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      A trait database and updated checklist for European subterranean spiders

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          Abstract

          Species traits are an essential currency in ecology, evolution, biogeography, and conservation biology. However, trait databases are unavailable for most organisms, especially those living in difficult-to-access habitats such as caves and other subterranean ecosystems. We compiled an expert-curated trait database for subterranean spiders in Europe using both literature data (including grey literature published in many different languages) and direct morphological measurements whenever specimens were available to us. We started by updating the checklist of European subterranean spiders, now including 512 species across 20 families, of which at least 192 have been found uniquely in subterranean habitats. For each of these species, we compiled 64 traits. The trait database encompasses morphological measures, including several traits related to subterranean adaptation, and ecological traits referring to habitat preference, dispersal, and feeding strategies. By making these data freely available, we open up opportunities for exploring different research questions, from the quantification of functional dimensions of subterranean adaptation to the study of spatial patterns in functional diversity across European caves.

          Abstract

          Measurement(s) morphological trait • ecological trait
          Technology Type(s) literature extraction • observation
          Sample Characteristic - Organism Agelenidae • Amaurobiidae • Anapidae • Cybaeidae • Dysderidae • Hahniidae • Leptonetidae • Linyphiidae • Liocranidae • Mysmenidae • Nesticidae • Pholcidae • Pimoidae • Segestriidae • Sicariidae • Sparassidae • Symphytognathidae • Telemidae • Tetragnathidae • Theridiidae
          Sample Characteristic - Environment caves • subterranean habitats
          Sample Characteristic - Location Europe

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            ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R

            After more than fifteen years of existence, the R package ape has continuously grown its contents, and has been used by a growing community of users. The release of version 5.0 has marked a leap towards a modern software for evolutionary analyses. Efforts have been put to improve efficiency, flexibility, support for 'big data' (R's long vectors), ease of use and quality check before a new release. These changes will hopefully make ape a useful software for the study of biodiversity and evolution in a context of increasing data quantity.
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              Rebuilding community ecology from functional traits.

              There is considerable debate about whether community ecology will ever produce general principles. We suggest here that this can be achieved but that community ecology has lost its way by focusing on pairwise species interactions independent of the environment. We assert that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context of a biotic interaction milieu. We suggest this approach can create a more quantitative and predictive science that can more readily address issues of global change.
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                Author and article information

                Contributors
                stefano.mammola@helsinki.fi , stefano.mammola@cnr.it
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                26 May 2022
                26 May 2022
                2022
                : 9
                : 236
                Affiliations
                [1 ]GRID grid.7737.4, ISNI 0000 0004 0410 2071, LIBRe—Laboratory for Integrative Biodiversity Research, Finnish Museum of Natural History, , University of Helsinki, ; Helsinki, Finland
                [2 ]GRID grid.5326.2, ISNI 0000 0001 1940 4177, DarkMEG—Molecular Ecology Group, Water Research Institute, National Research Council of Italy (CNR), ; Verbania, Pallanza Italy
                [3 ]GRID grid.4905.8, ISNI 0000 0004 0635 7705, Ruđer Bošković Institute, ; Zagreb, Croatia
                [4 ]Croatian Biospeleological Society, Zagreb, Croatia
                [5 ]GRID grid.5841.8, ISNI 0000 0004 1937 0247, Department of Evolutionary Biology, Ecology and Environmental Sciences, Biodiversity Research Institute (IRBio), , Universitat de Barcelona, ; Barcelona, Spain
                [6 ]GRID grid.452935.c, ISNI 0000 0001 2216 5875, Zoological Research Museum Alexander Koenig, ; Bonn, Germany
                [7 ]GRID grid.7605.4, ISNI 0000 0001 2336 6580, Department of Life Sciences and Systems Biology, , University of Turin, ; Torino, Italy
                [8 ]GRID grid.265074.2, ISNI 0000 0001 1090 2030, Systematic Zoology Laboratory, Department of Biological Sciences, , Tokyo Metropolitan University, Minami-Osawa, Hachioji-shi, ; Tokyo, Japan
                [9 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Zoology, , University of Oxford, ; Oxford, UK
                [10 ]GRID grid.9227.e, ISNI 0000000119573309, Key Laboratory of the Zoological Systematics and Evolution, Institute of Zoology, , Chinese Academy of Sciences, ; Beijing, China
                [11 ]GRID grid.8404.8, ISNI 0000 0004 1757 2304, Museo di Storia Naturale dell’Università degli Studi di Firenze, “La Specola”, ; Firenze, Italy
                [12 ]GRID grid.7849.2, ISNI 0000 0001 2150 7757, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNA, ; F-69622 Villeurbanne, France
                [13 ]GRID grid.7737.4, ISNI 0000 0004 0410 2071, Department of Geosciences and Geography, , University of Helsinki, ; Helsinki, Finland
                Author information
                http://orcid.org/0000-0002-4471-9055
                http://orcid.org/0000-0001-6710-0581
                http://orcid.org/0000-0002-7566-5424
                http://orcid.org/0000-0001-5434-2127
                http://orcid.org/0000-0002-3013-7337
                http://orcid.org/0000-0002-4228-2750
                Article
                1316
                10.1038/s41597-022-01316-3
                9135732
                35064126
                7f760850-6763-4403-8a11-fdf5fbccf846
                © 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
                : 1 October 2021
                : 5 April 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000780, European Commission (EC);
                Award ID: 882221
                Award ID: 882221
                Award Recipient :
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                © The Author(s) 2022

                community ecology,taxonomy,conservation biology
                community ecology, taxonomy, conservation biology

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