8 research outputs found
Recommended from our members
Towards a function-first framework to make soil microbial ecology predictive
Soil microbial communities perform vital ecosystem functions, such as the decomposition of organic matter to provide plant nutrition. However, despite the functional importance of soil microorganisms, attribution of ecosystem function to particular constituents of the microbial community has been impeded by a lack of information linking microbial function to community composition and structure. Here, we propose a function-first framework to predict how microbial communities influence ecosystem functions. We first view the microbial community associated with a specific function as a whole, and describe the dependence of microbial functions on environmental factors (e.g. the intrinsic temperature dependence of bacterial growth rates). This step defines the aggregate functional response curve of the community. Second, the contribution of the whole community to ecosystem function can be predicted, by combining the functional response curve with current environmental conditions. Functional response curves can then be linked with taxonomic data in order to identify sets of “biomarker” taxa that signal how microbial communities regulate ecosystem functions. Ultimately, such indicator taxa may be used as a diagnostic tool, enabling predictions of ecosystem function from community composition. In this paper, we provide three examples to illustrate the proposed framework, whereby the dependence of bacterial growth on environmental factors, including temperature, pH and salinity, is defined as the functional response curve used to interlink soil bacterial community structure and function. Applying this framework will make it possible to predict ecosystem functions directly from microbial community composition
FungalTraits : a user-friendly traits database of fungi and fungus-like stramenopiles
The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies. Over the past decades, rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats. Yet, in spite of the progress of molecular methods, knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging. In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels. Combining the information from previous efforts such as FUNGuild and FunFun together with involvement of expert knowledge, we reannotated 10,210 and 151 fungal and Stramenopila genera, respectively. This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera, designed for rapid functional assignments of environmental studies. In order to assign the trait states to fungal species hypotheses, the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences. On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1% dissimilarity threshold.Supplementary Information: Fig. S1. Trait distributions of fungal genera in different fungal phyla.Fig. S2. Trait distributions of Stramenopila genera in different Stramenopila phyla.Fig. S3. Distribution of the ten most common fungal guilds among annotated sequences.Table S1. Traits of genera.Table S2. Traits of sequences.Table S3. Traits of species hypothesis.Table S4. Example dataset for genus-level annotation using the vlookup function in Excel.Table S5. Comparison of workflows and outputs conducted in FunTraits and FUNGuild.Supplementary item 1. List of trait states for genera and sequences.Supplementary item 2. Instructions for annotators of fungal ITS sequences.Estonian Science Foundation, the University of Tartu and the European Regional Development Fund.https://www.springer.com/journal/132252021-11-01hj2021BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant Patholog
TRY plant trait database - enhanced coverage and open access
10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18