Liis Kasari

Evaluating functional diversity : missing trait data and the importance of species abundance structure and data transformation

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data.

Applying the dark diversity concept to nature conservation

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.

Within-community environmental variability drives trait variability in species-rich grasslands

Aims Spatial environmental heterogeneity has been considered an important coexistence mechanism, because environmental variation enables different species to co-occur. We predict if functional differences are important for coexistence, then both species and functional diversity should be positively related to environmental heterogeneity. Location 33 dry calcareous grassland sites in Estonia. Methods In each site, we established a transect (10 x 0.1 m), consisting of 100 quadrats (10 x 10 cm). In each quadrat, we recorded species richness and composition, and measured soil depth, moisture, and light availability. We collected data on 8 traits from most of the species found across the sites. We calculated functional diversity (FD) at the quadrat scale, and compared the observed-FD to that expected at random using two null models. The first null model used all the species that occurred in the transect in the randomisations, to determine environmental filtering from the transect to the quadrat. The second null model restricted the species used in the randomisations to those species whose trait range was within the range of the observed values in the quadrat, to detect evidence for niche partitioning. Quadrat mean trait values and variability in functional composition were then related to small-scale mean environmental conditions and heterogeneity respectively. Results We found convergent patterns in biomass, specific leaf area, specific root length, and clonality compared to randomised communities that included all species occurring in the transect, and we found divergence in height and leaf area using the range restricted null model. Hence, we found patterns consistent with environmental filtering and niche partitioning depending on the traits considered. Quadrat mean traits were significantly correlated with the measured environmental variables, with the main trend being a positive relationship between size-related traits and soil resources, and a negative relationship between these traits and light availability. Trait variability in height, leaf area, leaf dry matter content, specific root length and clonality was positively related to soil depth heterogeneity. There was a trend for species richness to be negatively related to environmental heterogeneity. Conclusions Co-occurring species were more similar in several traits partly due to micro-environmental filtering in response to variability in soil depth. While environmental heterogeneity increased trait variability, negative relationships with species richness were observed. Hence, niche partitioning does not appear to be important for the maintenance of high small-scale species richness in these grasslands. This article is protected by copyright. All rights reserved.

Abiotic rather than biotic filtering shapes the arbuscular mycorrhizal fungal communities of European seminatural grasslands

Although it is well known that arbuscular mycorrhizal fungi (AMF) play a key role in the functioning of natural ecosystems, the underlying drivers determining the composition of AMF communities remain unclear. In this study, we established 138 sampling plots at 46 grassland sites, consisting of 26 acidic grasslands and 20 calcareous grasslands spread across eight European countries, to assess the relative importance of abiotic and biotic filtering in driving AMF community composition and structure in both the grassland soils and in the roots of 13 grassland plant species. Soil AMF communities differed significantly between acidic and calcareous grasslands. In root AMF communities, most variance was attributable to soil variables while very little variation was explained by host plant identity. Root AMF communities in host plant species occurring in only one grassland type closely resembled the soil AMF communities of that grassland type and the root AMF communities of other host plant species occurring in the same grassland type. The observed AMF-host plants networks were not modular but nested. Our results indicate that abiotic conditions, rather than biotic filtering through host plant specificity, are the most important drivers in shaping AMF communities in European seminatural grasslands.