Smit, C. (Christian)

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    Directional trends in species composition over time can lead to a widespread overemphasis of year-to-year asynchrony
    (Wiley, 2020) E-Vojtkó, A. (Anna); Danihelka, J. (Jirí); Pakeman, R.J. (Robin J.); Peñuelas, J. (Josep); Young, T. (Truman P.); Partel, M. (Meelis); Kertész, M. (Miklós); Gotzenberger, L. (Lars); Schmiedel, U. (Ute); Conti, L. (Luisa); Val, J. (James); Garnier, E. (Eric); García-González, R. (Ricardo); Dengler, J. (Jürgen); Jentsch, A. (Anke); Woodcock, B.A. (Ben A.); Schuetz, M. (Martin); Yu, F.H. (Fei-Hai); Gómez, D. (Daniel); Smit, C. (Christian); Bello, F. (Francesco) de; Smilauer, P. (Petr); Wesche, K. (Karsten); Schmidt, W. (Wolfgang); Stock, M. (Martin); Eldridge, D.J. (David J.); Marrs, R.H. (Rob H.); Juergens, N. (Norbert); Klumpp, K. (Katja); Song, M.H. (Ming-Hua); Estiarte, M. (Marc); Harrison, S. (Susan); Smilauerová, M. (Marie); Louault, F. (Frédérique); Skalova, H. (Hana); Herben, T. (Tomas); Vandvik, V. (Vigdis); Galland, T. (Thomas); Ónodi, G. (Gábor); Zobel, M. (Martin); Ibáñez, R. (Ricardo); Valencia, E. (Enrique); Leps, J. (Jan); Rueda, M. (Marta); Peco, B. (Begoña)
    Questions: Compensatory dynamics are described as one of the main mechanisms that increase community stability, e.g., where decreases of some species on a yearto-year basis are offset by an increase in others. Deviations from perfect synchrony between species (asynchrony) have therefore been advocated as an important mechanism underlying biodiversity effects on stability. However, it is unclear to what extent existing measures of synchrony actually capture the signal of year-to-year species fluctuations in the presence of long-term directional trends in both species abundance and composition (species directional trends hereafter). Such directional trends may lead to a misinterpretation of indices commonly used to reflect year-toyear synchrony. Methods: An approach based on three-term local quadrat variance (T3) which assesses population variability in a three-year moving window, was used to overcome species directional trend effects. This “detrending” approach was applied to common indices of synchrony across a worldwide collection of 77 temporal plant community datasets comprising almost 7,800 individual plots sampled for at least six years. Plots included were either maintained under constant “control” conditions over time or were subjected to different management or disturbance treatments. Results: Accounting for directional trends increased the detection of year-to-year synchronous patterns in all synchrony indices considered. Specifically, synchrony values increased significantly in ~40% of the datasets with the T3 detrending approach while in ~10% synchrony decreased. For the 38 studies with both control and manipulated conditions, the increase in synchrony values was stronger for longer time series, particularly following experimental manipulation. Conclusions: Species’ long-term directional trends can affect synchrony and stability measures potentially masking the ecological mechanism causing year-to-year fluctuations. As such, previous studies on community stability might have overemphasised the role of compensatory dynamics in real-world ecosystems, and particularly in manipulative conditions, when not considering the possible overriding effects of long-term directional trends.
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    LOTVS: a global collection of permanent vegetation plots
    (2022) E-Vojtkó, A. (Anna); Danihelka, J. (Jirí); Buckley, H. (Hannah); Pakeman, R.J. (Robin J.); Peñuelas, J. (Josep); Young, T. (Truman P.); Partel, M. (Meelis); Kertész, M. (Miklós); Gotzenberger, L. (Lars); Schmiedel, U. (Ute); Gómez-García, D. (Daniel); Conti, L. (Luisa); Val, J. (James); Garnier, E. (Eric); García-González, R. (Ricardo); Wiser, S.K. (Susan K.); Dengler, J. (Jürgen); Jentsch, A. (Anke); Woodcock, B.A. (Ben A.); Schuetz, M. (Martin); Ibañez-Gaston, R. (Ricardo); Yu, F.H. (Fei-Hai); Smit, C. (Christian); Adler, P.B. (Peter B.); Bello, F. (Francesco) de; Smilauer, P. (Petr); Wesche, K. (Karsten); Schmidt, W. (Wolfgang); Stock, M. (Martin); Hallett, L. (Lauren); Sperandii, M.G. (Marta Gaia); Eldridge, D.J. (David J.); Marrs, R.H. (Rob H.); Juergens, N. (Norbert); Wolf, A.A. (Amelia A.); Day, N.J. (Nicola J.); Klumpp, K. (Katja); Song, M.H. (Ming-Hua); Le-Duc, M. (Mike); Estiarte, M. (Marc); Harrison, S. (Susan); Smilauerová, M. (Marie); Louault, F. (Frédérique); Skalova, H. (Hana); Herben, T. (Tomas); Vandvik, V. (Vigdis); Galland, T. (Thomas); Ónodi, G. (Gábor); Bazzichetto, M. (Manuele); Zobel, M. (Martin); Kimuyu, D.M. (Duncan M.); Valencia, E. (Enrique); Leps, J. (Jan); Rueda, M. (Marta); Peco, B. (Begoña)
    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.