- Multidisciplinarity - This project combines paleoecology, high throughput sequencing technology applied to environmental DNA, bioinformatics and advanced computational tools
- Big data science – This project uses advanced computational tools and biostatistics to regress measures of biodiversity attributes on biotic and abiotic factors for discovering complex, group-wise patterns between high-dimensional datasets.
- Link to climate change policy - The assessment of freshwater community loss linked to eutrophication and climate change will support the identification of upcoming demands in environmental monitoring, assessment and management
Eutrophication and climate change are two of the most pressing environmental issues, affecting up to 50% of aquatic ecosystems worldwide 1, 2. Because of these environmental issues, about 40% of the world's population live in water stressed areas. These areas are projected to become 50-65% of the earth surface by 2025 3. Human-driven environmental change is affecting the abundance and distribution of species, altering biological communities and ecosystems 4, 5, 6. Current evidence shows that species extinction rates are many times greater than the direst predictions made two decades ago by the Convention on Biological Diversity, which predicted the extinction of more than 30% of multicellular species by 2100 7, 8. The most severe species decline, corresponding to 76% since 1970, is observed in freshwater ecosystems 7.
Biodiversity sustains ecosystem functions ensuring the delivery of ecosystem services critical to humans and wildlife. Yet, resource managers and policy makers struggle to initiate remedial actions from businesses and governments to mitigate loss of biodiversity. This is because there is inconclusive evidence that the benefits of protecting species richness and diversity outweigh the cost of biodiversity’s decline. We cannot reconcile concerns for biodiversity loss with evidence for dynamism of communities and resilience of trophic structure through past climate change. This is because most current studies focus on transient effects of environmental change in artificial settings 9 and ignore temporal variance in climate 10. Studying biodiversity attributes over evolutionary time scales is fundamental for understanding their effect on ecosystem functions, as both evolve through time and are contingent upon sequential or intensifying environmental factors 11.
Here, we will implement a transformative approach that enables the study of biodiversity in massively multi-generational natural ecosystems (100s of years) against a backdrop of anthropogenic change. We propose to apply traditional paleoecology combined with state-of-the-art technologies in DNA sequencing and advanced computational tools on dated sedimentary archives of natural lakes to discover biodiversity attributes critically impacted by eutrophication and climate change.
Biodiversity fingerprinting. Sedimentary records of primary producers (diatoms) and primary consumers (zooplankton) combined with metabarcoding or marker gene sequencing - the application of high throughput sequencing technology to environmental DNA extracted from dated sedimentary archives - will be used to determine the responses of lake systems to extrinsic environmental drivers.
Metataxonomy. Taxonomic groups’ assemblage in the sedimentary archives will be identified and quantified via searches of the metabarcoding output against existing databases (BOLD; SILVAngs; NCBI). The combined analysis of the sequence data will be accomplished with tools such as QIIME 12, VSEARCH 13, and OptiClust 14. Inferences on community changes over time will be made via estimates of alpha and beta diversity.
Bio-chemical associations. Sparse Canonical Correlation Analysis (sCCA) will be employed to regress measures of biodiversity attributes on biotic and abiotic factors in standard, multiple regressions using generalized linear models (GLM). sCCA is ideal for discovering complex, group-wise patterns between high-dimensional datasets.
Training and Skills
The DR will receive multisciplinary training spanning from traditional paleoecology via placements at Loughborough University, to cutting-edge high throughput sequencing and advanced computation with focus on machine learning. At the University of Birmingham, the DR will work in close liaison with the Environmental Omics Sequencing Facility, where he/she will be trained in high throughput sequencing technologies and liquid handling robotics for sample preparation. At the UoB, the DR will also receive training in bioinformatics, biostatistics and machine learning by Co-Is Brown and He, benefiting from access to one of the most up to date high performance computing facilities in the country.
Year 1: Paleoecological analysis of sediment including identification of algae and invertebrate remains from sediment. Gain familiarity with bioinformatics. Student conference in Birmingham.
Year 2: eDNA analysis, including DNA extraction from sediment, and ‘amplicon libraries’ preparation and sequencing. Present preliminary data in a workshop or national conference. Prepare draft of first thesis chapter.
Year 3: Bioinformatics analysis using QIIME 12,VSEARCH 13, and OptiClust 14. Application of machine learning algorithms to link biodiversity attributes and environmental changes (e.g. climate variables and eutrophication) and identify repeatability of biodiversity changes over time. Present thesis work in international conferences. Write thesis. Submit research article.
Partners and collaboration (including CASE)
Dr Glenn Watts works in the Evidence Directorate of the Environment Agency, leading a research team of 11 specialising in climate change and resource efficiency. His interests are in climate change impact and adaptation in the water sector. Dr Watts ha co-designed the proposed project and will offer co-supervision and training to the DR. Furthermore, he will offer short work placements at the Environmental Agency to accelerate the translation of research findings into climate change policy. One the expected outputs of the proposed research is the identification of priority species for conservation.