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LOTVS: A global collection of permanent vegetation plots
Author(s) -
Sperandii Marta Gaia,
de Bello Francesco,
Valencia Enrique,
Götzenberger Lars,
Bazzichetto Manuele,
Galland Thomas,
EVojtkó Anna,
Conti Luisa,
Adler Peter B.,
Buckley Hannah,
Danihelka Jiří,
Day Nicola J.,
Dengler Jürgen,
Eldridge David J.,
Estiarte Marc,
GarcíaGonzález Ricardo,
Garnier Eric,
GómezGarcía 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 MingHua,
Stock Martin,
Val James,
Vandvik Vigdis,
Wesche Karsten,
Wiser Susan K.,
Woodcock Ben A.,
Young Truman P.,
Yu FeiHai,
Wolf Amelia A.,
Zobel Martin,
Lepš Jan
Publication year - 2022
Publication title -
journal of vegetation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 115
eISSN - 1654-1103
pISSN - 1100-9233
DOI - 10.1111/jvs.13115
Subject(s) - vegetation (pathology) , ecological succession , ecology , plant community , sampling (signal processing) , biodiversity , geography , resource (disambiguation) , environmental science , environmental resource management , biology , medicine , computer network , filter (signal processing) , pathology , computer science , computer vision
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.