Why we still need permanent plots for vegetation science

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Prepared by Francesco de Bello, Enrique Valencia, David Ward & Lauren Hallett

A dedicated researcher (Jan Lepš, Šuspa, with the help of Tereza Dudíková) doing an annual sampling of species frequency in a species rich meadow, Ohrazení, south Bohemia (photo from 2008). The sampling is now running for more than 20 years with the same sampling approach, and by the same person, ensuring consistency in the data. At the same time, the researcher also recognizes that his taxonomical abilities to distinguish the more complicated species in the site, often only using vegetative parts, improved with time while his vision abilities worsened. Photo credit: Jana Macková née Karbulková.

Permanent-plot studies have been identified among the six most important tools in vegetation science. However, most field and experimental observations are conducted only over short periods, often due to funding limitations, except in some exceptional occasions (see the above photo of Jan Šuspa Lepš and his student). At the same time, environmental drivers work over long time periods, the response of vegetation could be delayed (see extinction debt; Helm et al., 2006) and that the effect of management may have long-term legacies (Spiegelberger et al., 2006). With some notable exceptions, field and experimental observations do not exceed a few decades, often overlapping with the career of a few dedicated researchers. However, permanent plots are essential to highlight the inherent non-linear variability in plant communities and how community composition and function respond to global change drivers.

To stress the importance of permanent-plot studies, and their different applications to answer a variety of ecological questions, we organized a collection of studies for a Special Feature in the Journal of Vegetation Science. The papers in this Special Feature (with open access for six months from their publication) cover a number of long-term studies that show how permanent plots can be essential to answering a broad variety of important ecological questions. To test a variety of long-standing ecological theories, some papers focus on the unique characteristics of individual sites (Brambila et al., 2020; Burge et al., 2020; Collins et al., 2020 Fisher et al., 2020; Herben et al., 2020) or intensive long-term experimental manipulations (Hédl and Chudomelová, 2020; Liu et al., 2020; Rychtecká and Lepš, 2020; Ward et al., 2020). Others combine long-term datasets to identify general patterns across biomes (Ward et al., 2020, Valencia et al. 2020). This collection of studies provides several answers to the original question raised by Bakker at al. (1996), in another Special Feature in JVS, of why do we need to invest time, effort and funding in permanent plots. It aims at demonstrating the need for special funding schemes not based on short-term funding cycles.

A schematic representation of the variation of permanent plot data and their use to answer questions related to temporal trends and components of ecological stability (including resistance and resilience after pulses, stress and exceptional weather conditions). The overall stability is the result of the interplay between variations in environmental conditions and biotic interactions. Notice that, in practice, permanent plots usually cover shorter time intervals than resurveys of historical plots. The schema is Fig. 1 from this study.

In our introductory paper to the Special Feature, we also highlight the important distinction between permanent plots and vegetation resurvey. Both approaches are very useful to assess medium- to long-term trends in vegetation (see the schema above). The possible downside of vegetation resurveys (well covered recently in a stimulating Special Feature on Vegetation Resurvey in the sister journal Applied Vegetation Science) is the potential risk of relocation and sampling biases since the specific location of the resurvey plot is not always exact. Permanent plots, contrastingly, are based on regular observation of the temporal dynamics of vegetation using sampling units with a clearly fixed location in time, while keeping the sampling approach consistent (as in the first photo of this post). As further discussed in this Special Feature, frequent and regular sampling using permanent plots also allows the assessment of non-linear species dynamics and community stability (see the schema above) in addition to longer-term trends.

The collection of studies presented in this Special Feature embodies the output of many hours of dedicated field sampling and shows different directions and potential applications in the use of long-term sampling schemes using permanent plots. Indeed, we still need many efforts in the near and far future to maintain existing sites and inspire more ecologists to invest their energies in these rewarding sampling approaches (see the schema above).

References:

  • Bakker, J.P., Willems, J.H., & Zobel, M. (1996). Long-term vegetation dynamics: Introduction. Journal of Vegetation Science, 7, 146. https://doi.org/10.1111/j.1654-1103.1996.tb01958.x
  • Brambila, A., Chesnut, J.W., Prugh, L.R., & Hallett, L.M. (2020) Herbivory enhances the effect of environmental variability on plant community composition and beta diversity. Journal of Vegetation Science, 31, 744–754. https://doi.org/10.1111/jvs.12862.
  • Burge, O.R., Bellingham, P.J., Arnst, E.A., Bonner, K. I., Burrown, L.W., Richardson, S., et al. (2020). Integrating permanent plot and palaeoecological data to determine subalpine post-fire succession, recovery and convergence over 128 years. Journal of Vegetation Science, 31, 755–767. https://doi.org/10.1111/jvs.12887
  • Fischer, F. M., Chytrý, K., Těšitel, J., Danihelka, J., & Chytrý, M. (2020). Weather fluctuations drive short-term dynamics and long‐term stability in plant communities: a 25-year study in a Central European dry grassland. Journal of Vegetation Science, 31, 711–721. https://doi.org/10.1111/jvs.12895
  • Hédl, R., & Chudomelová, M. (2020). Understanding the dynamics of forest understorey: Combination of monitoring and legacy data reveals patterns across temporal scales. Journal of Vegetation Science, 31, 733-743. https://doi.org/10.1111/jvs.12882
  • Helm, A., Hanski, I., & Pärtel, M. (2006). Slow response of plant species richness to habitat loss and fragmentation. Ecology Letters, 9, 72–77. https://doi.org/10.1111/jvs.12882/10.1111/j.1461-0248.2005.00841.x
  • Herben, T., Hadincová, V., Krahulec, F., Pecháčková, S., & Skálová, H. (2020). Which traits predict pairwise interactions in a mountain grassland. Journal of Vegetation Science, 31, 699–710. https://doi.org/10.1111/jvs.12872
  • Liu, D., Zhang C., Ogaya, O., Estiarte, M., & Peñuelas, J. (2020). Effects of decadal experimental drought and climate extremes on vegetation growth in Mediterranean forests and shrublands. Journal of Vegetation Science, 31, 768–779. https://doi.org/10.1111/jvs.12902
  • Rychtecká, T., & Lepš, J. (2020). Species traits are better determinants of mobility than management in a species rich meadow. Journal of Vegetation Science, 31, 686–698. https://doi.org/10.1111/jvs.12926
  • Spiegelberger, T., Hegg, O., Matthies, D., Hedlund, K., & Schaffner, U. (2006). Long term effects of short‐term perturbation in a subalpine grassland. Ecology, 87, 1939-1944. https://doi.org/10.1890/0012-9658(2006)87[1939:LEOSPI]2.0.CO;2
  • Valencia, E., de Bello, F., Lepš, J., Galland, T., E-Vojtkó, A., Conti, L., et al. (2020). Directional trends in species composition over time can lead to a widespread overemphasis of year-to-year asynchrony. Journal of Vegetation Science, 31, 792–802. https://doi.org/10.1111/jvs.12916
  • Ward, D., Kirkman, K.P., Tsvuura, Z., Morris, C.D., & Fynn, R.W.S. (2020). Are there common assembly rules for different grasslands? Comparisons of long-term data from a subtropical grassland with temperate grasslands. Journal of Vegetation Science, 31, 780–791, https://doi.org/10.1111/jvs.12906

This is a plain language summary for the paper of de Bello et al. published in the Journal of Vegetation Science (https://doi.org/10.1111/jvs.12928).