Harnessing iEcology data to uncover invasive species behaviour

Journal article

Invasive animal species threaten ecosystems, biodiversity and human livelihoods. Behavioural traits such as boldness, exploratory tendencies, learning ability and social interactions are known to influence invasion success. Yet these behavioural traits remain underexplored due to challenges in observing behaviour across large spatial and temporal scales. The emerging field of iEcology—studying ecology using digital data such as online photos, videos, sounds and text, generated for other purposes—offers a novel and scalable approach for investigating invasive species behaviour. Here, we demonstrate the application of iEcology to uncover novel insights into the behaviour of invasive species, such as dominance over the native species, interactions with native species or increased tolerance to humans, all critical for assessing species' invasion potential and management. We also discuss challenges of applying iEcology to studying the behaviour of invasive animals and highlight the need for careful validation and complementary methods. Finally, we highlight ways and provide a workflow to maximise the potential of iEcology for advancing the study of invasive species behaviour. We advocate for integrating iEcology into invasion science to advance our understanding of animal behaviours accompanying invasion success and ultimately to support the monitoring, management and mitigation strategies of biological invasions. We argue that iEcology is best viewed as a complementary tool that enriches traditional behavioural ecology and invasion biology, enabling rapid, accessible insights into one of the most urgent ecological issues of our time.

Authors: Mikula, P; Pipek, P; Bulla, M; Castillo, ML; Chowdhury, S

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Methods in Ecology and Evolution
• Article number: 2041-210x.70266
• Publication date: 2026-02-17
• Acceptance date: 2026-01-30
• DOI: 10.1111/2041-210x.70266
• EISSN: 2041210X
• ISSN: 2041210X
• Language: English
• Keywords: animal behaviour; ecological monitoring; iEcology; behavioural ecology; digital data; invasive species