ItemBook Chapter

AI-Driven Policy Frameworks and Decision Support Systems for Invasive Species Management and Biodiversity Conservation

Title
AI-Driven Policy Frameworks and Decision Support Systems for Invasive Species Management and Biodiversity Conservation
Creator
Ghosh, Oindrilla; Kumar, Binod
Description
Invasive species pose significant threats to biodiversity and ecosystem health. AI-driven policy frameworks and decision support systems can enhance invasive species management and biodiversity conservation efforts. By integrating machine learning algorithms and big data analysis, these systems provide real-time insights, enabling stakeholders to make informed decisions quickly. AI can identify patterns in species distribution, predict invasion potential, and assess ecological impacts. Additionally, these tools facilitate collaboration among policymakers, scientists, and conservationists, ensuring that strategies are evidence-based and tailored to local contexts. Effective implementation requires considering socio-economic factors and stakeholder engagement. As climate change continues to alter ecosystems, AI-driven systems can adapt to new challenges, promoting resilience. By harnessing technology, we can develop proactive strategies that balance human interests with ecological health, ultimately leading to sustainable environmental management. 2026 by IGI Global Scientific Publishing. All rights reserved.
Source
Harnessing AI for Invasive Species Management and Biodiversity Conservation;pp.1-32
Date
01-01-2026
Publisher
IGI Global
Coverage
Ghosh O., Christ University, India; Kumar B., Radha Govind University, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833734618-2; 979-833734616-8;
Format
online
Language
English
Type
Book chapter

Citation

Ghosh, Oindrilla; Kumar, Binod, “AI-Driven Policy Frameworks and Decision Support Systems for Invasive Species Management and Biodiversity Conservation,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/24800.

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