Biodiversity science and policy need more model intercomparisons – Nature

Report on Biodiversity Model Intercomparison Projects (BMIPs) and Their Role in Achieving Sustainable Development Goals

Introduction

The accelerating decline of global biodiversity poses a significant threat to sustainable development worldwide. To effectively halt this decline, robust models capable of projecting future biodiversity changes are essential for informing policy decisions. Drawing parallels from the success of climate model intercomparison projects, biodiversity model intercomparison projects (BMIPs), developed over the past decade, present a promising approach to enhance biodiversity science and policy. This report emphasizes the critical role of BMIPs in supporting the United Nations Sustainable Development Goals (SDGs), particularly those related to life on land (SDG 15) and life below water (SDG 14).

Overview of Biodiversity Model Intercomparison Projects (BMIPs)

Purpose and Framework

BMIPs provide a coordinated and standardized experimental framework that enables systematic comparison of biodiversity models. This standardization ensures consistency in model inputs, scenarios, and outputs, thereby enhancing the reliability and comparability of biodiversity projections.

Applications and Policy Support

• Addressing general biodiversity modelling questions to improve scientific understanding.
• Supporting national to international actions aimed at achieving the goals and targets of the Kunming–Montreal Global Biodiversity Framework, which aligns with SDG 15 (Life on Land) and SDG 14 (Life Below Water).

Key Components for Effective BMIPs

Historical Benchmark Datasets

Establishing historical benchmark datasets is vital for validating biodiversity models. These datasets enable:

1. Impact attribution by linking biodiversity changes to specific drivers.
2. Cross-system understanding of predictive performance and model complexity.
3. Enhanced confidence in model predictions, facilitating informed decision-making aligned with SDG 15.

International Collaboration and Governance

• Strengthening international collaboration, coordination, and knowledge sharing to increase the relevance, transparency, and impact of BMIPs.
• Fostering broader community engagement to incorporate diverse perspectives and expertise.
• Establishing clear governance structures to oversee modelling activities, infrastructure, and community consultation.
• Developing strategies for long-term funding to ensure sustainability and effectiveness of BMIPs.

Advancing BMIPs: Lessons from Climate Model Intercomparison Projects

Climate model intercomparison projects have been instrumental in advancing mechanistic understanding of climate change and its anthropogenic drivers. BMIPs can emulate this success by:

• Adopting mechanistic modelling approaches that capture ecological processes.
• Ensuring open access to modelling tools and data to promote transparency and reproducibility.
• Investing strategically in data infrastructure and modelling capabilities to support robust biodiversity projections.
• Facilitating international coordination to align biodiversity modelling efforts with global sustainability agendas, including the SDGs.

Contribution to the Kunming–Montreal Global Biodiversity Framework and SDGs

BMIPs are positioned to make meaningful contributions to the Kunming–Montreal Global Biodiversity Framework by providing robust projections that inform policy and action planning across various spatial scales and scenarios. This directly supports the achievement of multiple SDGs:

• SDG 14: Life Below Water – by improving understanding and management of marine biodiversity.
• SDG 15: Life on Land – by enhancing projections of terrestrial biodiversity changes and informing conservation strategies.
• SDG 13: Climate Action – by linking biodiversity changes to climate drivers and supporting mitigation and adaptation efforts.

Recommendations for Future Development

1. Adopt mechanistic and process-explicit modelling approaches to improve the accuracy and applicability of biodiversity projections.
2. Develop and maintain comprehensive historical benchmark datasets to validate models and attribute biodiversity changes to specific drivers.
3. Establish robust governance frameworks to coordinate BMIP activities, ensure community engagement, and secure sustainable funding.
4. Promote open access to modelling tools and data to facilitate collaboration and transparency.
5. Enhance international coordination and knowledge sharing to align BMIP efforts with global biodiversity and sustainability targets.

Conclusion

To effectively address the global biodiversity crisis and support the Sustainable Development Goals, particularly SDG 14 and SDG 15, biodiversity science and policy must embrace model intercomparison projects. Strategic investments in data infrastructure, modelling capabilities, and global governance are essential to realize the full potential of BMIPs. Concerted international coordination, increased funding, and proactive knowledge sharing will enable BMIPs to provide robust, actionable projections that guide biodiversity conservation and sustainable development worldwide.

1. Sustainable Development Goals (SDGs) Addressed or Connected to the Issues Highlighted in the Article

1. SDG 13: Climate Action
   • The article discusses climate models and their role in understanding anthropogenic climate change and its impact on biodiversity.
   • It highlights the importance of biodiversity model intercomparison projects (BMIPs) to project biodiversity changes under climate scenarios.
2. SDG 15: Life on Land
   • The article focuses on halting biodiversity decline, projecting biodiversity trajectories, and supporting the Kunming–Montreal Global Biodiversity Framework.
   • It emphasizes biodiversity conservation and ecosystem services through improved modeling and data infrastructure.
3. SDG 17: Partnerships for the Goals
   • The article stresses the need for international coordination, collaboration, governance structures, and knowledge sharing to enhance biodiversity modeling efforts.
   • It calls for strategic investments and global governance to support BMIPs.

2. Specific Targets Under Those SDGs Identified Based on the Article’s Content

1. SDG 13: Climate Action
   • Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters.
   • Target 13.3: Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning.
2. SDG 15: Life on Land
   • Target 15.5: Take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity, and protect and prevent the extinction of threatened species.
   • Target 15.8: Introduce measures to prevent the introduction and significantly reduce the impact of invasive alien species on land and water ecosystems.
   • Target 15.a: Mobilize significant resources from all sources to conserve and sustainably use biodiversity and ecosystems.
3. SDG 17: Partnerships for the Goals
   • Target 17.6: Enhance North-South, South-South, and triangular regional and international cooperation on and access to science, technology, and innovation.
   • Target 17.16: Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships that mobilize and share knowledge, expertise, technology, and financial resources.

3. Indicators Mentioned or Implied in the Article to Measure Progress Towards the Identified Targets

1. Indicators Related to Biodiversity Modeling and Projections
   • Use of standardized, historical benchmark datasets to validate biodiversity models and enable impact attribution.
   • Measurement of global and regional biodiversity trajectories and their uncertainties through BMIPs.
   • Indicators of model performance, predictive accuracy, and complexity to assess confidence in biodiversity projections.
2. Indicators Related to Governance and Collaboration
   • Existence and effectiveness of governance structures overseeing BMIPs, including community consultation and long-term funding mechanisms.
   • Level of international coordination, collaboration, and knowledge sharing among biodiversity modeling communities.
   • Accessibility and openness of modeling tools and data to the broader community.
3. Indicators Supporting the Kunming–Montreal Global Biodiversity Framework
   • Robust projections supporting policy and action planning across spatial scales and scenarios.
   • Progress in achieving biodiversity conservation goals through informed decision-making based on model outputs.

4. Table of SDGs, Targets, and Indicators Relevant to the Article

Source: nature.com