LOTVS: A global collection of permanent vegetation plots

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.

Functional trait trade-offs define plant population stability across different biomes

“…We used 78 datasets contained in the LOTVS collection of temporal vegetation data. These consist of a total of 7396 permanent plots of natural and semi-natural vegetation that have been consistently sampled for periods of between six and 99 years, depending on the dataset (electronic supplementary material, table S2) [36,37]. These datasets were collected from study sites in different biomes that span the globe, in 18 different countries: Australia, China, Czech Republic, Estonia, France, Germany, Hungary, Kenya, Mongolia, Netherlands, New Zealand, Norway, Russia, South Africa, Spain, Switzerland, United Kingdom and USA.…”

“…Here, using an extended compilation of long-term, recurrently monitored vegetation plots, encompassing different habitat types around the world (https://lotvs.csic.es) [36], we determine which plant traits better predict the temporal stability of plant populations. We expect that populations of species with more acquisitive and higher dispersal-ability traits will tend to be more variable over time, while those of species with more conservative trait values and lower dispersal ability will tend to be more stable over time.…”

ReSurveyEurope: A database of resurveyed vegetation plots in Europe

“…ReSurveyEurope has established a number of cooperation agreements on data‐sharing and possible joint analyses with other initiatives. These include, in particular: forestREplot, a database of forest resurvey plots in temperate zones (Verheyen et al., 2017; https://forestreplot.ugent.be/), the Global Observation Research Initiative in Alpine Environments (GLORIA) network (Pauli et al., 2015; https://www.gloria.ac.at/home), and the Long‐term Vegetation Sampling (LOTVS; Sperandii et al., 2022; https://lotvs.csic.es/). Most European data sets from these global networks were integrated into ReSurveyEurope with the help of database managers and based on the consent of owners or providers of the individual original data sets.…”

Understanding the drivers of intraspecific demographic variation: Needs and opportunities

“…However, these databases currently include mainly species from cold, dry areas that are represented by few populations and do not span the climate and geographic ranges of the species. Beyond demographic data, modeling approaches that capitalize on more readily available abundance data, such as that found in LOTVS (Sperandii et al, 2022), may facilitate analyses of trait‐demographic relationships across species ranges (Laughlin et al, 2020). Chalmandrier et al (2021) calibrated trait‐demographic relationships using abundance data to address patterns of plant community structure across a temperature gradient.…”