Why we<i>still</i>need permanent plots for vegetation science

Abstract

The use of permanent plots has a long tradition in ecology (Callahan, 1984; Wildi and Schültz, 2000; Lindenmayer et al., 2012; Hughes et al., 2017) and vegetation science (Bakker et al., 1996a). Recently, permanent-plot studies were considered among the six most important developments in vegetation science (Chytrý et al., 2019). As the present Special Feature demonstrates, the value of permanent plots is becoming ever more evident as a growing number of available time series highlights the variability inherent in plant communities and the non-linear ways in which community composition and function respond to global change. In a previous Special Feature in Journal of Vegetation Science edited by Bakker et al. (1996a), different contributors showed the importance of permanent plots in understanding the mechanisms underlying vegetation changes, particularly following succession. Bakker et al. (1996a) used the term ‘permanent plots’ broadly to ‘include studies in which a series of randomly located plots or transects have been described at certain time intervals within a fixed area’. Such permanent plots are thus based on regular observation of the temporal dynamics of vegetation using sampling units with a fixed location in time, while the sampling approach is kept consistent. A similar approach is the resurvey of vegetation plots. The topic of vegetation resurvey was well covered recently in a stimulating Special Feature in the sister journal Applied Vegetation Science (Hédl et al., 2017). In this approach, historical vegetation plots (usually older than two decades) are resampled using the same or similar sampling method, though not always using the same exact geographical location (Alstad et al., 2016). Vegetation resurveys are often conducted when contemporary researchers wish to capture trends in vegetation response to environmental changes — such as climate change — that the original researchers did not anticipate (Harrison et al., 2010). These opportunistic studies aim to make the best use of existing data and allow earlier observations than many permanent-plot studies, but a downside of this approach is the potential risk of relocation and sampling biases (Kapfer et al., 2017). The distinction between permanent plots and semi-permanent (or quasi-permanent) plots used in the vegetation resurvey approach is often not definite, and both approaches can be very useful to assess medium- to long-term trends in vegetation (Figure 1). At the same time, as further discussed in this Special Feature, frequent and regular sampling using permanent plots allows the assessment of species dynamics and community stability (Figure 1 and this Special Feature) in addition to longer-term trends. Within permanent plots, we can further differentiate between observational plots and experimental plots, where natural or semi-natural vegetation is sampled after the application of experimental treatments in the latter. The difference between these types of plots is that experimental set-ups are affected by both experimental treatments and natural variability. Establishing and, when needed, maintaining the treatments can require additional effort. Sampling with a long-term view takes effort. As summarized by Bakker et al. (1996a) ‘it needs a great deal of discipline to maintain a series of permanent plots and analyse them yearly over a period long enough to answer relevant (ecological) questions’. The commitment of individual researchers to permanent-plot sampling have significantly advanced the field of ecology. For example, permanent-plot studies spearheaded by a few individuals have elucidated the cyclical nature of population dynamics (The Portal Project; Morgan Ernest et al., 2016), and the role of disturbance for diversity (Jasper Ridge; Hobbs et al., 2007). Such discipline, however essential, is likely not the only trait required of researchers who successfully undertake the challenge of establishing and maintaining permanent plots for many years. Researchers also need to be able to secure support from institutions, either academic or governmental, including continuous funding, special agreement with landowners, security at the sampling sites and safe and stable data storage. Institutional support is likely a major bottleneck, particularly in the context of predominantly short-term scientific support from most existing grant agencies. Because of this, most field observations and experiments are conducted only over short periods, despite the fact that environmental drivers work over long time periods, the response of vegetation could be delayed in time (see extinction debt; Helm et al., 2006) and that the effect of management may have long-term legacies (e.g., short-term fertilization effects detectable after 70 years; Spiegelberger et al., 2006). With some notable exceptions (e.g., Crawley et al., 2005; Silvertown et al., 2006), many permanent-plot sampling schemes do not exceed a few decades, often overlapping with the career of a few dedicated researchers. Developing funding mechanisms to support the long-term work of individual research teams provides the missing support needed. A limited number of national and international initiatives have successfully launched and maintained permanent vegetation monitoring schemes worldwide, particularly using forest and grassland plots. For example, the Center for Tropical Forest Science established a global network of forest inventory plots in the 1980s (Anderson-Teixeira et al., 2015). Currently, together with standardized sampling and data storage (Condit et al., 2014), this evolved into the ForestGEO initiative (https://forestgeo.si.edu/what-forestgeo). Similar initiatives include, for example, the Chinese Forest Biodiversity Monitoring Network (http://www.cfbiodiv.org/; De Cáceres et al., 2012), the Brazilian Biodiversity Research Program (Magnusson et al., 2018), the Spanish Forest Inventory (Ruiz-Benito et al., 2013) or New Zealand's Land Use and Carbon Analysis System (Holdaway et al., 2017). In 1980, the US National Science Foundation established the Long-term Ecological Research (LTER) program, which supports a network of 28 sites to offer a long-term view on ecological dynamics. Today, research programmes at multiple LTER sites (including in other regions of the world), provide open-access ecological data to answer a number of pressing ecological questions across taxa. Other national initiatives, such as the Biodiversity Exploratories (BE), a German Science Foundation-funded project, maintain a very exhaustive standardized sampling of plots along a land-use intensity gradient in different regions. Similarly, the Environmental Change Network (ECN) focuses on monitoring, data and research to understand environmental change in the United Kingdom. Some initiatives have established a common sampling scheme to follow trends in composition and diversity in specific ecosystems, such as mountain summits (e.g., Pauli et al., 2012) or tundra (Elmendorf et al., 2012), although these sites are not always sampled on an annual basis. Establishing comparable sampling schemes in different regions and habitats represents an ideal solution to develop robust monitoring schemes. However, this clearly requires a highly coordinated effort, with common and stable funds, which unfortunately is still often unrealistic. Moreover, there is a balance between standardized, comparable designs across systems and long-term experiments tailored to test key purported dynamics of an individual system, with their specificities. Initiatives such as the ones mentioned above are restricted either to a few countries or to particular habitats and organisms. However, a number of ‘grassroot’ initiatives (Aubin et al., 2020) have developed worldwide to implement distributed, replicated permanent-plot experiments (e.g., the global Nutrient Network, NutNet, https://nutnet.org/, Borer et al., 2014, or DroughtNet, https://drought-net.colostate.edu/). At the same time, synthesis efforts have developed to compile permanent-plot data, irrespective of specific sampling methods, across individual studies for cross-site comparisons. For example, BioTIME (Dornelas et al., 2018) is an impressive initiative that collects data from existing long-term sampling schemes for different organisms from independent sources for a minimum of two years, although not necessarily consecutively. This type of data, despite the sampling differences, can be effective to assess large-scale trends in biodiversity (Dornelas et al., 2014; Blowes et al., 2019). A particularly interesting example of independent efforts to monitor biodiversity in time is the Park Grass Experiment (e.g., Crawley et al., 2005; Silvertown et al., 2006). The Park Grass Experiment, begun in 1856, is likely the oldest ongoing ecological experiment. Its value to science has changed and grown since it was established to test primarily agricultural questions. Particularly in recent years, the interest in the original experiment has transcended its initial aim and facilitated tests of questions related to the mechanisms governing the relationship between biodiversity and productivity and the response of plant communities to atmospheric nutrient deposition (Storkey et al., 2016). Hence, the Park Grass initiative illustrates how long-term experiments grow in value with time and how they may be used to investigate scientific questions that were inconceivable at their inception. The papers in this Special Feature cover a number of long-term studies that show how permanent plots can be essential to answering a number of important ecological questions. Some papers focus on the unique characteristics of individual sites (Brambila et al., 2020; Burge et al., 2020; Collins et al., 2020; Fischer 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) to test long-standing ecological theories. Others combine long-term data sets to identify general patterns across biomes, e.g., Ward et al. (2020), or Valencia et al. (2020, with the LOng-Term Vegetation Sampling, LOTVS). The pressing threat from multiple global change drivers and the need to follow their consequences in different regions and habitats worldwide call for coordinated efforts using repeated monitoring tools such as permanent plots (Borer et al., 2014). For this reason, we think it is important to answer the question: why do we still need to invest time, effort and funding in permanent plots? Following Bakker et al. (1996b), this Special Feature is an attempt to provide answers to this question and illustrate the need for special funding schemes beyond conventional ones that are based on short-term funding cycles. The title of this section is inspired by Herben's contribution (1996) in the Special Feature edited by Bakker et al. (1996a). Here we explore different ways in which permanent plots can be employed as a tool to answer a variety of pressing ecological questions. We can broadly classify these questions into two very general, and interrelated, groups: (a) mechanisms causing and maintaining biodiversity; and (b) long-term vegetation dynamics under historical as well as novel environmental drivers and their consequences for ecosystem functions. We illustrate some key examples from the literature for both of these questions and their interactions. We then show how the collection of studies in this Special Feature advances our understanding of both sets of questions and provides perspectives for future ecological research. Assessing the spatial and temporal scales of species turnover in permanent plots has been repeatedly identified as key to understanding the mechanisms maintaining species diversity (Herben, 1996). In 1993, van der Maarel and Sykes (1993) formulated the so-called ‘carousel model’ based on some earlier ideas by Herben et al. (1993), i.e., high temporal mobility of species in relatively homogeneous habitat conditions supporting a temporal turnaround of species as a mechanism of maintenance of biodiversity. This finding is consistent with the studies of Sale (1978) and Chesson and Warner (1981) on lottery systems in high-diversity coral reefs, with a rapid turnover with little or no niche differentiation. They are also consistent with the findings of negative plant–soil feedbacks (Chung et al., 2019). More recent studies (Rychtecká and Lepš, 2020, this issue) have shown a pronounced difference in mobility among species, from typical stable ‘sitters’ to more mobile ‘travellers’, in species-diverse wet-meadow communities. The results of Rychtecká and Lepš can also be interpreted in terms of species traits, which are becoming an essential tool for ecologists (Pillay and Ward, 2014; Giarrizzo et al., 2017). Also, they reported greater mobility for species with more ‘acquisitive’ strategies (high specific leaf are [SLA], high nitrogen leaf content) and species with well-developed clonal organs of lateral spread. Interestingly, in the same communities, species also differentiated into different types of temporal fluctuation (with more or less stable populations in time; Májeková et al., 2014), although such differentiation was not correlated with differences in species’ spatial stability. These types of studies using data from permanent plots provide an exciting venue to understand how the complex interaction between spatial and temporal fluctuations can allow for regeneration niches of different species, and how local diversity is maintained. Permanent plots can be further used to directly extract essential and unique information about species interactions (Damgaard et al., 2009; Adler et al., 2012; Tredennick et al., 2017; Garnier et al., 2018; Herben et al., 2019). This makes possible the separation of mechanistic/deterministic components of community dynamics from environmental and demographic stochasticity, as well as parameterizing a mechanistic model of community functioning that can be used for further predictions under different scenarios (Adler et al., 2012; Tredennick et al., 2017). In another study in this Special Feature, located in a mountain meadow, spatially explicit ramet counts of 20 coexisting species were collected (very patiently) at a scale of 3 cm × 3 cm grid cells (Herben et al., 2020, this issue). Bayesian models showed large variation in pairwise species competition coefficients behind species’ temporal and spatial fluctuations. By considering species traits in combination with spatial and temporal fluctuations, it was possible to provide a novel insight into species coexistence. While competition was generally found to be size-asymmetrical, with bigger species over-competing smaller ones, trait differences contributed to within-community niche differentiation. This was likely done by reducing competition between co-occurring grassland species, with a potential role in species coexistence. While these studies demonstrate high species mobility at very fine spatial scales, at spatial scales bigger we often in This was by both van der Maarel and Sykes (1993) and Herben et al. (1993), as also by et al. In this Fischer et al. dynamics within plots in a grassland with plant to patterns over the previous two years. These community changes were found to be and contributed to the stability of this which has changed little over the years, with the of van der Maarel and Sykes In the of species with different to environmental conditions within a community is a key mechanism temporal stability of communities, i.e., dynamics — also and Valencia et al. (2020, this issue). Fischer et al. that of to ongoing climate change could in such long-term stability and a such as an number of species and their population monitoring of these permanent plots make it possible to test this environmental changes can trends in species respond to environmental changes (e.g., a series of with of individuals on short time scales, by a of species’ at time scales, and by species turnover and local extinction the in changes in vegetation for example extinction et al., Helm et al., 2006), such turnover and changes can to Collins et al. (2020, this using located transects across different community showed community and composition changes following and disturbance by in their They provide a unique on the of vegetation changes, which be to by using short-term research. or less frequent sampling clearly to the complex of and disturbance disturbance and under a the variation could be as by van der Maarel and Sykes (1993) and shown by and (2020, this issue) in an The turnover by monitoring in permanent plots was than the long-term changes by a resurvey of semi-permanent plots, which showed temporal to the management at the time of the was by a long-term biodiversity to et al., and also show variation the of changes, the sampling as a of The monitoring designs clearly need to into temporal scales when vegetation dynamics. for example by can both and biodiversity et al., although often these effects are over short temporal scales and on local biodiversity only can further or the effect of environmental variation on diversity At the in a of and with high a highly In this et al. (2020, this issue) found that the effect of was highly In under years, and diversity to from but at other the effect of was relatively In with the results of Collins et al. and and (2020, both in this the findings of et al. that the of species fluctuations in response to disturbance be by annual is thus possible that the importance of disturbance could be in short-term studies that did not assess effects within the context of longer-term climate variability. The study of which the special of Bakker et al. (1996a), has advanced to the repeated sampling of permanent vegetation plots over it is often to the of has or a Moreover, and in communities — that when they more similar with time — environmental conditions are similar et al., However, is less likely there is high in the species composition of initial or where the is highly In such is more likely than et al., to the general of historical long-term sampling more than a few decades, Burge et al. (2020, this issue) show that long-term permanent plots, together with and from within these permanent plots, have the potential to the assessment of vegetation dynamics and to and ecosystem in the of environmental and Burge et al. thus a historical of data collection to of the studies of in the after a in to They showed that vegetation changes are still although they are to approach a However, both and are not that after a long time, the is to These in the of different scenarios of changes, and changes in could to the of vegetation and habitat context can also the response of vegetation to conditions and of These effects can on plant communities, in terms of plant and productivity et al., et al., an experimental approach on natural communities, Liu et al. (2020, this issue) the of long-term experimental on They found that habitat context climate and affected the of climate with effects of experimental and years. a understanding of the effect of climate change on vegetation can be possible only by dedicated sampling repeated over Research that conducted by Liu et al. is to explore the changes of multiple under long-term and to to and implement strategies for the maintenance of ecosystem biodiversity and functioning under climate change. long-term experiments the Park Grass (see or the Experiment et al., et al., 2020) are is the to the of using comparable across different regions of the Ward et al. (2020, this issue) of comparable experimental designs to test vegetation response to and fertilization in a grassland was consistent with results from the in the Park Grass Experiment and which is another LTER et al., some relatively differences, the reported consistent vegetation across of different conditions and different species which for of common Similar long-term such as the Nutrient Network grassland experiments (Borer et al., 2014), which over sites across different be employed for the of ecological predictions over the effect of use and With the of and comparable initiatives to assess the temporal dynamics of vegetation across different regions of the as mentioned it is still possible to and analyse data collected from individual a a global collection of temporal with individual plots sampled over at six years, Valencia et al. (2020, this issue) drivers of temporal vegetation stability to trends and fluctuations. By using a novel et al., they analyse common of species’ temporal to understand mechanisms between species As by Fischer et al. and Herben et al. (2020, both in this different species’ fluctuations in time could from either different to environmental fluctuations or from changes in between species is to to community stability based on fluctuations. However, a generally is that can also the effect of long-term trends (e.g., Collins et al., 2020; and Chudomelová, 2020; Liu et al., 2020, this which effects in their of (see also Ward et al., 2020, this where the purported also changed over the 70 of their Valencia et al. showed the importance of particularly following long-term environmental which be from changes to environmental fluctuations. that most studies on dynamics are done under often earlier studies on plant community stability have the role of dynamics in In the to Fischer et al. and Valencia et al. both this issue) it thus be important to the effect of fluctuations to trends in vegetation from the effect of fluctuations. A number of and ecologists have the need to and maintain long-term research sites in different types of natural and semi-natural to answer a of pressing ecological and also provide data to answer questions that were not at the time of existing are under the of LTER sites worldwide, in data often available within such as et al., or the Environmental these initiatives, particularly by both academic and institutions, essential to answer both and ecological questions in to different the potential for across studies, common initiatives with comparable sampling schemes can be The collection of studies in this Special Feature the of many of dedicated field sampling and different and potential in the use of long-term sampling schemes using permanent plots. we still need many efforts in the and future to maintain existing sites and more ecologists to invest their in these sampling We who contributed to this Special Feature and of efforts to permanent plots the different contributors to this Special Feature we to particularly Lepš, Liu and for the very on this and its which is the of this effort.

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