Aims The aim of this guide is to provide practical help for ecologists who analyze data from biodiversity–ecosystem functioning experiments. Our approach differs from others in the use of least squares-based linear models (LMs) together with restricted maximum likelihood-based mixed models (MMs) for the analysis of hierarchical data. An original data set containing diameter and height of young trees grown in monocultures, 2- or 4-species mixtures under ambient light or shade is used as an example.
Methods Starting with a simple LM, basic features of model fitting and the subsequent analysis of variance (ANOVA) for significance tests are summarized. From this, more complex models are developed. We use the statistical software R for model fitting and to demonstrate similarities and complementarities between LMs and MMs. The formation of contrasts and the use of error (LMs) or random-effects (MMs) terms to account for hierarchical data structure in ANOVAs are explained.
Important Findings Data from biodiversity experiments can be analyzed at the level of entire plant communities (plots) and plant individuals. The basic explanatory term is species composition, which can be divided into contrasts in many ways depending on specific biological hypotheses. Typically, these contrasts code for aspects of species richness or the presence of particular species. For significance tests in ANOVAs, contrast terms generally are compared with remaining variation of the explanatory terms from which they have been ‘carved out’. Once a final model has been selected, parameters (e.g. means or slopes for fixed-effects terms and variance components for error or random-effects terms) can be estimated to indicate the direction and size of effects.

Aims Growth rates of plants are driven by factors that influence the amount of resources captured and the efficiency of resource use. In trees, the amount of light captured and the efficiency of light use strongly depends on crown characteristics and leaf traits. Although theory predicts that both crown and leaf traits affect tree growth, few studies have yet to integrate these two types of traits to explain species-specific growth rates. Using 37 broad-leaved tree species of subtropical forests in SE China, we investigated how interspecific differences in wood volume growth rates were affected by crown and leaf traits. We tested the hypotheses that (i) larger crown dimensions promote growth rates, (ii) species-specific growth rates are positively related to leaf stomatal conductance, leaf water potential and leaf chemical components, and negatively related to leaf C/N and leaf toughness and (iii) the two sets of traits better explain growth rates in combination than either alone.
Methods Our study was conducted in a large-scale forest Biodiversity and Ecosystem Functioning experiment in China (BEF-China), located in a mountainous region in Jiangxi Province. We related 17 functional traits (two crown dimension and three crown structure traits; six physiological and six morphological leaf traits) to the mean annual growth rate of wood volume of young trees of the studied species. Interrelationships between crown and leaf traits were analyzed using principal component analysis. Simple linear regression analysis was used to test the effect of each trait separately. We used multiple regression analysis to establish the relationship of growth rate to each set of traits (crown traits, physiological and morphological leaf traits) and to the combination of all types of traits. The coefficients of determination (R 2 adj) of the best multiple regression models were compared to determine the relative explanatory power of crown and leaf traits and a combination of both.
Important findings The species-specific growth rates were not related to any of the single crown traits, but were related positively to leaf stomatal conductance and leaf water potential individually, and negatively to leaf toughness, with approximately 13% variance explained by each of the traits. Combinations of different crown traits did not significantly explain the species-specific growth rates, whereas combinations of either physiological or morphological leaf traits explained 24% and 31%, respectively. A combination of both crown and leaf traits explained 42% of variance in species-specific growth rates. We concluded that sets of traits related to carbon assimilation at the leaf-level and to overall amount of leaves exposed at the crown-level jointly explained species-specific growth rates better than either set of traits alone.

Aims Soil sample preservation is a challenging aspect in molecular studies on soil microbial communities. The demands for specialized sample storage equipment, chemicals and standardized protocols for nucleic acid extraction often require sample processing in a home laboratory that can be continents apart from sampling sites. Standard sampling procedures, especially when dealing with RNA, comprise immediate snap freezing of soils in liquid nitrogen and storage at ?80°C until further processing. For these instances, organizing a reliable cooling chain to transport hundreds of soil samples between continents is very costly, if possible at all. In this study we tested the effect of soil sample preservation by freeze-drying with subsequent short-term storage at 4°C or ambient temperatures compared to ?80°C freezing by comparative barcoding analyses of soil microbial communities.
Methods Two grassland soil samples were collected in Central Germany in the Biodiversity Exploratory Hainich-Dün. Samples were freeze-dried or stored at ?80°C as controls. Freeze-dried samples were stored at 4°C or ambient temperature. Investigated storage times for both storage temperatures were 1 and 7 days. Total DNA and RNA were extracted and bacterial and arbuscular mycorrhizal (AM) fungal communities were analyzed by amplicon 454 pyrosequencing of the 16S (V4-V5 variable region) and 18S (NS31-AM1 fragment) of ribosomal RNA (rRNA) marker genes, respectively.
Important findings Bacterial communities were sufficiently well preserved at the rDNA and rRNA level although storage effects showed as slightly decreased alpha diversity indices for the prolonged storage of freeze-dried samples for 7 days. AM fungal communities could be studied without significant changes at the rDNA and rRNA level. Our results suggest that proper sampling design followed by immediate freeze-drying of soil samples enables short-term transportation of soil samples across continents.