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      Regional uniqueness of tree species composition and response to forest loss and climate change

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          Abstract

          The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change.

          Abstract

          This study maps global tree composition in forests and assesses the impacts of historical forest cover loss and climate change. The results highlight the need for preserving the remaining large forest biomes, while regenerating degraded forests in a way that provides resilience against climate change.

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          Matplotlib: A 2D Graphics Environment

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            Welcome to the Tidyverse

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              Array programming with NumPy

              Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
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                Author and article information

                Contributors
                nina.vantiel@epfl.ch
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                31 May 2024
                31 May 2024
                2024
                : 15
                : 4375
                Affiliations
                [1 ]Global Ecosystem Ecology, Department of Environmental Systems Science, ETH Zürich, ( https://ror.org/05a28rw58) Zürich, Switzerland
                [2 ]Environmental Computational Science and Earth Observation Laboratory, Ecole Polytechnique Fédérale de Lausanne, ( https://ror.org/02s376052) Lausanne, Switzerland
                [3 ]Ecosystems and Landscape Evolution, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, ( https://ror.org/05a28rw58) Zürich, Switzerland
                [4 ]GRID grid.419754.a, ISNI 0000 0001 2259 5533, Land Change Science Research Unit, Swiss Federal Institute for Forest, , Snow and Landscape Research, ; WSL Birmensdorf, Switzerland
                [5 ]GRID grid.419754.a, ISNI 0000 0001 2259 5533, Biodiversity and Conservation Biology, Swiss Federal Institute for Forest, , Snow and Landscape Research, ; WSL Birmensdorf, Switzerland
                [6 ]Laboratory of Biomolecular Research, Biology and Chemistry Division, Paul Scherrer Institute, ( https://ror.org/03eh3y714) PSI Villigen, Switzerland
                [7 ]Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, ( https://ror.org/05a28rw58) Zürich, Switzerland
                Author information
                http://orcid.org/0009-0003-7159-8783
                http://orcid.org/0000-0003-0648-8484
                http://orcid.org/0000-0002-2750-9793
                http://orcid.org/0000-0001-7770-6229
                http://orcid.org/0000-0002-8246-9667
                http://orcid.org/0000-0003-0374-2459
                http://orcid.org/0000-0003-3099-9604
                http://orcid.org/0000-0001-5674-8913
                http://orcid.org/0000-0002-2289-8259
                Article
                48276
                10.1038/s41467-024-48276-3
                11143270
                38821947
                a78aeddb-3743-4f0b-9fad-eaadaac10474
                © The Author(s) 2024

                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 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/.

                History
                : 16 June 2023
                : 26 April 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation);
                Award ID: 204057
                Award ID: 20BD21_193907
                Award ID: 20BD21_184131
                Award ID: 204057
                Award ID: 20BD21_193907
                Award Recipient :
                Funded by: DOB Ecology IJsseldijk 1 8194 LA Veessen Restor Foundation Fraumünsterstrasse 16 8001 Zürich
                Funded by: Internal WSL grant ClimEx Swiss Federal Research Institute WSL Zürcherstrasse 111 CH-8903 Birmensdorf
                Funded by: Internal WSL grant Treemap Swiss Federal Research Institute WSL Zürcherstrasse 111 CH-8903 Birmensdorf
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                biodiversity,conservation biology,climate-change ecology,ecological modelling,forest ecology

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