Advancing Environmental DNA (eDNA) applications for effective urban biomonitoring

Abstract

Urbanisation is a major threat to biodiversity. Nevertheless, biodiversity within urban ecosystems provides significant ecological and social value, delivering essential ecosystem services and supporting a diverse range of taxa, including endangered species. Although ecological research on urban ecosystems is increasing, it remains underrepresented compared to more traditional areas of ecological study. Furthermore, traditional approaches to obtaining urban biodiversity data, such as camera trapping, species distribution modelling, and participant surveys, face logistical constraints and limited detectability of certain taxa in urban contexts. As a result, knowledge gaps and a lack of effective data persist, hindering efforts to inform urban biodiversity policy and conservation. Addressing these challenges requires the exploration of innovative approaches to effectively monitor biodiversity in urban environments.
Environmental DNA (eDNA) analysis is an emerging, rapidly expanding tool in ecological monitoring. This approach involves capturing DNA that organisms shed into various environmental media such as water, soil, and air, enabling researchers to infer species presence effectively. The applications of eDNA analysis are extensive, such as the early detection of invasive species through targeted detection to broad scale monitoring of entire ecological communities via metabarcoding. The method is especially well suited to urban environments due its non-invasive approach, potential for integration with citizen science, and cost-effectiveness. While urban eDNA research is still developing, advancing and effectively communicating its applications is critical for present and future urban biodiversity management.
The thesis aims to advance the use of eDNA analysis for monitoring urban ecosystems and to demonstrate its efficacy as a biodiversity assessment tool. This research explores both conventional and novel sampling strategies for capturing eDNA from diverse urban environmental sources. This research also considers how species ecology affects eDNA detectability, with implications for urban species monitoring and conservation. To fulfill these aims, the thesis is structured around two key applications of eDNA: targeted detection of individual species and community-level monitoring via metabarcoding.
Chapter 2 investigates the targeted detection of a widespread invasive turtle species in urban aquatic environments, evaluating conventional water-based eDNA methods. It highlights the challenges of translating findings from controlled mesocosm studies to more complex real-world ecosystems, particularly when surveying for challenging taxa. Chapter 3 addresses these challenges by incorporating species-specific ecology and behaviour into the survey design. By targeting eDNA ‘hotspots’, detection probabilities for the invasive turtle were comparable to conventional aquatic eDNA methods, with improved efficiency and resource use. Chapter 4 shifts the focus to urban rooftops, providing a case study for examining species presence on green rooftop infrastructure in urban Sydney, Australia. This study compares biodiversity detected on green roofs with that of an adjacent conventional roof, offering insights into the ecological value of green infrastructure in densely built environments. Chapter 5 extends eDNA applications to a peri-urban conservation corridor, evaluating the performance of both passive and active eDNA water sampling techniques. This chapter demonstrates the utility of each approach and assess their effectiveness for long-term ecosystem management.
Overall, this research advances eDNA applications for urban biomonitoring by highlighting the importance of eDNA sample source, methods, and target species when conducting eDNA based biodiversity assessments. It shows how integrating eDNA into urban biodiversity monitoring frameworks can improve conservation outcomes, management effectiveness and support evidence-based decision-making.

Date of Award	2026
Original language	English
Supervisor	Dianne GLEESON (Supervisor) & Elise FURLAN (Supervisor)