JOURNAL ARTICLE
Areography, environmental heterogeneity and spatial models explain patterns of past and present diversity in Edraianthus (Campanulaceae).
Published In: Botanical Journal of the Linnean Society, 2023, v. 202, n. 2. P. 215 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Glasnović, Peter; Fišer, Živa; Jančič, Matic; Balant, Manica; Surina, Boštjan 3 of 3
Abstract
This article investigates the distribution patterns, species diversity, and environmental niche relationships of 17 taxa within the genus *Edraianthus* (Campanulaceae) in the Balkan Peninsula, focusing on current and Last Glacial Maximum (LGM) conditions through ecological niche modelling (ENM). The study identifies the central and southern Dinaric Alps as a key center of diversity and endemism, with species richness best explained by topographic factors (e.g., slope) and bioclimatic variables related to temperature and precipitation. ENM projections suggest that lowland and thermophilic taxa shifted their ranges southward during the Quaternary glaciations, while high-mountain taxa primarily shifted elevationally. Niche overlap analyses reveal greater similarity among phylogenetically close or ecologically similar taxa, whereas isolated or elevationally distinct species show less overlap, indicating that both allopatric and sympatric processes have contributed to diversification. The genetic diversity of the widespread taxon *E. graminifolius* correlates positively with local taxon richness, possibly reflecting past and ongoing hybridization and ecological specialization within this genus.
Additional Information
- Source:Botanical Journal of the Linnean Society. 2023/06, Vol. 202, Issue 2, p215
- Document Type:Article
- Subject Area:Geology
- Publication Date:2023
- ISSN:0024-4074
- DOI:10.1093/botlinnean/boac079
- Accession Number:163872400
- Copyright Statement:Copyright of Botanical Journal of the Linnean Society is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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