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      A new comprehensive trait database of European and Maghreb butterflies, Papilionoidea

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          Abstract

          Trait-based analyses explaining the different responses of species and communities to environmental changes are increasing in frequency. European butterflies are an indicator group that responds rapidly to environmental changes with extensive citizen science contributions to documenting changes of abundance and distribution. Species traits have been used to explain long- and short-term responses to climate, land-use and vegetation changes. Studies are often characterised by limited trait sets being used, with risks that the relative roles of different traits are not fully explored. Butterfly trait information is dispersed amongst various sources and descriptions sometimes differ between sources. We have therefore drawn together multiple information sets to provide a comprehensive trait database covering 542 taxa and 25 traits described by 217 variables and sub-states of the butterflies of Europe and Maghreb (northwest Africa) which should serve for improved trait-based ecological, conservation-related, phylogeographic and evolutionary studies of this group of insects. We provide this data in two forms; the basic data and as processed continuous and multinomial data, to enhance its potential usage.

          Abstract

          Measurement(s) resources • Egg Laying • larval environment • pupal environment • geographic location • behavior • size • voltinism • phenology • host plant
          Technology Type(s) digital curation
          Factor Type(s) species
          Sample Characteristic - Organism Papilionoidea
          Sample Characteristic - Location Europe • Northwest Africa

          Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12998828

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          Most cited references139

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          MissForest--non-parametric missing value imputation for mixed-type data.

          Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often depend on a complete set. Missing value imputation offers a solution to this problem. However, the majority of available imputation methods are restricted to one type of variable only: continuous or categorical. For mixed-type data, the different types are usually handled separately. Therefore, these methods ignore possible relations between variable types. We propose a non-parametric method which can cope with different types of variables simultaneously. We compare several state of the art methods for the imputation of missing values. We propose and evaluate an iterative imputation method (missForest) based on a random forest. By averaging over many unpruned classification or regression trees, random forest intrinsically constitutes a multiple imputation scheme. Using the built-in out-of-bag error estimates of random forest, we are able to estimate the imputation error without the need of a test set. Evaluation is performed on multiple datasets coming from a diverse selection of biological fields with artificially introduced missing values ranging from 10% to 30%. We show that missForest can successfully handle missing values, particularly in datasets including different types of variables. In our comparative study, missForest outperforms other methods of imputation especially in data settings where complex interactions and non-linear relations are suspected. The out-of-bag imputation error estimates of missForest prove to be adequate in all settings. Additionally, missForest exhibits attractive computational efficiency and can cope with high-dimensional data. The package missForest is freely available from http://stat.ethz.ch/CRAN/. stekhoven@stat.math.ethz.ch; buhlmann@stat.math.ethz.ch
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            The ecological implications of body size

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              Differences in the climatic debts of birds and butterflies at a continental scale

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                Author and article information

                Contributors
                tgshreeve@brookes.ac.uk
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                15 October 2020
                15 October 2020
                2020
                : 7
                : 351
                Affiliations
                [1 ]GRID grid.7628.b, ISNI 0000 0001 0726 8331, Centre for Ecology, Environment and Conservation, Faculty of Health and Life Sciences, , Oxford Brookes University, ; Oxford, OX3 0BP UK
                [2 ]ZEN lab., Dipartimento di Biologia dell’Università di Firenze, Via Madonna del Piano 6, 50019 Comune di Sesto Fiorentino, Firenze, Italy
                [3 ]GRID grid.5515.4, ISNI 0000000119578126, Department of Biology, , Universidad Autónoma de Madrid, Campus Cantoblanco, ; 28049 Madrid, Spain
                [4 ]GRID grid.500071.3, ISNI 0000 0000 9114 1714, Senckenberg Deutsches Entomologisches Institut, ; Eberswalder Str. 90, 15374 Müncheberg, Germany
                [5 ]GRID grid.7492.8, ISNI 0000 0004 0492 3830, Department of Community Ecology, , Helmholtz Centre for Environmental Research - UFZ, ; Theodor-Lieser-Strasse 4, 06120 Halle, Germany
                [6 ]GRID grid.5522.0, ISNI 0000 0001 2162 9631, Institute of Environmental Sciences, , Jagiellonian University, ; Gronostajowa 7, 30-387 Kraków, Poland
                [7 ]GRID grid.7605.4, ISNI 0000 0001 2336 6580, Department of Life Sciences and Systems Biology, , Università degli Studi di Torino, ; Via Accademia Albertina 13, 10123 Torino, Italy
                [8 ]GRID grid.452330.3, ISNI 0000 0001 2230 9365, Croatian Natural History Museum, ; Demetrova 1, 10 000 Zagreb, Croatia
                [9 ]GRID grid.447761.7, ISNI 0000 0004 0396 9503, Institute of Entomology, Biology Centre CAS, ; Branisovska 31, Ceske Budejovice, Czech Republic
                [10 ]GRID grid.9647.c, ISNI 0000 0004 7669 9786, iDiv, German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, ; Deutscher Platz 5e, 04103 Leipzig, Germany
                [11 ]GRID grid.494924.6, UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, ; Wallingford, OX10 8BB UK
                Author information
                http://orcid.org/0000-0001-7129-4526
                http://orcid.org/0000-0003-2804-9626
                http://orcid.org/0000-0001-5272-3903
                http://orcid.org/0000-0002-5256-791X
                http://orcid.org/0000-0001-8779-2335
                http://orcid.org/0000-0002-8624-4983
                http://orcid.org/0000-0003-3064-7553
                http://orcid.org/0000-0003-1863-221X
                Article
                697
                10.1038/s41597-020-00697-7
                7567092
                33060594
                b02fb396-38e0-4b9e-95ff-d65778093050
                © The Author(s) 2020

                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/.

                The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.

                History
                : 14 May 2020
                : 14 September 2020
                Categories
                Data Descriptor
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                © The Author(s) 2020

                conservation biology,entomology,biodiversity
                conservation biology, entomology, biodiversity

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