The QMEE CDT Project proposal database

Welcome to the QMEE CDT Project proposal database. This is a live list of projects proposals put forward by PIs across the CDT partner institutions

PIs/Supervisors will continue to add projects to this list over the next few months, so do keep checking back! You can search the projects using the box below: simply enter some text and press Search to do a text search across all the database fields. If you want to search more finely, the search tool also allows you to search on particular details of the project descriptions: you will see these finer search options appear if you click on the search box.

Click on the view button next to a project to get the full proposal description. If you want to download project details, either for all projects, or for a subset you have searched for, then click on the 'Download details' button.

Large-scale phylogenetics to link biological trait evolution and environmental susceptibility in European freshwater macroinvertebrates
Aquatic macroinvertebrates form complex assemblages composed of numerous species from several phyla, which are widely used in biomonitoring of water quality under the EU Water Framework Directive. However, because of the need for rapid and cost-effective identification, many species are lumped taxonomically, e.g. by family, or even into trait-based groupings, such as “riverflies”, although responses to water quality and environmental stressors differ between closely related species. Recent protocols for metabarcoding, i.e. DNA sequencing from environmental specimen mixtures, provide faster and more highly-resolved taxonomic identification. In addition, with growing genomic data, molecular phylogenetics can be incorporated in the study of complex species assemblages and linked to ecological, physiological and behavioural characteristics that determine differential responses to environmental conditions (and may reveal the membership in feeding groups and position in trophic networks) via contemporary evolutionary statistical methods. We will make use of high quality datasets of biological and ecological traits that have recently been compiled from extensive literature sources for the majority of aquatic macroinvertebrate species (~8800 species in 18 phyla) present in Europe, and link these trait data to a growing body of DNA sequence data to estimate phylogenetic trees of unprecedented completeness at the species level. Species are not independent entities; they variously share millions of years of evolution and a phylogenetic tree describes how. Thus, closely related species share similar characteristics giving phylogenetic trees inherent predictive power, e.g. predicting the response to water quality, based on known species traits (such as life cycle duration, body size, feeding habits, reproduction, microhabitat and climatic associations). Within this framework, it will be possible to construct generalized least squares and mixed models to statistically characterise a suite of ecological (based on known trait data) and evolutionary (phylogenetic position in the tree) markers for water quality. This model will be based on data from continuous biomonitoring of water bodies in all European countries assessed for species occurrences that are classified against unimpacted “reference conditions”. Using this to inform phylogenetic imputation techniques, it is possible to predict which species or taxonomically higher groups should be used as indicators in the future. The model will also incorporate species distribution data and differences in range sizes (as a proxy of dispersal), in particular between running and standing (lotic and lentic) waterbodies that greatly differ in habitat stability (and possibly susceptibility to disturbance). This project represents a pioneering attempt towards an evolutionary perspective on biological and ecological traits to complement current practices of aquatic biomonitoring of observing species occurrences. The application of phylogenetic methods at the ecosystem level has never been conducted at the scale we propose here. It will permit the estimation of rates of trait variation across different portions of the tree-of-life and provide critical links between aspects of ecological, life history and species diversity. The project will be integrated with European-wide efforts towards a DNA-based system for monitoring and calibrating these data against the conventional indices of water quality.
Alfried Vogler
Chris Vinditti
Prof Guy Woodward, Imperial College, guy.woodward@imperial.ac.uk; Dr Kat Bruce, NatureMetrics Ltd, kat@naturemetrics.co.uk
Computing, Quantitative data analysis, Ecological observations / data collection, Evolutionary observations / data collection
Chris Vinditti
Bioinformatics - data extraction from genomic resources. Large scale phylogenetic inference – Bayesian Markov chain and maximum likelihood. Phylogenetic comparative methods – trait evolution modeling, speciation and extinction rates, environmental niche modelling. Student preference will allow a focus on novel bioinformatics approaches for water monitoring or on development of comparative methods.
The project will incorporate ‘tree thinking’ and the use of explicit ecological traits (rather than simplistic species occurrences) into mainstream environmental science. The unprecedented scale, based on a whole-ecosystem and species-rich groups, will permit novel comparisons of trait evolution across the tree-of-life.
Lineage diversification involves speciation and trait evolution, but it is unclear to what degree these processes are correlated. Using trait information and a fully resolved phylogenetic tree the project will address fundamental questions about the roles of the environment, competition and biogeographic distributions in the diversification process.
Biomonitoring based on taxonomic identification does not consider the traits that determine environmental associations. The “reference condition” approach has been adopted as a central principle of the Water Framework Directive, and this will be refined here using trait-based analyses for a causal relationship of species occurrence and environmental stress.
An evolutionary, trait-based approach to biomonitoring of aquatic systems will lead to a clearer understanding of the specific factors leading to susceptibility of species. DNA-based approaches thus not only can produce faster and more accurate identifications, but also transform the interpretation of biomonitoring data.
By synthesizing environmental trait data and phylogenetics, this project bridges ecological and evolutionary disciplines that to date have mostly existed in isolation. Bioinformatics approaches are increasingly applied to ecological and evolutionary research but have not been linked for the analysis of complex species assemblages and entire ecosystems.
Systematics and taxonomy, Environmental genomics, Ecological/Evolutionary tools, technology & methods
Bioinformatics (pipeline development and scripting in Vogler lab); phylogenetic analysis (building large trees by hands-on training and participation in relevant MSc modules); statistical analysis of trait association (Venditti research group); applied aspects of biomonitoring through secondment at NatureMetrics Ltd. (CASE partner) and attendance at the DNAquaNet consortium (EU-COST Action).
Natural History Museum, Reading University, NatureMetrics (Egham, Surrey)
Yes
2017-10-02 11:58:52