As environmental challenges intensify, Nature-based Solutions (NbS) have emerged as a critical approach for fostering sustainable and resilient ecosystems across diverse landscapes. The integration of natural processes into planning and management offers significant benefits for environmental health and socio-ecological balance. However, the complexity of ecosystems—whether urban, rural, or regional—often presents challenges in the effective design and implementation of these solutions. The advent of Artificial Intelligence (AI) and decision support tools provides a powerful means to overcome these obstacles, enabling a deeper understanding and more precise application of NbS across various contexts.
This session will explore the potential for combining in a way that benefits both fields. It will look at how AI-driven tools can be used to improve environmental planning and policymaking. By examining case studies and practical examples, the session will demonstrate how AI enhances the effectiveness of NbS by improving our ability to model, predict, and optimize their impacts on ecosystems. Furthermore, the discussion will address the role of AI in developing fair and inclusive governance frameworks, ensuring that the advantages of NbS are accessible to all communities and regions. Additionally, the economic implications of integrating AI with NbS will be explored, highlighting opportunities for cost-effective and scalable sustainable action. The session will address common challenges and misconceptions associated with AI in ecosystem management, emphasizing the need for effective integration strategies and long-term sustainability. This session seeks to:
• Enhancing NbS with AI: Examine how AI can be used in conjunction with NbS to enhance our understanding of socio-ecological systems and amplify the impact of NbS across various ecosystems.
• AI-driven implementation: Illustrate the ways in which AI can facilitate the design and implementation of NbS, thereby supporting the achievement of sustainable environmental management.
• Governance and equity: Debate the potential of AI-enabled decision support tools to promote inclusive governance models, ensuring fair and effective NbS deployment in diverse contexts.
• Economic and sustainability insights: Investigate the economic benefits and sustainability outcomes of integrating AI with NbS for scalable solutions.
This session will explore the potential for combining in a way that benefits both fields. It will look at how AI-driven tools can be used to improve environmental planning and policymaking. By examining case studies and practical examples, the session will demonstrate how AI enhances the effectiveness of NbS by improving our ability to model, predict, and optimize their impacts on ecosystems. Furthermore, the discussion will address the role of AI in developing fair and inclusive governance frameworks, ensuring that the advantages of NbS are accessible to all communities and regions. Additionally, the economic implications of integrating AI with NbS will be explored, highlighting opportunities for cost-effective and scalable sustainable action. The session will address common challenges and misconceptions associated with AI in ecosystem management, emphasizing the need for effective integration strategies and long-term sustainability. This session seeks to:
• Enhancing NbS with AI: Examine how AI can be used in conjunction with NbS to enhance our understanding of socio-ecological systems and amplify the impact of NbS across various ecosystems.
• AI-driven implementation: Illustrate the ways in which AI can facilitate the design and implementation of NbS, thereby supporting the achievement of sustainable environmental management.
• Governance and equity: Debate the potential of AI-enabled decision support tools to promote inclusive governance models, ensuring fair and effective NbS deployment in diverse contexts.
• Economic and sustainability insights: Investigate the economic benefits and sustainability outcomes of integrating AI with NbS for scalable solutions.