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      New Guinean orogenic dynamics and biota evolution revealed using a custom geospatial analysis pipeline

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          Abstract

          Background

          The New Guinean archipelago has been shaped by millions of years of plate tectonic activity combined with long-term fluctuations in climate and sea level. These processes combined with New Guinea’s location at the tectonic junction between the Australian and Pacific plates are inherently linked to the evolution of its rich endemic biota. With the advent of molecular phylogenetics and an increasing amount of geological data, the field of New Guinean biogeography begins to be reinvigorated.

          Results

          We inferred a comprehensive dated molecular phylogeny of endemic diving beetles to test historical hypotheses pertaining to the evolution of the New Guinean biota. We used geospatial analysis techniques to compare our phylogenetic results with a newly developed geological terrane map of New Guinea as well as the altitudinal and geographic range of species ( https://arcg.is/189zmz). Our divergence time estimations indicate a crown age (early diversification) for New Guinea Exocelina beetles in the mid-Miocene ca. 17 Ma, when the New Guinean orogeny was at an early stage. Geographic and geological ancestral state reconstructions suggest an origin of Exocelina ancestors on the eastern part of the New Guinean central range on basement rocks (with a shared affinity with the Australian Plate). Our results do not support the hypothesis of ancestors migrating to the northern margin of the Australian Plate from Pacific terranes that incrementally accreted to New Guinea over time. However, our analyses support to some extent a scenario in which Exocelina ancestors would have been able to colonize back and forth between the amalgamated Australian and Pacific terranes from the Miocene onwards. Our reconstructions also do not support an origin on ultramafic or ophiolite rocks that have been colonized much later in the evolution of the radiation. Macroevolutionary analyses do not support the hypothesis of heterogeneous diversification rates throughout the evolution of this radiation, suggesting instead a continuous slowdown in speciation.

          Conclusions

          Overall, our geospatial analysis approach to investigate the links between the location and evolution of New Guinea’s biota with the underlying geology sheds a new light on the patterns and processes of lineage diversification in this exceedingly diverse region of the planet.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12862-021-01764-2.

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          Most cited references97

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          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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                Author and article information

                Contributors
                balke.m@snsb.de
                Journal
                BMC Ecol Evol
                BMC Ecol Evol
                BMC Ecology and Evolution
                BioMed Central (London )
                2730-7182
                6 April 2021
                6 April 2021
                2021
                : 21
                : 51
                Affiliations
                [1 ]GRID grid.466902.f, ISNI 0000 0001 2248 6951, Natural History Museum of Geneva, ; CP 6434, 1211 Geneva 6, Switzerland
                [2 ]GRID grid.1007.6, ISNI 0000 0004 0486 528X, GeoQuEST Research Centre, School of Earth, Atmospheric and Life Sciences, , University of Wollongong, ; Wollongong, NSW 2522 Australia
                [3 ]GRID grid.425585.b, ISNI 0000 0001 2259 6528, Naturhistorisches Museum Wien, ; Burgring 7, 1010 Vienna, Austria
                [4 ]GRID grid.452781.d, ISNI 0000 0001 2203 6205, SNSB‐Zoologische Staatssammlung München, ; Munich, Germany
                [5 ]GRID grid.47840.3f, ISNI 0000 0001 2181 7878, Department of Environmental Science, Policy and Management, , University of California, ; Berkeley, CA USA
                [6 ]GRID grid.242287.9, ISNI 0000 0004 0461 6769, Institute for Biodiversity Science and Sustainability, , California Academy of Sciences, ; San Francisco, CA USA
                [7 ]GRID grid.443497.9, ISNI 0000 0004 0385 9267, Department of Biology, , Universitas Cenderawasih (UNCEN), ; Waena, Papua Indonesia
                [8 ]GRID grid.443762.0, ISNI 0000 0000 9845 8298, Department of Biology, Faculty of Sciences and Mathematics, , State University of Papua (UNIPA), ; Jalan Gunung Salju Amban, Manokwari, 98314 West Papua Indonesia
                [9 ]Walian 2, Tomohon Selatan, 95439 N Sulawesi Indonesia
                [10 ]GRID grid.422371.1, ISNI 0000 0001 2293 9957, Museum Für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, ; Invalidenstraße 43, 10115 Berlin, Germany
                [11 ]GRID grid.412690.8, ISNI 0000 0001 0663 0554, University of Papua New Guinea, ; Port Moresby, Papua New Guinea
                [12 ]GRID grid.452781.d, ISNI 0000 0001 2203 6205, Department of Entomology, , SNSB‐Zoologische Staatssammlung München, ; Münchhausenstrasse 21, 81247 Munich, Germany
                Author information
                https://orcid.org/0000-0002-8439-1285
                https://orcid.org/0000-0002-1829-0881
                https://orcid.org/0000-0001-5034-7342
                https://orcid.org/0000-0002-7782-6041
                https://orcid.org/0000-0002-6253-3078
                http://orcid.org/0000-0002-3773-6586
                Article
                1764
                10.1186/s12862-021-01764-2
                8022562
                34cfb7df-45af-4a5d-8293-5d250022aa0d
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 18 September 2020
                : 9 February 2021
                Funding
                Funded by: DFG
                Award ID: BA2152/3-1, 6-1, 7-1, 11-1, 11-2, 17-1, 19-1, 19-2
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 16GW0111K, 16GW0112
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: P 24312-B17, P 31347-B25
                Funded by: FundRef http://dx.doi.org/10.13039/501100005341, Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst;
                Award ID: Innovativ Program
                Award Recipient :
                Funded by: UK Darwin Initiative
                Award ID: Training the next generation of PNG conservation biologists
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                beetle evolution,dytiscidae paleogeography,island biogeography,melanesia,foja gauttier mountains,ultramafic rocks,water beetle phylogenetics

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