Understanding spatiotemporal changes in freshwater biodiversity using environmental DNA

Eastwood, Niamh ORCID: https://orcid.org/0000-0003-2969-6091 (2024). Understanding spatiotemporal changes in freshwater biodiversity using environmental DNA. University of Birmingham. Ph.D.

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Abstract

Human driven environmental change is having a widespread negative impact upon the planet’s biodiversity. Biodiversity is key to delivering the ecosystem functions and services which maintain a healthy environment. However, existing methods for monitoring biodiversity and understanding the interrelations between environmental change and biodiversity change are lacking. Traditional methods for biodiversity monitoring are taxonomically limited, labour intensive and low throughput, all of which results in a lack of whole community biodiversity data.
In this thesis, I set out a novel framework which utilises big data science to combine whole community biodiversity data with multiple environmental matrices and applies machine learning approaches to uncover the relationships between environmental and biodiversity change. I then applied this framework to a pilot lake to find correlations between the historical community, as measured using sedimentary environmental DNA, biocide usage and climate change. I show that the combination of these pressures can explain a large proportion of the variation in the lake community over time, underlining the value of longitudinal data analysis.
I improve on the processing of environmental DNA samples by developing a novel multiplexed metabarcoding method which utilises an early pooling approach and validate the method across biological matrices. This method offers a large reduction in library preparation cost and labour.
I then apply the multiplex method to two different sample types (water and biofilm) from over 50 lakes across England to assess spatial variation in freshwater communities. I showed that established regulatory methods under the water framework directive to classify lakes do not explain all of the variation in community diversity.
This thesis shows that whole community approaches, which capture variation in prokaryotic and eukaryotic biodiversity, can better reflect responses to environmental change and changes in ecosystem function and service delivery. This can be utilised to identify the factors, or combination of factors, most disruptive to biodiversity and therefore potential targets for regulation and remediation.

Type of Work:	Thesis (Doctorates > Ph.D.)
Award Type:	Doctorates > Ph.D.
Supervisor(s):	Supervisor(s) Email ORCID Orsini, Luisa UNSPECIFIED orcid.org/0000-0002-1716-5624 Abdallah, Mohamed UNSPECIFIED orcid.org/0000-0002-4624-4073 Zhou, Jiarui UNSPECIFIED orcid.org/0000-0002-1025-718X
Licence:	All rights reserved
College/Faculty:	Colleges > College of Life & Environmental Sciences
School or Department:	School of Biosciences
Funders:	Biotechnology and Biological Sciences Research Council
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QH Natural history > QH301 Biology
URI:	http://etheses.bham.ac.uk/id/eprint/14823

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