Scalable early warning and rapid response data systems for invasive species biosecurity

Invasive Alien Species are a major driver of biodiversity loss globally, with impacts across all sectors of society. Actions that focus on prevention, such as biosecurity practices, pathway management, contingency planning and rapid response, are more cost effective than ongoing management or wide scale eradication of established species. This is reflected in KM-GBF target 6 which requires parties to prevent establishment of priority species and 50% of other invasive species by 2050. Addressing this target requires robust prioritisation, tracking and response to new incursions of invasive non-native species. While global datasets such as GRIIS and GISD can help with establishing baseline data there is no best practise workflow to track species establishment and detection of new species through time or the management response to these species, which are critical to developing an indicator for the target. Records of species occurrence and incursion may come from a variety of sources including surveys, monitoring surveillance and citizen science, and will be variable depending on current practice and supporting governance and infrastructure. Currently bespoke approaches are being developed or maintained, but these can lack consistency and interoperability with other datasets or don’t have common access. As with other biodiversity data, IAS data should adhere to the FAIR and OPEN data principles. Substantial improvements to invasive species management and information sharing could be made by increasing the accessibility and interoperability of incursion tracking and response systems and considering areas of improvement, for example linking these to existing global databases and / or through the use of AI and LLMs.

This project will investigate the barriers, challenges and needs across different knowledge systems in implementing effective biosecurity, incursion tracking and rapid response systems. We aim to understand how systems can be improved and how can local systems (e.g. for protected areas) be interoperable with national reporting systems where needs and priorities may differ.

The student will use a series of case studies to consider fundamental knowledge and process gaps to develop an effective and scalable workflow for reporting on biosecurity practises. The case studies will explore different scales and knowledge systems and will facilitate working with practitioners and decision makers to understand the use and limitations of current practise, resources and reporting requirements. This information will be used to co-design workflows to integrate data on biological invasions and to improve user access and ease of analysis and reporting. The overall aim is to develop a scalable workflow and reporting analytics to interrogate datasets and visualise trends for invasive species biosecurity, providing a model that can be replicated elsewhere. This will directly address the policy needs for addressing target 6 and mitigate the adverse impacts of invasive species and bending the curve on biodiversity loss.

Objectives:

1. Scope the invasive species biosecurity data requirements to report on KM-GBF target 6. Review how complete this is for case studies representing different spatial scales and knowledge systems
2. Design a scalable workflow to enable the creation and use of Fair and Open datasets and information using the full range of available data sources to support early detection of invasive species incursions and their management
3. Develop a user interface for data interrogation and a series of analytical modules to support T6 reporting (e.g. datasets for tracking and indicator), incursion tracking, horizon scanning and risk management feasibility.

More information here: Scalable early warning and rapid response data systems for invasive species biosecurity. – IAPETUS