Environmental DNA (eDNA) and other molecular based approaches are revolutionizing the field of biomonitoring. These approaches undergo rapid modifications, and it is crucial to develop the best practices by sharing the newest information and knowledge. In our ongoing project we:
assess the state-of-the-art of eDNA methods at Finnish Environment Institute SYKE;
identify concrete next steps towards the long-term aim of implementing eDNA methods into environmental and biomonitoring;
promote information exchange on eDNA methods and
advance future research efforts both within SYKE and with our national and international partners.
assess the state-of-the-art of eDNA methods at Finnish Environment Institute SYKE;
identify concrete next steps towards the long-term aim of implementing eDNA methods into environmental and biomonitoring;
promote information exchange on eDNA methods and
advance future research efforts both within SYKE and with our national and international partners.
Scientific background
Well-functioning and intact natural ecosystems are essential for human well-being, provide a variety of ecosystem services and contain a high diversity of organisms. However, human activities such as eutrophication, pollution, land-use or invasive species, are threatening the state and functioning of ecosystems from local to global scale (e.g. Benateau et al. 2019; Reid et al. 2018; Vörösmarty et al. 2010). New molecular techniques in the field and in the laboratory have enabled sampling and identification of much of terrestrial, marine and freshwater biodiversity. These include environmental DNA (eDNA, e.g. Valentini et al. 2016) and bulk-sample DNA metabarcoding approaches (e.g. Elbrecht et al. 2017) and targeted RNA-based methods (e.g. Mäki and Tiirola 2018). The eDNA technique uses DNA that is released from organisms into their environment, from which a signal of organisms’ presence in the system can be obtained. For example, in aquatic ecosystems, eDNA is typically extracted from sediment or filtered water samples (e.g. Deiner et al. 2016), and this approach is distinguished from bulk DNA metabarcoding, where organisms are directly identified from e.g. complete biological monitoring samples (e.g. Elbrecht et al. 2017). Despite the demonstrated potential of environmental and bulk-sample DNA metabarcoding approaches in recent years, there are still significant bottlenecks to their routine use that need to be addressed (e.g. Pawlowski et al. 2020).
Methods and implementati
on
The project is divided into three work packages: WP1 Gathering existing knowledge, identifying knowledge gaps and proposing best practices, WP2 Roadmap to implementation and WP3 eDNA monitoring pilot. Please see more details in the Fig. 1
Coastal Waste Detection Based on Deep Convolutional Neural Networks