Detection

detection

Current methods for detecting and monitoring invasive alien species (IAS) are often uncoordinated and reactive, causing delays that hinder effective management. Many emerging wildlife detection technologies could be used for IAS monitoring, but most are not yet technologically ready for widespread application. OneSTOP focuses on some of the most promising approaches: Air-DNA, iEcology, computer vision, and using citizen science in gardens as early warning sites for biological invasions.

These novel detection tools will feed into data-sharing systems, ensuring timely, accessible information reaches key stakeholders. They will also be implemented and tested in risk sites identified in the project’s Living Labs.

Air-DNA iEcology Computer vision Sentinel gardens

Air-DNA

Air-DNA is an advanced technique that identifies species by analysing DNA traces in air samples. It offers a fast, accurate, and cost-effective way to detect invasive alien species across multiple taxonomic groups, including animals, plants, fungi, and bacteria. Despite its potential, challenges remain, such as optimising sampling, reducing false positives, refining DNA extraction, and minimising contamination risks. 

Platform Kinetics is developing high-volume air samplers capable of capturing airborne particulates across a wide range of sizes, from spores to insect fragments. They will enable scheduled sample collection, adaptive sampling based on environmental triggers and multi-sample extraction and preservation. The samplers will record and integrate spatial and temporal data with external sources, enhancing IAS monitoring at scale.

D2.2 Evaluation of air-DNA workflow output - June 2027


iEcology

IAS are closely linked to human activities like trade, travel, and urbanisation, which contribute to their visibility across numerous online platforms. iEcology uses real-time global data from diverse digital sources— social media, online databases and image repositories—to study ecological patterns. Its scalability supports early IAS detection, while its broad geographical and temporal coverage enables tracking of their spread. Additionally, analysing online trends provides valuable insights into societal factors influencing IAS management.

OneSTOP is advancing iEcology by developing repeatable workflows, applying advanced data analysis techniques and integrating new digital sources. It uses Application Programming Interfaces to collect and aggregate digital content from European users on platforms like YouTube, Reddit, Wikipedia Page Views, and Google Trends. Machine learning and advanced algorithms will enhance the efficiency of analysing this extensive data.

D2.3 Evaluation of iEcology workflow output - March 2026


Computer vision

Computer vision enables automated detection and monitoring of IAS through image analysis. Machine learning (ML)-powered algorithms are already used in wildlife monitoring, from camera traps for mammals and birds to aerial identification of tree crowns. OneSTOP is advancing these technologies for large-scale detection of invasive plants, mammals, and insects using vehicle-mounted cameras and light traps.

A custom-built machine vision camera system will be deployed on vehicles, using deep-learning models developed in the MAMBO project with Pl@ntNet. This will automate species recognition, eliminating the need for botanical experts during recording. The system will also help detect roadkill, many of which involve IAS.

OneSTOP is also adapting standardised light traps for real-world use by field practitioners. The project employs the AMI system, developed by AU and UKCEH, which specifically attracts nocturnal insects.

D2.1 Implementation guide - December 2027


Sentinel gardens

Many IAS, especially birds and vascular plants, are monitored using data from citizen scientist volunteers who contribute valuable observations. OneSTOP is harnessing the power of citizen science to improve early IAS detection and monitoring, with a particular focus on engaging gardeners and their gardens as ‘sentinel’ sites. Gardens play a crucial role in IAS introductions, both through cultivated plants spreading into new environments and the unintentional movement of weeds, diseases, and invertebrates via soil and plant transport.

OneSTOP is encouraging participation through widely used citizen science platforms and apps that support open data sharing, such as iNaturalist, Observado.org, iRecord (UK), and IAS-specific tools like the EASIN app.

 D2.4 Sentinel gardens - February 2028