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Publications Files/2020 Platania Et at Biodecrypt.Pdf Received: 10 April 2020 | Revised: 27 May 2020 | Accepted: 12 June 2020 DOI: 10.1111/geb.13154 MACROECOLOGICAL METHODS Assigning occurrence data to cryptic taxa improves climatic niche assessments: Biodecrypt, a new tool tested on European butterflies Leonardo Platania1 | Mattia Menchetti2 | Vlad Dincă3 | Cecília Corbella1 | Isaac Kay-Lavelle1 | Roger Vila1 | Martin Wiemers4,5 | Oliver Schweiger5 | Leonardo Dapporto2 1Institut de Biologia Evolutiva (CSIC - Universitat Pompeu Fabra), Barcelona, Spain Abstract 2ZEN Lab, Dipartimento di Biologia, dell' Aim: Occurrence data are fundamental to macroecology, but accuracy is often compro- Università di Firenze, Sesto Fiorentino, Italy mised when multiple units are lumped together (e.g., in recently separated cryptic species or 3Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland in citizen science records). Using amalgamated data leads to inaccuracy in species mapping, 4Senckenberg Deutsches Entomologisches to biased beta-diversity assessments and to potentially erroneously predicted responses to Institut, Müncheberg, Germany climate change. We provide a set of R functions (biodecrypt) to objectively attribute uni- 5Department of Community Ecology, dentified occurrences to the most probable taxon based on a subset of identified records. Helmholtz Centre for Environmental Research - UFZ, Halle, Germany Innovation: Biodecrypt assumes that unidentified occurrences can only be attributed at certain distances from areas of sympatry. The function draws concave hulls based Correspondence Leonardo Dapporto, ZEN Lab, Dipartimento on the subset of identified records; subsequently, based on hull geometry, it attributes di Biologia dell’Università di Firenze, (or not) unidientified records to a given taxon. Concavity can be imposed with an alpha via Madonna del Piano 6 50019, Sesto Fiorentino, Italy. value and sea or land areas can be excluded. A cross-validation function tests attribution Email: [email protected] reliability and another function optimises the parameters (alpha, buffer, distance ratio Funding information between hulls). We applied the procedure to 16 European butterfly complexes recently European Regional Development Fund and separated into 33 cryptic species for which most records were amalgamated. We com- Ministerio de Economía y Competitividad, Grant/Award Number: CGL2016-76322-P pared niche similarity and divergence between cryptic taxa, and re-calculated and con- and PID2019-107078GB-I00; Academy of tributed updated climatic niche characteristics of the butterflies in Europe (CLIMBER). Finland, Grant/Award Number: 328895 Main conclusions: Biodecrypt showed a cross-validated correct attribution of known Editor: Ardnt Hampe records always ≥ 98% and attributed more than 80% of unidientified records to the [Correction added on 04 September 2020, after first online publication: Mattia most likely taxon in parapatric species. The functions determined where records can Menchetti contributed equally to this study be assigned even for largely sympatric species, and highlighted areas where further and therefore has been added as a co-first author.] sampling is required. All the cryptic taxa showed significantly diverging climatic niches, reflected in different values of mean temperature and precipitation compared to the values originally provided in the CLIMBER database. The substantial fraction of cryptic taxa existing across different taxonomic groups and their divergence in climatic niches highlight the importance of using reliably assigned occurrence data in macroecology. KEYWORDS biodecrypt, climatic niches, CLIMBER variables, cryptic taxa, European butterflies, occurrence data Leonardo Platania and Mattia Menchetti contributed equally to this study. 1852 | © 2020 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/geb Global Ecol Biogeogr. 2020;29:1852–1865. PLATANIA ET al. | 1853 1 | INTRODUCTION among two or more newly recognised entities, based on a subset of ascertained records and on justifiable geographic rules. We applied A solid record of species occurrence data is key to understanding the this procedure to the cryptic butterfly species of Europe recently multiple factors defining their large-scale geographic distributions separated into different taxa (Wiemers et al., 2018) that were amal- and, by means of ecological niche modelling, to assess and project gamated in the Distribution Atlas of Butterflies in Europe (Kudrna their responses to changing environmental conditions in terms of et al., 2011; Kudrna, Pennerstorfer, & Lux, 2015). This atlas, of which range expansion or contraction (Franklin, 2010; Hortal et al., 2015; several editions have been published, represents the most compre- Schweiger et al., 2012; Thuiller et al., 2016). In addition, resulting hensive source of occurrence data for European butterflies, and the species-specific niche characteristics have provided conservation data from the 2011 edition were used to calculate the widely used biogeography with a powerful set of species features, such as mea- CLIMBER variables describing species ranges and their climatic pref- sures of mean and variation in multiple climatic characteristics (e.g., erences over Europe (Schweiger et al., 2014). the variables describing the climatic niche characteristics of the We provide six new R functions, added to the recluster R pack- butterflies in Europe (CLIMBER); Schweiger, Harpke, Wiemers, & age (Dapporto et al., 2013), for parameter optimisation, record at- Settele, 2014), useful for assessing community-wide responses to tribution to potential cryptic taxa and for testing the reliability of global change (Devictor et al., 2012; Herrando et al., 2019; Zografou the procedure. Finally, we provide new CLIMBER variables for the et al., 2014). species included in this study and show that cryptic taxa differ sub- Generating reliable species occurrence data at continental scale stantially in their climatic niches. requires an enormous effort and such databases have been assem- bled over decades of field research, often based on, or improved by, citizen science projects (Dennis, Morgan, Brereton, Roy, & Fox, 2017; 2 | METHODS Titeux et al., 2017). In addition, proper definition and discrimination of species are necessary for reliable niche modelling, as well as for 2.1 | The algorithm the identification of environmental preferences of species and the derived specific indices. However, the existence of a considerable The objective of the algorithm is to reliably attribute species mem- fraction of cryptic species in almost all groups of living organisms bership to a set of ambiguous records belonging to two (or more) (Bickford et al., 2007) poses a serious challenge to our understand- cryptic species based on the distribution of a subset of accurately ing of diversity in general, and to this line of research in particular. determined records. The main idea is that records from an area When a taxon believed to represent a single species is recognised as where only one taxon occurs can be attributed with confidence, two or multiple cryptic species, the occurrence data accumulated for while records from the areas of sympatry or too far from any as- decades suddenly become obsolete. Researchers often amalgamate certained record cannot be reliably attributed. For this purpose, we the occurrence data for cryptic taxa, but this approach ignores a sub- developed a series of R (R Core Team, 2019) functions added to the stantial fraction of diversity in terms of species identity, distribution, recluster R package (biodecrypt, biodecrypt.view, biodecrypt.cross, evolution, and its potential dynamics in changing environments. biodecrypt.wrap, biodecrypt.optimise, plot.biodecrypt). The main Most complexes of cryptic taxa are parapatric with minimal inputs for the functions are a matrix with longitude and latitude for areas of sympatry, frequently because they evolved in allopatry all the occurrence data and a vector (in the same order) providing and the achievement of secondary sympatry is delayed by (a) lim- their identification. The records identified to species-level (identified ited dispersal and competition due to a still incomplete separation records) must be indicated in the vector with a sequential numeric of ecological niches or by (b) reproductive interference due to the value (1, 2, …, n), which represents the verified membership to the nth lack of a pre-mating barrier (Pigot & Tobias, 2013, 2015; Vodă, species. The occurrence data with unknown identification (unidenti- Dapporto, Dincă, & Vila, 2015). Only a minor fraction of cryptic fied records) are marked with a 0 (Figure 1). Based on this vector taxa are largely sympatric and these typically show strong repro- and on the geographic coordinates of identified records, biodecrypt ductive barriers (Dincă, Lukhtanov, Talavera, & Vila, 2011; Dincă builds hulls of distribution for each species. In a highly simplified et al., 2013). Because cryptic species tend to show parapatric hypothesis, the distribution of a species can be approximated by a distributions (Dapporto et al., 2017; Scalercio et al., 2020; Vodă convex hull among the geographic coordinates of identified records. et al., 2015; Waters, 2011), they encompass a conspicuous fraction Nevertheless, areas of distribution can be largely concave, mostly in of beta diversity (Vodă et al., 2015) and, since they inhabit differ- geomorphologically highly heterogeneous regions. This is the case ent areas, are expected to be adapted to different climates
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