The arbuscular mycorrhizal (AM) fungi are a globally distributed group of soil organisms that play critical roles in ecosystem function. However, the ecological niches of individual AM fungal taxa are poorly understood.

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Interactions between communities of plants and arbuscular mycorrhizal (AM) fungi shape fundamental ecosystem properties. Experimental evidence suggests that compositional changes in plant and AM fungal communities should be correlated, but empirical data from natural ecosystems are scarce. We investigated the dynamics of covariation between plant and AM fungal communities during three stages of grassland succession, and the biotic and abiotic factors shaping these dynamics. Plant communities were characterised using vegetation surveys. AM fungal communities were characterised by 454-sequencing of the small subunit rRNA gene and identification against the AM fungal reference database MaarjAM. AM fungal abundance was estimated using neutral-lipid fatty acids (NLFAs). Multivariate correlation analysis (Procrustes) revealed a significant relationship between plant and AM fungal community composition. The strength of plant-AM fungal correlation weakened during succession following cessation of grassland management, reflecting changes in the proportion of plants exhibiting different AM status. Plant-AM fungal correlation was strong when the abundance of obligate AM plants was high, and declined as the proportion of facultative AM plants increased. We conclude that the extent to which plants rely on AM symbiosis can determine how tightly communities of plants and AM fungi are interlinked, regulating community assembly of both symbiotic partners.

Although mycorrhizas are expected to play a key role in community assembly during ecological succession, little is known about the dynamics of the symbiotic partners in natural systems. For instance, it is unclear how efficiently plants and arbuscular mycorrhizal (AM) fungi disperse into early successional ecosystems, and which, if either, symbiotic partner drives successional dynamics. This study describes the dynamics of plant and AM fungal communities, assesses correlation in the composition of plant and AM fungal communities and compares dispersal limitation of plants and AM fungi during succession. We studied gravel pits 20 and 50 years post abandonment and undisturbed grasslands in Western Estonia. The composition of plant and AM fungal communities was strongly correlated, and the strength of the correlation remained unchanged as succession progressed, indicating a stable dependence among mycorrhizal plants and AM fungi. A relatively high proportion of the AM fungal taxon pool was present in early successional sites, in comparison with the respective fraction of plants. These results suggest that AM fungi arrived faster than plants and may thus drive vegetation dynamics along secondary vegetation succession.

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Increasing urbanization worldwide calls for more sustainable urban development. Simultaneously, the global biodiversity crisis accentuates the need of fostering biodiversity within cities. Policies supporting urban nature conservation need to understand people's acceptance of biodiversity‐friendly greenspace management. We surveyed more than 2,000 people in 19 European cities about their attitudes toward near‐natural urban grassland management in public greenspaces, and related their responses to nine sociocultural parameters. Results reveal that people across Europe can support urban biodiversity, yet within the frames of a generally tidy appearance of public greenery. Younger people and those using greenspaces for a greater variety of activities were more likely to favor biodiversity‐friendly greenspace management. Additionally, people who were aware of the meaning of biodiversity and those stating responsibility for biodiversity conservation particularly supported biodiversity‐friendly greenspace management. Our results point at explicit measures like environmental education to increase public acceptance of policies that facilitate nature conservation within cities.

High‐throughput sequencing (HTS) of multiple organisms in parallel (metabarcoding) has become a routine and cost‐effective method for the analysis of microbial communities in environmental samples. However, careful data treatment is required to identify potential errors in HTS data, and the large volume of data generated by HTS requires in‐house experience with command line tools for downstream analysis. This paper introduces a pipeline that incorporates the most common command line tools into an easy‐to‐use graphical interface—gDAT. By using the Python scripting language, the pipeline is compatible with the latest Windows, macOS and Linux operating systems. The pipeline supports analysis of Sanger, 454, IonTorrent, Illumina and PacBio sequences, allows custom modification of quality filtering steps, and implements both open and closed‐reference operational taxonomic unit‐picking for sequence identification. Predefined parameters are optimized for analysis of small subunit (SSU) rRNA gene amplicons from arbuscular mycorrhizal fungi, but the pipeline is widely applicable to metabarcoding studies targeting a broad range of organisms. The pipeline was additionally tested with data using general eukaryotic primers from the SSU gene region and fungal primers from the internal transcribed spacer (ITS) marker region. We describe the pipeline design and evaluate its performance and speed by conducting analysis of example data sets using different marker regions sequenced on Illumina platforms. The graphical interface, with the option to use the command line if needed, provides an accessible tool for rapid data analysis with repeatability and logging capabilities. Keeping the software open‐source maximizes code accessibility, allowing scrutiny and bug fixes by the community.