Expected Outcome:
In line with the European Green Deal priorities providing for a fair and just green transition, in particular the EU biodiversity strategy for 2030 and the EU Nature Restoration Regulation, which contributes to the EU's objectives on climate adaptation and mitigation, as well as the Kunming-Montréal Global Biodiversity Framework (GBF), successful proposals will contribute to the impacts of this Destination, notably to grow understanding of the biodiversity crisis and ecosystem services, leading policymakers and society to recognise the importance of protecting and restoring biodiversity, driving a path towards transformative change.
Project results are expected to contribute to all of the following expected outcomes:
- new knowledge to develop and accelerate pathways towards best available alternative socio-economic models that support biodiversity restoration and protection. These models should include adaptive legislative, governance, education and financing strategies, with potential applications of Generative AI to enhance research;
- decision makers (e.g. policy makers and public/private strategic decision makers) benefit from synthesised, systematised and prioritised knowledge on models that better integrate values of biodiversity and nature. Including valuation methods for assessing the benefits of restoration measures and the socio-economic distribution of impacts, tools and innovative market and governance instruments (e.g. potential incentives/capacity-building, including possible use of Generative AI-based tools), the application of environmental, social and ethical safeguards, and ensuring that biodiversity is continuously improved (e.g. through the non-deterioration principle) and to enhance community resilience to climate change;
- decision makers will have at their disposal information, tools, assessment strategies and metrics that allow for the continuous improved protection and restoration of biodiversity, alongside climate resilience, especially through enhanced climate adaptation. These should be integrated into socio-economic analytical frameworks, considering the quantitative and qualitative representation of social and economic variables in the short (up to 1 year), medium and long (5+ years) term, of the implications of applying such frameworks.
Scope:
The degradation of natural assets due to human activities, including climate change, emissions to air, water, and soil and land use intensification and change in Europe, and the subsequent cascading effects of biodiversity loss, have profound economic and social implications, including for our standards of living and immaterial aspects of quality of life. Biodiversity loss is increasingly recognised as a risk to macroeconomic and financial stability, affecting key institutions, countries and regions. Protecting and restoring ecosystems not only benefits biodiversity but also contributes to broader socio-economic objectives, such as human health and wellbeing, climate resilience, and particularly climate adaptation.
To address these trends, alternative socio-economic models can integrate biodiversity efforts into economic activities. The EU biodiversity strategy, GBF, and SDGs set ambitious biodiversity targets, but achieving them requires overcoming barriers in education, technology, society, economy, and governance. Numerous socio-economic models exist to achieve the necessary ecological, climate, economic, financial and social transition for biodiversity. These models need further analysis and development to be widely accepted and implementable. They play a key role in the transformative change called for by IPBES towards a nature positive society, for example through the deployment of nature-based solutions.
To contribute effectively to transformative change, it is crucial to deepen our understanding of the pathways to alternative socio-economic models. This includes better valuing the economic and social benefits that nature protection and restoration bring, beyond monetary valuation, and assessing the cost of inaction. Where possible, the actions should incorporate both quantitative and qualitative research, and the use of Generative AI could integrate new socio-economic data, aiding in model interpretation and action implementation.
In particular, 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[1]. 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).
Proposals should create synergies with other relevant initiatives, particularly Horizon 2020 and Horizon Europe projects, and foresee clustering activities, through the dedication of appropriate resources. Proposals should foresee cooperation with the EC Knowledge Centre for Biodiversity and the Science Service project BioAgora.
Proposals should involve contributions from the social sciences (including economics, sociology and educational science) and humanities (SSH) disciplines.
[1] Including the IPBES values assessment, the IPBES scenarios and models assessment, the IPBES nexus assessment and the IPBES transformative change assessment.
