diversity. © 2010 Blackwell Publishing Ltd/CNRS.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Software
                Role: Data curationRole: Software
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – review & editing
                Role: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                12 July 2021
                July 2021
                12 July 2021
                : 19
                : 7
                : e3001340
                Affiliations
                [1 ] Landscape Ecology, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
                [2 ] Land Change Science Research Unit, Swiss Federal Institute for Forest, Snow and Landscape Research, WSL, Birmensdorf, Switzerland
                [3 ] Ecosystem Modeling, Center for Computational and Theoretical Biology, University of Würzburg, Würzburg, Germany
                [4 ] Theoretical Ecology, University of Regensburg, Regensburg, Germany
                [5 ] Department of Biology, Lund University, Lund, Sweden
                [6 ] Department of Ecology, Institute of Biological Sciences, Federal University of Goiás, Goiânia, Brazil
                University of Cambridge, UNITED KINGDOM
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-7931-6571
                https://orcid.org/0000-0002-0116-220X
                https://orcid.org/0000-0002-6255-9059
                https://orcid.org/0000-0002-2001-7382
                Article
                PBIOLOGY-D-20-01974
                10.1371/journal.pbio.3001340
                8384074
                34252071
                49a4ad80-e92a-4774-811d-92f3abccd2af
                © 2021 Hagen et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 July 2020
                : 23 June 2021
                Page count
                Figures: 4, Tables: 4, Pages: 31
                Funding
                Funded by: Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
                Award ID: DFG FZT 118
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 310030_188550
                Award Recipient :
                OH, JC, FH, MP, TR and LP were part of the sELDiG working group, which was supported by the Synthesis Centre of the German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig (DFG FZT 118). LP was supported by the Swiss National Science Foundation grant (N° 310030_188550). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Methods and Resources
                Biology and Life Sciences
                Ecology
                Biodiversity
                Ecology and Environmental Sciences
                Ecology
                Biodiversity
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Speciation
                Biology and Life Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Ecology and Environmental Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Biology and Life Sciences
                Ecology
                Theoretical Ecology
                Ecology and Environmental Sciences
                Ecology
                Theoretical Ecology
                Biology and Life Sciences
                Biogeography
                Phylogeography
                Ecology and Environmental Sciences
                Biogeography
                Phylogeography
                Earth Sciences
                Geography
                Biogeography
                Phylogeography
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Genetics
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Speciation
                Species Delimitation
                Biology and Life Sciences
                Conservation Biology
                Species Extinction
                Ecology and Environmental Sciences
                Conservation Science
                Conservation Biology
                Species Extinction
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Species Extinction
                Biology and Life Sciences
                Paleontology
                Paleogenetics
                Earth Sciences
                Paleontology
                Paleogenetics
                Custom metadata
                vor-update-to-uncorrected-proof
                2021-07-22
                Gen3sis is implemented in a mix of R and C++ code, and wrapped into an R-package. All high-level functions that the user may interact with are written in R, and are documented via the standard R / Roxygen help files for R-packages. Runtime-critical functions are implemented in C++ and coupled to R via the Rcpp framework. Additionally, the package provides several convenience functions to generate input data, configuration files and plots, as well as tutorials in the form of vignettes that illustrate how to declare models and run simulations. The software, under an open and free GPL3 license, can be downloaded from CRAN at https://CRAN.R-project.org/package=gen3sis. The development version, open to issue reporting and feature suggestions, is available at https://github.com/project-Gen3sis/R-package. Supporting information, such as notes, scripts, data, figures and animations, are available at https://zenodo.org/record/5006413, facilitating full reproducibility.

                Life sciences
                Life sciences

                Comments

                Comment on this article