This book is primarily written for ecologists needing to analyse data resulting from field observations and experiments. It will be particularly useful for students and researchers dealing with complex ecological problems, such as the variation of biotic communities with environmental conditions or the response of biotic communities to experimental manipulation. Following a simple introduction to ordination methods, the text focuses on constrained ordination methods (RDA, CCA) and the use of permutation tests on statistical hypotheses of multivariate data. An overview of classification methods, or modern regression methods (GLM, GAM, loess), is provided and guidance on the correct interpretation of ordination diagrams is given. Seven case studies of varying difficulty help to illustrate the suggested analytical methods, using the Canoco for Windows software. The case studies utilise both the descriptive and manipulative approaches, and they are supported by data sets and project files available from the book website.

In this paper we reflect on a number of aspects of ordination methods: how should absences be treated in ordination and how do model-based methods, including Gaussian ordination and methods using generalized linear models, relate to the usual least-squares (eigenvector) methods based on (log-)transformed data. We defend detrended correspondence analysis by theoretical arguments and by reanalysing data that previously gave bad results. We show by examples that constrained ordination can yield more informative views on effects of interest compared to unconstrained ordination (where such effects can be invisible) and show how constrained axes can be interpreted. Constrained ordination uses an ANOVA/regression approach to enable the user to focus on particular aspects of species community data, in particular the effects of qualitative and quantitative environmental variables. We close with an analysis examining the interaction effects between two factors and we demonstrate how principal response curves can help in their visualisation. Example data and Canoco 5 projects are provided as Supplementary Material. Keywords multivariate analysis . ordination . constrained ordination . interaction . experimental design . data transformation . principal response curves Electronic supplementary material: The online version of this article

Ecological communities and their response to environmental gradients are increasingly being described by various measures of trait composition. Aggregated trait averages (i.e. averages of trait values of constituent species, weighted by species proportions) are popular indices reflecting the functional characteristics of locally dominant species. Because the variation of these indices along environmental gradients can be caused by both species turnover and intraspecific trait variability, it is necessary to disentangle the role of both components to community variability. For quantitative traits, trait averages can be calculated from ‘fixed’ trait values (i.e. a single mean trait value for individual species used for all habitats where the species is found) or trait values for individual species specific to each plot, or habitat, where the species is found. Changes in fixed averages across environments reflect species turnover, while changes in specific traits reflect both species turnover and within‐species variability in traits. Here we suggest a practical method (accompanied by a set of R functions) that, by combining ‘fixed’ and ‘specific averages’, disentangles the effect of species turnover, intraspecific trait variability, and their covariation. These effects can be further decomposed into parts ascribed to individual explanatory variables (i.e. treatments or environmental gradients considered). The method is illustrated with a case study from a factorial mowing and fertilization experiment in a meadow in South Bohemia. Results show that the variability decomposition differs markedly among traits studied (height, Specific Leaf Area, Leaf N, P, C concentrations, leaf and stem dry matter content), both according to the relative importance of species turnover and intraspecific variability, and also according to their response to experimental factors. Both the effect of intraspecific trait variability and species turnover must be taken into account when assessing the functional role of community trait structure. Neglecting intraspecific trait variability across habitats often results in underestimating the response of communities to environmental changes.

Abstract. Soils are extremely rich in biodiversity, and soil organisms play pivotal roles in supporting terrestrial life, but the role that individual plants and plant communities play in influencing the diversity and functioning of soil food webs remains highly debated. Plants, as primary producers and providers of resources to the soil food web, are of vital importance for the composition, structure, and functioning of soil communities. However, whether natural soil food webs that are completely open to immigration and emigration differ underneath individual plants remains unknown. In a biodiversity restoration experiment we first compared the soil nematode communities of 228 individual plants belonging to eight herbaceous species. We included grass, leguminous, and non-leguminous species. Each individual plant grew intermingled with other species, but all plant species had a different nematode community. Moreover, nematode communities were more similar when plant individuals were growing in the same as compared to different plant communities, and these effects were most apparent for the groups of bacterivorous, carnivorous, and omnivorous nematodes. Subsequently, we analyzed the composition, structure, and functioning of the complete soil food webs of 58 individual plants, belonging to two of the plant species, Lotus corniculatus (Fabaceae) and Plantago lanceolata (Plantaginaceae). We isolated and identified more than 150 taxa/groups of soil organisms. The soil community composition and structure of the entire food webs were influenced both by the species identity of the plant individual and the surrounding plant community. Unexpectedly, plant identity had the strongest effects on decomposing soil organisms, widely believed to be generalist feeders. In contrast, quantitative food web modeling showed that the composition of the plant community influenced nitrogen mineralization under individual plants, but that plant species identity did not affect nitrogen or carbon mineralization or food web stability. Hence, the composition and structure of entire soil food webs vary at the scale of individual plants and are strongly influenced by the species identity of the plant. However, the ecosystem functions these food webs provide are determined by the identity of the entire plant community.

The stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.

Succession is one of the most studied processes in ecology and succession theory provides strong predictability. However, few attempts have been made to influence the course of succession thereby testing the hypothesis that passing through one stage is essential before entering the next one. At each stage of succession ecosystem processes may be affected by the diversity of species present, but there is little empirical evidence showing that plant species diversity may affect succession. On ex-arable land, a major constraint of vegetation succession is the dominance of perennial early-successional (arable weed) species. Our aim was to change the initial vegetation succession by the direct sowing of later-successional plant species. The hypothesis was tested that a diverse plant species mixture would be more successful in weed suppression than species-poor mixtures. In order to provide a robust test including a wide range of environmental conditions and plant species, experiments were carried out at five sites across Europe. At each site, an identical experiment was set up, albeit that the plant species composition of the sown mixtures differed from site to site. Results of the 2-year study showed that diverse plant species mixtures were more effective at reducing the number of natural colonisers (mainly weeds from the seed bank) than the average low-diversity treatment. However, the effect of the low-diversity treatment depended on the composition of the species mixture. Thus, the effect of enhanced species diversity strongly depended on the species composition of the low-diversity treatments used for comparison. The effects of high-diversity plant species mixtures on weed suppression differed between sites. Low-productivity sites gave the weakest response to the diversity treatments. These differences among sites did not change the general pattern. The present results have implications for understanding biological invasions. It has been hypothesised that alien species are more likely to invade species-poor communities than communities with high diversity. However, our results show that the identity of the local species matters. This may explain, at least partly, controversial results of studies on the relation between local diversity and the probability of being invaded by aliens.

Arbuscular mycorrhizal fungi (AMF) are ubiquitous soil fungi, forming mutualistic symbiosis with a majority of terrestrial plant species. They are abundant in nearly all soils, less diverse than soil prokaryotes and other intensively studied soil organisms and thus are promising candidates for universal indicators of land management legacies and soil quality degradation. However, insufficient data on how the composition of indigenous AMF varies along soil and landscape gradients have hampered the definition of baselines and effect thresholds to date. Here, indigenous AMF communities in 154 agricultural soils collected across Switzerland were profiled by quantitative real-time PCR with taxon-specific markers for six widespread AMF species. To identify the key determinants of AMF community composition, the profiles were related to soil properties, land management and site geography. Our results indicate a number of well-supported dependencies between abundances of certain AMF taxa and soil properties such as pH, soil fertility and texture, and a surprising lack of effect of available soil phosphorus on the AMF community profiles. Site geography, especially the altitude and large geographical distance, strongly affected AMF communities. Unexpected was the apparent lack of a strong land management effect on the AMF communities as compared to the other predictors, which could be due to the rarity of highly intensive and unsustainable land management in Swiss agriculture. In spite of the extensive coverage of large geographical and soil gradients, we did not identify any taxon suitable as an indicator of land use among the six taxa we studied.

Plant species diversity, plant biomass and responses of the soil community on abandoned land across Europe: idiosyncracy or above-belowground time lags