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.

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An evolutionary framework for ecological status assessment using freshwater macroinvertebrates
Aquatic macroinvertebrates form complex species assemblages and are widely used in biomonitoring of water quality under the Water Framework Directive. Because of the need for rapid and cost-effective identification, many species are lumped taxonomically, e.g. by family, or even into loose ecological groups, such as 'riverflies'. However, responses to water quality and environmental stressors differ greatly between species, even if closely related. Recent protocols for DNA sequencing from environmental specimen mixtures ('metabarcoding') provide faster and more highly-resolved taxonomic identification (1). 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 via contemporary evolutionary statistical methods (2). We make use of high-quality datasets of biological and ecological traits available for the majority of aquatic macroinvertebrate species in Europe (~8800 species in 18 phyla) (3), and link these trait data to a growing body of DNA 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, by incorporating information about known species trait relationships, as those affecting life cycle duration, body size, feeding habits, reproduction, or habitat climatic associations (see 4). 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 ongoing biomonitoring of water bodies in most 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 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. The project will incorporate 'tree thinking' and the use of explicit ecological traits into mainstream environmental science. The unprecedented scale, based on a whole-ecosystem and all-species phylogenies, will permit novel comparisons of trait evolution across the tree-of-life. References: (1) Andujar C, et al. 2018. Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill. Mol Ecol, 27 (1), 146-166 (2) Capellini I, et al. 2015. The role of life history traits in mammalian invasion success. Ecol Lett, 18, 1099-1107. (3) Murria C, et al. 2018. Ecological constraints from incumbent clades drive trait evolution across the tree-of-life of freshwater macroinvertebrates. Ecography: 41 (7) 1049-1063 (4) Beerman AJ, et al. 2018. DNA metabarcoding reveals the complex and hidden responses of chironomids to multiple stressors. Environ Sci Eur 30:26
Alfried Vogler
Chris Venditti
Dr Kat Bruce, NatureMetrics Ltd, Egham, UK (kat@naturemetrics.co.uk)
Quantitative data analysis, Ecological observations / data collection, Evolutionary observations / data collection
Chris Venditti
Bioinformatics - data extraction from genomic resources. Large scale phylogenetic inference - Bayesian Markov chain and maximum likelihood. Phylogenetic comparative methods - trait evolution modelling, 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
This project represents a pioneering attempt towards an evolutionary perspective on biological and ecological traits, to complement current practices of aquatic biomonitoring based on simplistic measures of species occurrences and abundance. The application of phylogenetic methods at the ecosystem level provides critical links between aspects of ecological, life history and species diversity.
It is often assumed that trait evolution and speciation are coupled - but there are hints in literature that question this assumption. The ecological drivers of diversification are usually understood to be environment, competition and biogeography but their relative contribution is unknown. Using trait information and a fully resolved phylogenetic tree this project will be able to address this.
The project will be integrated with European-wide efforts (the EU COST action DNAquaNet) towards a DNA-based system for monitoring and for calibrating these data against the conventional indices of water quality. NatureMetrics, a company providing DNA-based monitoring of freshwater, acts as CASE partner and will utilise trait-based assessment in their development of environmental models.
It is often assumed that trait evolution and speciation are coupled - but there are hints in literature that question this assumption. The ecological drivers of diversification are usually understood to be environment, competition and biogeography but their relative contribution is unknown. Using trait information and a fully resolved phylogenetic tree this project will be able to address this.
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, Ecosystem-scale processes and land use, 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.
Natural History Museum, Reading University, NatureMetrics (Egham, Surrey)
Yes
2019-05-23 15:38:18