A conceptual classification scheme of invasion science

Area of Science:

• Invasion science
• Biodiversity conservation
• Data science

Background:

• The era of big data and global biodiversity decline necessitates transforming information into actionable knowledge.
• Existing frameworks like hypothesis networks are insufficient for organizing invasion science literature and data.

Purpose of the Study:

• To propose a conceptual classification scheme for invasion science.
• To organize publications and datasets, guide research, and identify knowledge gaps.
• To create a foundational reference for advancing invasion science.

Main Methods:

• Combined expert knowledge with comprehensive literature analysis.
• Identified five major research themes within invasion science.
• Developed a hierarchical structure linking themes, research questions, and hypotheses.

Main Results:

• Five major research themes were identified: introduction pathways, invasion success/invasibility, impacts, management, and meta-invasion science.
• These themes were structured into 10 research questions and 39 major hypotheses.
• The classification scheme provides a theoretical foundation for invasion science.

Conclusions:

• The proposed classification scheme offers a robust framework for organizing invasion science knowledge.
• This approach can guide future research, identify knowledge gaps, and support AI-driven information organization.
• The conceptual scheme is adaptable to other scientific fields, promoting interdisciplinary collaboration for Anthropocene challenges.