Actions are expected to:

• analyse existing models: evaluate and prioritise existing alternative socio-economic models related to biodiversity protection and restoration, identifying best practices and assessing their impacts across Europe. This analysis should explore pathways for future development and implementation of these models, aiming to generate the most positive biodiversity outcomes, while also promoting climate resilience, social equity and community well-being;
• analyse barriers: Identify and propose solutions to overcome potential barriers and obstacles in scaling up the best available models. This includes considering the potential of Generative AI to enhance model implementation and effectiveness;
• identify gaps and build capacity: pinpoint gaps in current research, innovation, skills, education, legislation and technology. Propose capacity-building strategies to address these gaps, ensuring that the necessary infrastructure and knowledge are in place to support the widespread adoption of effective and fair socio-economic models;
• advance valuation methods: Build on previous research, notably incentive mechanisms and natural capital valuation methods (both monetary and non-monetary), to make progress towards standardised, widely accepted indicators. These indicators should reflect broader socio-economic, biodiversity and natural capital benefits as well as trade-offs. A reflexive use of valuation methods is encouraged, considering the ethical and social implications of different valuation approaches;
• develop and pilot strategies: using collaborative and participatory approaches, develop and pilot strategies, scenario methods, market and non-market measures, instruments, and approaches to scale-up the implementation of alternative socio-economic model.
• co-design pathways: work with stakeholders, including decision-makers, to co-design pathways towards the implementation of alternative socio-economic models. Develop innovative technologies and tools to support scenarios that capture the specificities of different ecosystems, ensuring that models are adaptable and responsive to the unique challenges faced by various regions and sectors.
• engage stakeholders: actively involve end-users such as policy and decision makers and citizens in the co-creation process. This could include the use of Generative AI-based tools to fully account for diverse views and needs, facilitating broader acceptance and application of the proposed models.
• disseminate knowledge: issue and disseminate recommendations, actionable knowledge and empowerment tools at European and possibly Member State levels. Explore synergies with other European initiatives, policies and strategies particularly those under the EU Green Deal, including various fiscal, financial and economic policies to help reach sustainability. Outcomes and findings should also be disseminated beyond the EU.
• investigate economic models: analyse how traditional economic models contribute to biodiversity loss, climate change and other socio-economic challenges, as well as the interactions between these challenges. Identify pragmatic actions and strategies to address these issues, considering the root causes of unsustainable practises, power imbalances and justice concerns.

Concretely, the project(s) should support the practical implementation of the EU biodiversity strategy and the GBF, providing evidence-based recommendations.

Actions should build on synergies across multiple SDGs to deliver both direct and indirect biodiversity benefits, and leverage the knowledge compiled in IPBES assessment reports.
Actions should consider ethical implications throughout project lifecycles, ensuring that outcomes align with broader societal values and contribute to equitable and just transitions.
Actions should address specific challenges faced by different ecosystems, especially vulnerable ecosystems (e.g. agriculture, forestry) and communities (e.g. rural areas, those facing socio-economic inequalities).