Core Evaluation Criteria
Proposals will be assessed based on the standard Horizon Europe criteria:
- Excellence: Quality of the research, methodology, scientific advancements, and novelty.
- Impact: Potential contribution to expected outcomes, benefits for target stakeholders, and the overall societal, economic, and environmental impact.
- Quality and Efficiency of Implementation: Soundness of the work plan, appropriateness of resources, quality of the consortium, and effective risk management.
Specific Scoring Factors for this Topic
- Contribution to expected outcomes: The extent to which the project contributes to updated knowledge and new tools for restoration, and the integration of nature restoration into climate and land-use policy models.
- Model development: Capacity to develop a dynamic ecosystem model simulating processes and interactions across scales, drawing from literature, existing datasets, and demonstration cases.
- Ecological reference values: Ability to estimate ecological reference values tailored to specific ecosystems and contexts, including climate change.
- Synergy identification: Prioritization of ecosystems where restoration offers synergies with climate change mitigation/adaptation, land degradation neutrality, or disaster risk prevention.
- Data handling: Approach to addressing data gaps, ensuring data is FAIR (Findable, Accessible, Interoperable, Re-usable), and considering the European Open Science Cloud (EOSC).
- Practical guidance: Formulation of practical guidelines for practitioners, including addressing invasive alien species.
- Model improvement: Capacity to improve and expand existing climate and land-use policy models by coupling new functionalities.
- Collaboration and synergy: Demonstrated plans to build on relevant existing projects, collaborate with other selected projects under this topic, and engage with the EC Knowledge Centre for Biodiversity and BioAgora.
- Scientific grounding: Integration of knowledge from IPBES assessment reports and potential for providing timely information for future reports.
- Transparency: Commitment to the highest standards of transparency and openness for models (assumptions, protocols, code, data).
- Citizen engagement: Appropriateness and planned use of Citizen Science approaches for data production and analysis.
- Interdisciplinarity: Integration of interdisciplinarity and trans-disciplinarity, including contributions from Social Sciences and Humanities (SSH).
- Inclusivity: Attention to gender and other social categories to ensure a socially just transition.
- Stakeholder engagement: Plans for citizen and stakeholder engagement, potentially through living labs.