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Ecology and Evolution
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Ecology and Evolution
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Ecology and Evolution
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DNA barcode analyses improve accuracy in fungal species distribution models

Authors: Javier Fernández‐López; M. Teresa Telleria; Margarita Dueñas; Tom May; María P. Martín;

DNA barcode analyses improve accuracy in fungal species distribution models

Abstract

AbstractSpecies distribution models based on environmental predictors are useful to explain a species geographic range. For many groups of organisms, including fungi, the increase in occurrence data sets has generalized their use. However, fungal species are not always easy to distinguish, and taxonomy of many groups is not completely settled. This study explores the effect of taxonomic uncertainty in databases used for modeling fungal distributions. We analyze distribution models for three morphospecies from the corticioid genus Xylodon (Hymenochaetales, Basidiomycota), comparing models based on species names on vouchers specimens with models derived from species identified by DNA barcode. Differences in the contribution of predictors driving the distribution of each modeled taxon and the extent of their ranges were studied. Records under Xylodon paradoxus, X. flaviporus, and X. raduloides were obtained from fungarium collections and GenBank repository. Two grouping criteria were used: (a) specimens were grouped by their collection or sequence voucher names and (b) specimens were grouped following molecular identification using ITS sequences through barcoding gap species recognition (BGSR). Climatic, geographic, and biotic variables were used to predict the potential distribution of each taxon through MaxEnt algorithm. From the three morphospecies selected according to voucher names, up to 19 species candidates were detected using BGSR. Climatic variables were the most important predictors in distribution models made from names on voucher specimens, but their importance decreased when BGSR was applied. In general, the extent of species distributions was more restricted for taxa under BGSR. Our results show that taxonomic uncertainty has a strong effect in Xylodon species distribution models. Misleading results can be obtained when cryptic species or identification errors mask the actual diversity of the presence records. Preserved specimens in natural history collections offer the possibility to assess whether the species name on labels matches the current species recognition criteria.

Keywords

Xylodon, Ecology, natural history collections, species recognition, species range, MaxEnt, ITS, QH540-549.5

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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