Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: LOTVS : a global collection of permanent vegetation plots
Authors: Sperandii, Marta Gaia
de Bello, Francesco
Valencia, Enrique
Götzenberger, Lars
Bazzichetto, Manuele
Galland, Thomas
E‐Vojtkó, Anna
Conti, Luisa
Adler, Peter B.
Buckley, Hannah
Danihelka, Jiří
Day, Nicola J.
Dengler, Jürgen
Eldridge, David J.
Estiarte, Marc
García‐González, Ricardo
Garnier, Eric
Gómez‐García, Daniel
Hallett, Lauren
Harrison, Susan
Herben, Tomas
Ibáñez, Ricardo
Jentsch, Anke
Juergens, Norbert
Kertész, Miklós
Kimuyu, Duncan M.
Klumpp, Katja
Le Duc, Mike
Louault, Frédérique
Marrs, Rob H.
Ónodi, Gábor
Pakeman, Robin J.
Pärtel, Meelis
Peco, Begoña
Peñuelas, Josep
Rueda, Marta
Schmidt, Wolfgang
Schmiedel, Ute
Schuetz, Martin
Skalova, Hana
Šmilauer, Petr
Šmilauerová, Marie
Smit, Christian
Song, Ming‐Hua
Stock, Martin
Val, James
Vandvik, Vigdis
Wesche, Karsten
Wiser, Susan K.
Woodcock, Ben A.
Young, Truman P.
Yu, Fei‐Hai
Wolf, Amelia A.
Zobel, Martin
Lepš, Jan
et. al: No
DOI: 10.1111/jvs.13115
Published in: Journal of Vegetation Science
Volume(Issue): 33
Issue: 2
Page(s): e13115
Issue Date: 7-Mar-2022
Publisher / Ed. Institution: Wiley
ISSN: 1100-9233
Language: English
Subjects: Ecoinformatics; Ecological succession; Ecosystem stability; Global scale; Permanent plot; Plant community; Plant diversity; Temporal analysis; Time-series; Vegetation
Subject (DDC): 577: Ecology
580: Plants (Botany)
Abstract: Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Natural Resource Sciences (IUNR)
Appears in collections:Publikationen Life Sciences und Facility Management

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