An Adaptive Pathway Plan is a strategic framework designed to enhance resilience and adapt to long-term changes, particularly in the context of climate change. It involves identifying adaptation challenges and evaluating the effectiveness of various interventions over time. The key components include:
Pathways Mapping: The plan illustrates sequences of measures or investments to achieve defined objectives, allowing for adjustments as conditions change.
Thresholds and Tipping Points: The approach uses indicators to signal when a change in strategy is needed, ensuring flexibility in decision-making.
Removal of Uncertainty: The uncertainty with using climate risk prediction models for decision making has led us to use Resilience instead, therefore removing uncertainty from the decision-making process.
Stakeholder Engagement: Involvement of diverse stakeholders ensures that the pathways are context-sensitive and reflect local needs.
Key enabling factors include:
Flexibility: The plan must adapt to changing conditions and uncertainties, allowing timely adjustments as new information arises.
Stakeholder Engagement: Involving diverse stakeholders ensures the plan addresses various needs, fostering broader support.
Clear Triggers: Establishing specific signposts for when to adjust strategies enhances decision-making and responsiveness.
Integrated Approach: Aligning the plan with existing policies creates a cohesive strategy that is easier to implement.
Ongoing Monitoring: Continuous evaluation of the plan's effectiveness is crucial for informed adjustments and long-term success.
Key lessons learned include:
Contextual Adaptation: Tailoring the analysis to specific contexts and needs enhances effectiveness and addresses complexity.
Visualization Tools: Diverse visual representations, like metro maps and decision trees, improve understanding and communication of pathways.
Stakeholder Engagement: Involving multiple actors is crucial for addressing varied values and objectives, requiring robust governance structures to support ongoing monitoring.
Shared Experiences: Documenting and sharing experiences can facilitate wider adoption and application of adaptive pathways in practice.
Kassandra is a predictive system, and it does so by creating ‘scenarios’ in which key parameters are altered individually or collectively and the variation of the Resilience Index is calculated. This is done iteratively until an optimum level is reached.
In addition, the scenarios can be of two types, passive and active. Passive scenarios are those where parameters external to the system are altered, for instance climatic data, whilst active scenarios simulate actual adaptations or management strategies, such as extensive tree planting.
The scenarios are not a forecast but plausible alternative images of how the future can unfold, or, as defined by the IPCC - Intergovernmental Panel on Climate Change.
Key conditions include:
Flexible Parameter Adjustment: The ability to easily alter key parameters, both individually and collectively, is crucial for exploring various scenarios and their impacts on the Resilience Index.
Comprehensive Scenario Planning: Implementing a structured approach to scenario planning helps ensure that all relevant variables are considered in the analysis.
Real-Time Data Integration: Incorporating real-time data feeds allows for dynamic scenario adjustments, improving the relevance and accuracy of predictions.
Stakeholder Input: Involving stakeholders in defining scenarios ensures that they reflect real-world concerns and priorities, enhancing buy-in and applicability.
Importance of Accurate Models: Initial models that lacked precision led to unreliable scenario outcomes. Ensuring data models are validated and refined improves prediction quality.
Parameter Interdependencies: Altering parameters individually sometimes yielded unrealistic results. Recognizing and accounting for interdependencies among parameters enhances scenario realism.
Iterative Testing: Conducting iterative tests of scenarios helped identify flaws and areas for improvement. Early iterations often revealed unforeseen implications of parameter changes.
Stakeholder Engagement: Gathering input from stakeholders in defining scenarios was crucial. Scenarios that did not align with community concerns faced challenges in acceptance and implementation.
Clear Communication: Presenting scenario results clearly and visually improved understanding among stakeholders. Complex data without clear visualizations often led to confusion and misinterpretation.
In this stage Kassandra undertakes an analysis of resilience for all the entities within the Digital Twin based on twelve main Kassandra Parameters, hundreds of sub-parameters and thousands of relationships between these parameters. This highlights immediately areas where resilience might be lower and that might require urgent action.
For the successful implementation of Current Resilience Identification using Kassandra, key conditions include:
Comprehensive Data Collection: Gathering extensive data on the twelve main Kassandra Parameters and their sub-parameters is essential for accurate resilience analysis.
Robust Analytical Framework: Developing a strong analytical framework to process and interpret the complex relationships between parameters is critical for meaningful insights.
Integration of Diverse Data Sources: Ensuring the integration of varied data sources enhances the breadth and accuracy of the resilience assessment.
The key lessons learned during the implementation of Current Resilience Identification using Kassandra are:
Iterative Analysis: Initial analyses often uncovered unexpected relationships or gaps in understanding. Iterative approaches allowed for refinement and enhanced accuracy in identifying resilience factors.
Visualizations Aid Understanding: Effective visual representations of data relationships significantly improved stakeholder comprehension and engagement in the analysis process.
Kassandra creates or builds upon a Digital Twin of the asset to be studied that uses analysis and simulation tools to take a long-term and whole-system view of an environment.
For the successful implementation of Digital Twin Creation using Kassandra, key conditions include:
High-Quality Data: Accurate real-time data from various sources is essential for a reliable Digital Twin.
Robust Integration: Seamless integration with existing systems ensures comprehensive environmental views.
Interdisciplinary Collaboration: Engaging experts from diverse fields facilitates holistic modelling.
User Accessibility: A user-friendly platform encourages stakeholder engagement.
Scalability: The framework should be adaptable to future data sources and analytical needs.
Continuous Validation: Regularly updating the Digital Twin ensures its accuracy over time.
To avoid common pitfalls, we have found that there is a need to prioritize data quality, adopt flexible development practices, and encourage interdisciplinary collaboration.
Data Quality Matters: Ensuring high-quality, accurate data is critical. Inaccurate data inputs led to misleading simulations, undermining trust in the Digital Twin.
Iterative Development: Adopting an agile approach allowed for iterative improvements based on user feedback. Initial rigid processes led to missed opportunities for optimization.
Interdisciplinary Collaboration: Collaborating with experts from various fields enriched the modelling process. Attempts to work in silos often led to incomplete or unrealistic simulations.
Scalability Planning: Planning for scalability from the start ensured the Digital Twin could adapt to growing data and user demands without major redesigns.
Regular Validation: Establishing mechanisms for continuous validation helped maintain the Digital Twin’s relevance and accuracy.
Kassandra is a platform designed to enhance climate change decision-making through the power of generative AI. It facilitates the acquisition and consolidation of data from various sources, such citizen engagement workshops, archive searches, surveys, or even IoT devices and urban applications, allowing for a comprehensive view of a city's environmental landscape.
Data Acquisition: Kassandra collects diverse data related to climate, resource usage, and urban dynamics, acting as a central hub for this information,
Data Transmission: The platform efficiently transmits this consolidated data to a virtual environment, making it accessible and easily understandable for decision-makers.
Data Analysis: By integrating with advanced analytics tools, Kassandra supports real-time insights, enabling city planners to visualize trends and make informed decisions regarding resource management.
Scalability: The platform’s seamless horizontal scaling allows for accommodating increasing data needs as cities grow and evolve.
The conditions crucial for enabling the success of Kassandra as a platform for climate change decision-making:
Data Quality: Ensuring the accuracy, consistency, and completeness of data collected from various sources.
Interoperability: Facilitating seamless integration between Kassandra and existing urban systems and technologies.
Stakeholder Engagement: Involving community members, policymakers, and experts in the decision-making process to ensure diverse perspectives are considered.
Key lessons learned during the implementation of Kassandra as a climate change decision-making platform include:
Importance of Data Governance: Establishing clear protocols for data collection, storage, and sharing is essential. Inadequate governance can lead to data inconsistencies and trust issues among stakeholders.
Iterative Development: Adopting an agile approach allowed for continuous improvement based on user feedback and changing requirements. Rigid planning often led to delays and misalignment with user needs.
Collaboration with Stakeholders: Engaging local communities, policymakers, and technical experts throughout the process fostered buy-in and created a more relevant tool. Initial efforts that overlooked this collaboration faced challenges in acceptance.
Scalability Considerations: Planning for future growth from the outset ensured that the platform could handle increasing data loads and user demands without significant overhauls.
Malnutrition is the most important aspect of food and nutrition insecurity and comes in many forms: undernutrition, overnutrition, and micronutrient deficiencies, often referred to as “hidden hunger”.
Our transnational cooperation was largely based on personal contacts and larger efforts were dependent on external funding. The work for the preparation of the joint management plan has allowed us to structure the transnational cooperation and formalize it. All these measures will contribute to a more sustainable and long-term cooperation that isn´t so dependent on personal connections.
Now we have a better explanation of the tasks and organization of the transnational cooperation group, and we also included all municipalities in the area in the group.
An expert panel will help in management questions considering protection of World Heritage values and give valuable input to both site managers and the transnational cooperation group.
Personnel from different levels in the management authorities in both countries will meet regularly, and this is written into the management plan.
The transnational cooperation group agreed to meet more frequently while working on the management plan. We had many discussions and workshops about the mission and constitution of the group, and we have also discussed the transnational management with organizations not directly involved in it. Transnational cooperation has to be important for the involved organizations and there has to be a will to invest in it.
This kind of work takes time. By building cooperation over time, it is possible to move on from learning from each other to solving challenges together.
Cooperation can be very vulnerable if it is based on specific persons and personal connections, for example when persons in our cooperation group have changed and a new representative from the same organization did not have the chance to learn about the work from their predecessors. That´s why it is important to form routines for transferring knowledge within the involved organizations.
Another challenge is to find the right level of representation, to get persons involved who have both knowledge and right to make decisions. When involving many different organizations, it isn´t always possible to reach consensus in different matters, but the strength of the cooperation is in the discussions and in asking questions.
Another part of the success is that all work with the management plan (except the CVI project) was done as a part of our regular work. All things learned stays in the organizations when no short-time project staff have been participating. It took a long time, but it was worth it.
Linking SOUV, World Heritage values and attributes
Hilly landscape in the High Coast.
Erik Engelro
To be able to write a joint management plan, we need to agree on what we have to manage. A shared understanding of the key values and attributes is crucial. An important step for us was to facilitate meetings that brought the national geological surveys in both Sweden and Finland together so they could discuss land uplift and ice age traces and consider the site in its totality. These discussions gave important insight on the geological attributes of the site.
To get a clear overview of the key values of the property, excerpts from the SOUV for High Coast/Kvarken Archipelago were analysed and grouped together as seven key values. Attributes were listed for each key heritage value. This process gave a clear connection between the SOUV in the everyday work with WH management. It makes the abstract concept of World Heritage more tangibly associated to its management.
The analysis of the SOUV required involving professionals from different disciplines and getting them to discuss about what makes the WHS special.
This step was first explored in the Climate Vulnerability Index (CVI) Assessment that was carried out at the site. The work done in the CVI project was crucial to linking SOUV, values and attributes together and it has been described in a separate PANORAMA solution (link below)
As a part of the CVI process we assessed the current condition and recent trend for the excerpts from our SOUV. This was done in a workshop with participants from both countries. The assessment helps in prioritization in WH management.
In a transnational or serial WHS is it important to get specialists from different fields and different parts of the property to work together. We´ve learned that it is of great value to assess current condition and recent trend for WH values together with other stakeholders and specialists, as controversial results may raise many questions and perhaps skepticism. It is good to be able to show that the results are based on systematic work taking different views into consideration. And because of this broad base we know we can trust our results and conclusions.
It was easy to list the most important attributes in the periodic reporting 2023, but that wouldn´t have been the case if the periodic reporting would have been prior to the work we´ve done with SOUV, values and attributes. A clear and structured overview of values and attributes, and a better understanding of our SOUV is also helpful in interpretation, communication, and monitoring.
Accessible information is also beneficial for people working with planning and permits in the area.
The High Coast (Sweden) became a World Heritage Site in 2000, and 2006 the World Heritage became a transnational site with the addition of the Kvarken Archipelago (Finland). Since the nomination process wasn’t done together, there was no clear cooperation structure in place. In 2008, a transnational cooperation group was formed with representatives from municipalities and authorities from the involved regions. Since the expansion of the World Heritage site to include Kvarken Archipelago, the cooperation between management authorities has progressively increased. The level of cooperation has varied a bit, mostly due to personnel changes. It takes time to build a team.
There has been several larger joint projects, financed by Interreg, an EU fund that promotes cross-border cooperation. The last one was LYSTRA from 2018-2020. In this project, Metsähallitus and the County Administrative Board started to work very close together. Now the cooperation between the site managers and other staff is an essential part of the work and a large contributing factor to the joint management plan. The project produced the first joint plan, which was an interpretation plan for the whole site.
Sweden and Finland are very similar countries, which makes building cooperation easier. We found these following factors important:
A mindset that cooperation is important, and something that is worth to use resources for in the organizations at large.
A stable and predictable funding.
Resources for projects, both in the own organization to be able to run large projects, but also an availability of appropriate project funds to apply for.
Developing a consensus of what is important.
There were many lessons learned and knowledge that can be shared between organisations and there is a lot to learn from each other.
It was important to build on the different strengths of each organization to increase efficiency.
It is also important to involve the managers and directors in the cooperation, so that they also see the synergistic effects of collaborative planning. In our organizations the site managers are quite isolated and managing World Heritage is a small part of what our organizations do. So, with the strengthened cooperation, we have in fact created our own little team, albeit with the other team member in a different country.
A final lesson that we have learnt is that it is important to be a bit flexible to make things work in both countries with different management systems.
