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dc.contributor.authorMammola, Stefano
dc.contributor.authorPétillon, Julien
dc.contributor.authorHacala, Axel
dc.contributor.authorMonsimet, Jeremy
dc.contributor.authorMarti, Sapho-Lou
dc.contributor.authorCardoso, Pedro
dc.contributor.authorLafage, Denis
dc.date.accessioned2022-06-16T12:15:21Z
dc.date.available2022-06-16T12:15:21Z
dc.date.created2021-11-09T15:22:37Z
dc.date.issued2021
dc.identifier.citationDiversity and Distributions: A journal of biological invasions and biodiversity. 2021, .en_US
dc.identifier.issn1366-9516
dc.identifier.urihttps://hdl.handle.net/11250/2999069
dc.description.abstractAim: Species distribution models (SDMs) have emerged as essential tools in the equipment of many ecologists, useful to explore species distributions in space and time and answering an assortment of questions related to biogeography, climate change biology and conservation biology. Historically, most SDM research concentrated on well- known organisms, especially vertebrates. In recent years, these tools are becoming increasingly important for predicting the distribution of understudied invertebrate taxa. Here, we reviewed the literature published on main terrestrial arthropod predators (ants, ground beetles and spiders) to explore some of the challenges and opportunities of species distribution modelling in mega-diverse arthropod groups. Location: Global. Methods: Systematic mapping of the literature and bibliometric analysis. Results: Most SDM studies of animals to date have focused either on broad samples of vertebrates or on arthropod species that are charismatic (e.g., butterflies) or eco-nomically important (e.g., vectors of disease, crop pests and pollinators). We show that the use of SDMs to map the geography of terrestrial arthropod predators is a nascent phenomenon, with a near-exponential growth in the number of studies over the past ten years and still limited collaborative networks among researchers. There is a bias in studies towards charismatic species and geographical areas that hold lower levels of diversity but greater availability of data, such as Europe and North America. Conclusions: Arthropods pose particular modelling challenges that add to the ones already present for vertebrates, but they should also offer opportunities for future SDM research as data and new methods are made available. To overcome data limitations, we illustrate the potential of modern data sources and new modelling approaches. We discuss areas of research where SDMs may be combined with dispersal models and increasingly available phylogenetic and functional data to understand evolutionary changes in ranges and range- limiting traits over past and contemporary timescales.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectbibliometrics,en_US
dc.subjectclimate changeen_US
dc.subjectecological niche modelsen_US
dc.subjectMaxEnten_US
dc.subjectmechanistic modelsen_US
dc.subjectniche- based modelsen_US
dc.subjectpredicted distributionen_US
dc.subjectsocial network analysisen_US
dc.subjectstatistical modellingen_US
dc.titleChallenges and opportunities of species distribution modelling of terrestrial arthropod predatorsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400en_US
dc.source.pagenumber0en_US
dc.source.journalDiversity and Distributions: A journal of biological invasions and biodiversityen_US
dc.identifier.doi10.1111/ddi.13434
dc.identifier.cristin1952871
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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