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      Climate-induced forest dieback drives compositional changes in insect communities that are more pronounced for rare species

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          Abstract

          Species richness, abundance and biomass of insects have recently undergone marked declines in Europe. We metabarcoded 211 Malaise-trap samples to investigate whether drought-induced forest dieback and subsequent salvage logging had an impact on ca. 3000 species of flying insects in silver fir Pyrenean forests. While forest dieback had no measurable impact on species richness, there were significant changes in community composition that were consistent with those observed during natural forest succession. Importantly, most observed changes were driven by rare species. Variation was explained primarily by canopy openness at the local scale, and the tree-related microhabitat diversity and deadwood amount at landscape scales. The levels of salvage logging in our study did not explain compositional changes. We conclude that forest dieback drives changes in species assemblages that mimic natural forest succession, and markedly increases the risk of catastrophic loss of rare species through homogenization of environmental conditions.

          Abstract

          Sire et al. examine the effects of climate-induced forest dieback and salvage logging on insect diversity in silver fir Pyrenean forests using metabarcoding. Although no consistent variation in species richness was found, forest dieback cause massive changes in community composition particularly affecting rare species.

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            BLAST+: architecture and applications

            Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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              VSEARCH: a versatile open source tool for metagenomics

              Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
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                Author and article information

                Contributors
                lucas.sire@univ-tours.fr
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                18 January 2022
                18 January 2022
                2022
                : 5
                : 57
                Affiliations
                [1 ]Institut de Recherche sur la Biologie de l’Insecte (IRBI), UMR 7261, CNRS-Université de Tours, Tours, France
                [2 ]GRID grid.419247.d, ISNI 0000 0001 2108 8097, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), ; Müggelseedamm 301, 12587 Berlin, Germany
                [3 ]GRID grid.419010.d, ISNI 0000 0004 1792 7072, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, ; Kunming, Yunnan 650223 China
                [4 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, Kunming College of Life Sciences, University of Chinese Academy of Sciences, ; Kunming, China
                [5 ]GRID grid.507621.7, INRAE, Zoologie Forestière, ; F-45075 Orléans, France
                [6 ]INRAE ‘Forest Ecosystems’ Research Unit – Biodiversity team Domaine des Barres, F-45290 Nogent-sur-Vernisson, France
                [7 ]GRID grid.435629.f, ISNI 0000 0004 1755 3971, Water Research Institute, National Research Council of Italy, CNR-IRSA, ; Largo Tonolli 50, 28922 Verbania Pallanza, Italy
                [8 ]Université de Toulouse, INRAE, UMR DYNAFOR, Castanet-Tolosan, France
                [9 ]CRPF Occitanie, Tarbes, France
                [10 ]Field Station Fabrikschleichach, Department of Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Glashüttenstraße 5, 96181 Rauhenebrach, Germany
                [11 ]GRID grid.452215.5, ISNI 0000 0004 7590 7184, Bavarian Forest National Park, ; Freyunger Str. 2, 94481 Grafenau, Germany
                [12 ]GRID grid.8273.e, ISNI 0000 0001 1092 7967, School of Biological Sciences, University of East Anglia, ; Norwich Research Park, Norwich, Norfolk NR47TJ UK
                [13 ]GRID grid.14095.39, ISNI 0000 0000 9116 4836, Institut für Biologie, Freie Universität Berlin, ; Königin-Luise-Straße. 1-3, 12489 Berlin, Germany
                Author information
                http://orcid.org/0000-0002-2911-6109
                http://orcid.org/0000-0002-2528-4260
                http://orcid.org/0000-0002-5770-0353
                http://orcid.org/0000-0002-3062-3060
                http://orcid.org/0000-0002-1409-1586
                http://orcid.org/0000-0001-8551-5609
                http://orcid.org/0000-0001-6200-2376
                http://orcid.org/0000-0003-2278-2368
                Article
                2968
                10.1038/s42003-021-02968-4
                8766456
                35042989
                0dc0213b-e348-4fe7-ae9c-b5447bfa990e
                © The Author(s) 2022

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 May 2021
                : 7 December 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001665, Agence Nationale de la Recherche (French National Research Agency);
                Award ID: ANR-15-MASC-002-01
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001655, Deutscher Akademischer Austauschdienst (German Academic Exchange Service);
                Award ID: 57440917
                Award Recipient :
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                © The Author(s) 2022

                molecular ecology,biodiversity
                molecular ecology, biodiversity

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