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Title: Towards a networks based approach to biomonitoring
Author: Gray, Clare
ISNI:       0000 0004 7962 4026
Awarding Body: Queen Mary, University of London
Current Institution: Queen Mary, University of London
Date of Award: 2016
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Effective monitoring of the environment for anthropogenic impacts is essential for managing and conserving ecosystems, especially in the face of global climate change and an ever increasing human population. Yet current biomonitoring schemes are grounded in species or trait based approaches, and lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems. Ecological networks can offer new insights into ecosystem degradation by explicitly considering the interactions between species, adding value to current taxonomically constrained schemes. Here, I develop a formalisation of a method for constructing ecological networks from species lists and trophic information harvested from the primary literature (Chapter 2). I then use this method to augment traditional biomonitoring data with information on the interaction between species to build large collections of food webs (Chapters 3-5). I apply novel network analysis methods from complex network research to examine the substructure of these networks. In Chapter 3, I find that the structure, and substructure, of freshwater food webs are fundamentally altered by hydrochemical stress (Appendix A). Chapter 4 demonstrates that the structure of agricultural food webs are linked to the delivery of beneficial pest control services, potentially allowing those services to be enhanced through management of food web structure. Finally, in Chapter 5 I use more detailed food web data to investigate how freshwater food webs are impacted by a catastrophic pesticide spill, how the indirect effects propagate through the food web, and how the structure of the community and ecosystem functioning recover over time. The findings presented herein demonstrate that ecological networks constructed from routine biomonitoring data can be a useful tool for understanding the impacts of stressors on ecological communities. Considering the interactions between species is vital if we are to fully understand, and mitigate against the negative effects of global climate change on biodiversity.
Supervisor: Not available Sponsor: Queen Mary University of London ; Freshwater Biology Association
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Biological and Chemical Sciences ; biomonitoring ; Ecosystems