In the internal French Alps, subalpine grasslands become dominated by the tussock grass, Festuca paniculata, when mowing ceases. Does litter or living plants affect seedling recruitment in these subalpine communities, and does this vary between mown and unmown grasslands? Can the vegetation patterns observed in the field be related to the effects of F. paniculata? These hypotheses were tested using both a field and pot experiment. Seedlings of Bromus erectus, a subordinate species in these grasslands, were used as phytometers in both experiments. At both mown and unmown subalpine grassland sites in the French Alps, a removal experiment was established. This field experiment included removal of litter and living vegetation in order to differentiate their respective effect on seedling establishment. Vegetation and litter had contrasting effects. Vegetation affected the recruitment success of B. erectus by limiting seedling growth at the mown site and survival at the unmown site. Litter modified recruitment only at the unmown site, where it increased survival but limited growth. Survival and growth of seedlings responded to different environmental factors. Survival was determinedmore by soilmoisture, while growth probably dependedmore on light availability.Where there is a thick litter layer, as is the case in unmown subalpine grasslands, the competitive effect of vegetation can be counterbalanced by an increase in soil moisture due to the litter reducing rate of evaporation of water. The effect on seedlings of the presence of Festuca paniculata, the dominant species at these sites, was also quantified using a pot experiment, including a cutting treatment. This experiment showed that the competitive effect of the vegetation could be largely explained by the inhibitory effect on growth of the dominant species, F. paniculata. This study provides a better understanding of the processes that result in conservative plants, such as F. paniculata, becoming dominant in these subalpine environments upon cessation of traditional management practices.
Quantifying the functional diversity in ecological communities is very promising for both studying the response of diversity to environmental gradients and the effects of diversity on ecosystem functioning (i.e. in “biodiversity experiments”). In our view, the Rao coefficient is a good candidate for an efficient functional diversity index. It is, in fact, a generalization of the Simpson’s index of diversity and it can be used with various measures of dissimilarity between species (both those based on a single trait and those based on several traits). However, when intending to quantify the functional diversity, we have to make various methodological decisions such as how many and which traits to use, how to weight them, how to combine traits that are measured at different scales and how to quantify the species’ relative abundances in a community. Here we discuss these issues with examples from real plant communities and argue that diversity within a single trait is often the most ecologically relevant information. When using indices based on many traits, we plead for careful a priori selection of ecologically relevant traits, although other options are also feasible. When combining many traits, often with different scales, methods considering the extent of species overlap in trait space can be applied for both the qualitative and quantitative traits. Another possibility proposed here is to decompose the variability of a trait in a community according to the relative effect of among- and within-species differentiation (with the latter not considered by current indices of functional diversity), in a way analogical to decomposition of Sum of squares in ANOVA. Further, we show why the functional diversity is more tightly related to species diversity (measured by Simpson index) when biomass is used as a measure of population abundance, in comparison with frequency. Finally, the general expectation is that functional diversity can be a better predictor of ecosystem functioning than the number of species or the number of functional groups. However, we demonstrate that some of the expectations might be overrated – in particular, the “sampling effect“ in biodiversity experiments is not avoided when functional diversity is used as a predictor.