Opening the Pandora box of community ecology – The value of long-term data sets and collaborative research

Community ecologists study how communities of plants, animals and other organisms vary in space and time, how they interact and what controls these patterns. To do this they usually either observe (more or less) natural communities or conduct experimental manipulation in the field (in situ experiments) or in controlled conditions (mesocosms, microcosms). Observational studies of natural communities have the longest history and have contributed to major (and often controversial) theories in ecology such as the intermediate disturbance hypothesis (IDH). Starting with the more easily studies taxonomic groups such as vascular plants observational studies of natural communities have expanded to covering numerous taxonomic groups, including microbes and of course testate amoebae.

In order to describe the ecological preferences of species numerous plots need to be studied, typically in the range of 50-100 or more if possible. And even so, most studies end up with a fair number of rare species, which are found in few samples and are usually excluded from the data analyses. A further complication is that patterns observed at a single site (where many plots may be sampled) may be misleading and it is clearly preferable to study fewer plots in multiple sites to circumvent the problem of spatial autocorrelation (pseudo-replication within individual sites).

Studying numerous sites and ideally distant ones means that it is all but impossible to visit these sites on many occasions with the budget limitations most ecologists have to live with. Community ecologists therefore often collect their data and samples during a single visit. The timing of such field campaigns inevitably ends up being a compromise between ideal season and weather and the agenda of the various participants. The problem with this approach is that as many environmental factors vary over time -and this is clearly the case for soil pH, temperature, moisture content, water table depth, which are key ecological factors in terrestrial ecosystems – the available data will only represent a snapshot of what happens over the growing season or the year. This raises the questions: how representative is this snapshot of longer-term patterns? Are the relative values of the measured variables comparable among samples at different times?

As species may respond to environmental factors over more or less long-time periods patterns of community structure may not necessarily be best explained by one-time measurements of environmental variables but rather by more or less long-term averages or some measure of variability as done recently by Sullivan and Booth in a study of the relationship between the relative humidity of mosses and testate amoeba communities (Sullivan and Booth, 2011). The fact that some organisms are able to enter dormancy (e.g. encystment) during part of the year further complicated the story. However, only a small proportion of community ecology studies have addressed these longer-term patterns. This is of course understandable as the collection of long-term data at dozens of sites bears a cost that cannot be covered by classical funded research projects (i.e. typically 3 years) or regular budget of research groups (if they have any at all).

Community ecologists are usually taxonomically competent in one or two groups of organisms and therefore community ecology studies are typically limited to one of very few taxonomic groups. This makes it very difficult to assess how different communities respond to ecological gradients or perturbations as studies always differ in one aspect or another (e.g. slightly different methodologies used either to record the species data or the environmental variables). Yet sound comparative studies of multiple taxonomic groups would allow addressing important ecological questions such as how life history traits (e.g. dispersal potential, generation time) determine the responses of communities to ecological factors. This of course requires collaborative research efforts. And these are surprisingly rare!

A recent study published in the journal “Freshwater Biology” by Martin Jirousek and colleagues (Jiroušek et al., 2013) from the Czech Republic stands out by its focus on both long-term (15 years) environmental data and the comparative analysis of community patterns for four taxonomic groups, vascular plants, bryophytes, diatoms and (last but not least for this blog!) testate amoebae in 51 plots located in 12 Czech peat bogs in two mountain ranges.

Taxonomic groups included 1) short-lived microscopic organisms (diatoms and testate amoebae) and long-lived macroscopic organisms (vascular plants and bryophytes), 2) organisms dispersing easily (diatoms, testate amoebae and bryophytes) and less easily (vascular plants), and 3) photosynthetic (vascular plants, bryophytes, diatoms) and heterotrophic (testate amoebae – with a few mixotrophic exceptions) organisms.

The long-term ecological data also offered a unique opportunity to conduct a study on the effects of aerial liming (Ca, Mg), which has been used in the study area since the 1980’ as a forest amelioration practice (following damage caused by acid rain) and influenced the studied bogs. Such unintentional experiments can be highly valuable for ecologists, for example, as in this case to untangle ecological gradients that are usually strongly correlated (e.g. pH and calcium gradients in peatlands).

Martin Jirousek and colleagues hypothesised that long-term data would overall explain the community data better than short-term or one-time measurements and that this would be especially true for the longer-lived vascular plants and bryophytes. Following this they further hypothesised that the newly established pH and Calcium gradients would be better reflected in the shorter-lived communities of diatoms and testate amoebae. They compared the significance of environmental variables for different time spans: single time point, three, five, 10 and 15-year averages.

The results only partly supported the hypotheses. Micro and macro-organisms were correlated to both short- and long-term water chemistry variables (but not the same ones). Water table was correlated to all four communities but in agreement with the hypothesis, only the short-lived organisms reflected the recently established pH and Ca gradients. The results therefore generally support the idea that life-history traits condition the response of species communities to environmental gradients.

Although long-term ecological data sets such as the one used by Martin Jirousek and colleagues are not very common, they are perhaps not that rare. Ecologists would be well inspired to search for such data sets and if the monitoring program that generated them is still in place they should try to conduct similar studies (and encourage the monitoring program to continue!). Despite all technological advances we still can’t go back in time and therefore such data sets should be considered as a highly valuable asset. Although they involve some costs these can be very well justified if ecologists make good use of the data to address currently debated ecological questions such as the factors controlling community assembly and other questions related to metacommunity theory. This study also shows how valuable multi-taxa studies can be and hence how much added value there is to collaborative research!

Reference

Jiroušek, M., Poulíčková, A., Kintrová, K., Opravilová, V., Hájková, P., Rybníček, K., Kočí, M., Bergová, K., Hnilica, R., Mikulášková, E., Králová, Š. & Hájek, M. (2013) Long-term and contemporary environmental conditions as determinants of the species composition of bog organisms. Freshwater Biology, 58, 2196-2207.

Sullivan, M.E. & Booth, R.K. (2011) The Potential Influence of Short-term Environmental Variability on the Composition of Testate Amoeba Communities in Sphagnum Peatlands. Microbial Ecology, 62, 80-93.

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