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2020-12-30

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cc-by (c) Jiménez-Alfaro, Borja et al., 2020
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/173346

SIVIM Alpine - Database of high-mountain grasslands in the Iberian Peninsula

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https://doi.org/10.3897/VCS/2020/62232

Abstract

SIVIM Alpine (GIVD ID: EU-00-034) is a thematic database focused on vegetation plots from alpine grasslands of the Iberian Peninsula. The main aim of the database is to centralize historical and new vegetation plots of grassland-like communities above the treeline from Spanish mountains, the Pyrenees (including France and Andorra) and Serra da Estrela (Portugal). The database was registered in GIVD in December 2020, and it is currently available in EVA under semi-restricted regime. SIVIM Alpine includes both digitized relevés from the literature and unpublished data. Most of digitized relevés overlap with SIVIM (GIVD ID EU-00-004) but the header data and the geographical coordinates of SIVIM Alpine have been improved when possible. The database is routinely updated with new surveys conducted with GPS and detailed ecological data. Nowadays, SIVIM Alpine contains 6,420 vegetation plots corresponding to all phytosociological alliances described in the Iberian Peninsula for high-mountain grassland vegetation, 85% of them also classified at the association level. Plot size is available for 80% of the relevés. Plant taxonomy keeps the names provided by the original authors of the relevés, with an additional correspondence to Euro+Med and The Plant List, when possible. The database is continuously updated by revisiting the original sources. Different versions of the database have been used to vegetation analysis at national at continental scales.

Subject

Praderies, Península Ibèrica

Subject (English)

Prairies, Iberian Peninsula

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Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)

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JIMÉNEZ-ALFARO, Borja and FONT I CASTELL, Xavier. SIVIM Alpine - Database of high-mountain grasslands in the Iberian Peninsula. Vegetation Classification and Survey. 2020. Vol. 1, num. 219-220. ISSN 2683-0671. [consulted: 7 of August of 2026]. Available at: https://hdl.handle.net/2445/173346

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