Estimating essential phenotypic and molecular traits from integrative biodiversity data

In the context of biodiversity, only few functional traits and mechanisms are known from underrepresented groups such as mosses (bryophytes). Here, we use 16 field samples of complex thallose liverworts (order Marchantiales) collected from biological soil crusts as reference data for the reusable computational framework iESTIMATE that integrates and extracts phenotypic and molecular traits; and estimates Essential Molecular Variables (EMV). Our reference data involves (1) bioimaging, (2) metabolomics, and (3) DNA marker sequencing. These data are used to demonstrate the systematic and standardized extraction of phenotypic and molecular traits. To demonstrate the reusability of our framework, we propose naming schemes, apply Random Forest to estimate EMVs, phylogenetic dendrograms and partitioning around medoids to connect evolutionary relationships with ecological hypotheses and to document knowledge gains across domains. With this work we want to encourage the combined assessment, reuse and integration of phenotypic and molecular traits into functional ecology, biodiversity and related disciplines.