Subject Area: Adaptive Governance for Regenerative Social-Ecological Systems

Building communities that can learn their way into a different future

Adaptive governance remains essential for navigating uncertainty, ecological feedback and multiple centres of knowledge and authority. The argument developed here is that governance must also protect and renew the human, social, ecological and institutional capacities from which future adaptation emerges. Regenerative agriculture offers a living example: not a universal formula, but an active learning community that observes the place, shares experience, experiments, reflects and co-creates its future.

The challenge has changed

Adaptive governance developed as a response to the limitations of centralised, command-and-control strategies in managing complex social-ecological systems. Its significance lies in recognising uncertainty, decentralised knowledge, interactions across scales, ecological feedback, and the need for continual learning. Folke et al. (2005)outlined four key interconnected needs: understanding ecosystem dynamics, integrating this knowledge into adaptive management, fostering flexible institutions and multilevel governance, and preparing for disturbances, uncertainties, and surprises.

Those requirements remain valid. The issue is not that adaptive governance has failed or should be discarded. It is that the condition of many social-ecological systems has changed. Where ecological function, social trust, institutional legitimacy or organisational capability have already been depleted, adaptation may help a system persist without restoring the capacities that make future flourishing possible. Resilience may include renewal and transformation, but in practice it is often interpreted as the ability to absorb disturbance and retain essential function. Regeneration makes the direction of travel explicit: governance should not only help systems cope with change; it should help renew their capacity to create life, wellbeing, knowledge, agency and future options (Buckton et al., 2023; Das et al., 2026).

Regenerative governance should be seen as an expansion of adaptive governance, not as a competing approach. While adaptive governance emphasises learning, flexibility, polycentric coordination, and responding to feedback, regenerative thinking explicitly considers the health, vitality, and co-evolutionary capacity of the broader system. The practical question becomes:

Does this governance system increase or diminish the capacity of the wider living system – and of future generations – to adapt, survive and flourish?

From sustainability to regenerative capacity

Sustainability has evolved from focusing solely on resource conservation and harm reduction to encompassing social justice, ecosystem health, and managing interconnected social-ecological systems. Regenerative methods incorporate these concerns but emphasise strengthening living systems’ ability to heal themselves rather than just minimising damage. Gibbons (2020) describes regenerative sustainability as the goal of continuously boosting overall system health and wellbeing. Meanwhile, Mang and Reed (2020) differentiate between regenerative design, which aims to improve a system, and regenerative development, which focuses on building the local capacity so communities and environments can keep co-evolving beyond the initial changes.

This distinction is important. A successful project, policy, or technology might restore a wetland, enhance a supply chain, or redesign an operating model. However, unless stakeholders also build the knowledge, relationships, judgment, and institutional capacity to sustain learning, these improvements may be temporary. Regeneration is not just an end result; it is an ongoing capability.

Regenerative literature varies in approach. For instance, Fullerton (2015) describes regenerative capitalism by translating living-systems concepts into principles like right relationship, holistic wealth, circulation, resilience, and place. While these serve as helpful conceptual guides, broad principles alone do not make a system truly regenerative. They need governance structures, roles, feedback loops, and practical evidence to be effective. Without these mechanisms, regenerative language risks becoming mere aspiration, branding, or a moral stance rather than a concrete foundation for action.

Regenerative agriculture as a living example

Regenerative agriculture is crucial here because it emphasises the underlying issue. While industrial agriculture can sustain high yields over time, it does so at the expense of soil health, biodiversity, water cycles, local knowledge, and community resilience. The visible outcomes might appear acceptable, even as the foundational capacity for future productivity diminishes.

Regenerative agriculture is different: it views a farm as a living social-ecological system supported by extensive biological networks that traditional performance measures mostly miss. For example, arbuscular mycorrhizal fungi form symbiotic relationships with about 70% of plant species, creating vast underground networks for nutrient and carbon exchange. Stewart et al. (2026)estimate these networks transfer around one billion tonnes of carbon into soils annually. This research reveals the scale of the biological infrastructure beneath farms and underscores that understanding or managing a farm cannot be achieved by focusing solely on inputs, outputs, or isolated variables.

Farmers need to recognise patterns, align with ecological processes, respond to delayed effects, and adapt practices based on local conditions. The goal extends beyond simply maintaining yields or minimising harm; it aims to enhance the land, farming communities, and the broader food system’s resilience, productivity, and adaptability. Importantly, regenerative agriculture does not follow a single prescribed method. According to Gordon et al. (2023) nine discourses and four ongoing tensions involve holism, power and equity, definitions, and how far practices deviate from industrial agriculture. This diversity is both a strength and a challenge: it fosters inclusivity among different backgrounds and practices but also opens the door to co-optation and greenwashing.

The deeper lesson is that the regenerative agriculture community is an active learning community. Farmers, advisers, researchers, Indigenous knowledge holders and local networks compare experiences, experiment, observe consequences and revise practice. Seymour and Connelly (2023) found that peer networks, shared identity, care, reflection and changing relationships with land were central to the transformational potential of regenerative agriculture. The community is not simply implementing a completed model. It is learning its way towards different relationships among production, place, livelihood and ecological health.

Build communities that can learn their way into a different future.

This does not romanticise the field. Evidence for specific practices varies by location, climate, enterprise, and time frame. Commercial interests may adopt the terminology without altering extractive practices. Communities can become isolated, silence dissent, or favour dominant voices. The significance of regenerative agriculture is not in asserting universal success but in demonstrating how local learning, observation, shared goals, and stewardship can develop an alternative to industrial simplification.

Translating the lesson into organisations

The original argument in Adapt, Survive and Flourish was that the living-system lessons evident in regenerative agriculture can be applied to organisations more broadly. The translation is not literal. Organisations do not have soil microbiomes, and ecological metaphors should not be used to obscure human conflict, power or accountability. The useful transfer lies in the underlying pattern: current performance depends on capacities that can be cultivated, neglected or depleted.

Regenerative agriculture	Organisational translation
Restore soil health and biological activity	Restore human capability, trust, knowledge flows and the conditions for learning
Protect biodiversity and functional variety	Protect cognitive, cultural, professional and experiential diversity
Read local conditions and patterns of place	Attend to Gemba (the place where work is done), stakeholder experience and the actual conditions of work
Use ecological feedback and delayed consequences	Connect action to operational, social and environmental consequences
Reduce dependence on damaging external inputs	Build internal capability and reduce dependency created by hollowing out judgement and knowledge
Share learning through farmer networks	Develop communities of practice and cross-boundary learning networks
Steward the future fertility of the land	Steward the future potential of capabilities, relationships, knowledge and institutions
Regenerate the wider food system, not only the farm	Avoid local optimisation and govern the organisation as a participant in wider social-ecological systems

An organisation can keep achieving targets while depleting the foundational conditions necessary for future success. Trust can be exhausted without renewal. Skilled personnel may depart, leaving their knowledge untapped. Standardisation might eliminate variability, which is essential for learning and innovation. Focusing on short-term efficiency can reduce redundancy, weaken relationships, and undermine local judgment. Regenerative governance reveals these forms of depletion and holds them accountable.

The Adaptive Governance Cycle

Figure 1: Adaptive Regeneration Governance Cycle

The Adaptive Governance Cycle operates within a containing field of purpose, ethics and governance. Guiding Principles continually shape how Needs and Opportunites are realised by Process and Practice, which encounter reality at Gemba and generate Consequences. These initiate reflection and learning through the practice of Hansei. Organisational Awareness sits at the centre as a live sensing and sense-making hub, continuously responding to signals across the system.

Purpose, Ethics and Governance

Purpose, Ethics and Governance provide a containing field. They collectively guide decision making at all steps. Purpose provides direction, Ethics the boundary for acceptable behaviour and practice, and Governance the capability to develop, articulate and adjudicate over the Guiding Principles.

Organisational Awareness Hub.

Like an orb weaver spider, the hub sits at the centre and is attuned to and sensitive to signals produced at each node. It evaluates the signals and provides specific information to one or more of the nodes.

The two paths

Most adaptation occurs through normal distributed response within the field. This is the standard Gemba learning cycle. Occasionally, something will happen in the external environment that requires a change to an existing principle or a new one. For example, some organisations will now have guiding principles on the use of AI for research or document development. Such principles would have been unheard of in 1990.

Governance as a learning architecture

Governance is often viewed as oversight, control, compliance, and assurance. While these functions are essential, particularly when interests conflict, risks are significant, or harm could be shifted onto powerless groups, governance also influences an organisation’s capacity to notice, discuss, learn, and adapt. It affects whether uncomfortable information can be shared, if local judgment is honoured, and whether the impacts of decisions affect those who made them.

Martin et al. (2025)describe the policy-practice gap as a dual challenge of organisational learning. Practices must adapt to legitimate policy requirements, but policy must also adapt to the complexity and knowledge revealed through practice. A governance system dominated by deployment can suppress variation, local adjustment and discovery. A system dominated by local discovery can fragment, lose coherence or fail to implement necessary standards. The task is mutual adaptation over time.

This requires deliberate spaces for interplay between policy and practice: forums in which people across professional, hierarchical and organisational boundaries can compare work-as-imagined with work-as-done, identify tensions, challenge assumptions and revise both action and policy. Martin et al. propose shared purpose, interactive process management, participative centralisation, T-shaped capability and collaborative trust as design principles for balancing deployment and discovery.

This balance is also visible in contemporary governance work outside organisations. Søndergaard et al. (2023), examining alternative proteins, warn against optimising one objective while displacing harm into nutrition, livelihoods, inequality or cultural systems. Their food-environment-livelihood trilemma shows why transitions must be managed as open-ended, socially embedded processes rather than treated as technically predetermined solutions. Das et al. (2026) similarly connect ecological restoration with safety, circularity, livelihood resilience, participatory governance and institutional learning. These papers are useful precisely because they bring regenerative ambition back to trade-offs, operational conditions and accountable governance.

Adaptive capacity: human capital, social capital and social cohesion

Adaptive capacity does not reside in plans or technology alone. It depends on people who can interpret changing conditions and on relationships that turn their knowledge and effort into collective action. In Adapt, Survive and Flourish, adaptive capacity is expressed as the interaction of human capital and social capital (Malcolm, 2025).

Adaptive Capacity = Human Capital + Social Capital

Human capital

Human capital encompasses knowledge, skills, experience, judgment, creativity, confidence, and the ability to act. Regenerative governance does not view these qualities as assets to be tapped; instead, it fosters their growth through participation, guided practice, meaningful responsibilities, reflection, and understanding of consequences. Diversity is crucial because a system that includes various types of knowledge and abilities maintains more options when circumstances evolve (Buckton et al., 2023).

Social capital

Social capital includes networks, trust, reciprocity, shared language and the willingness to cooperate. Folke et al. (2005) place social networks and bridging relationships at the centre of adaptive governance because they connect knowledge, actors and authority across levels. Social capital turns individual capability into coordinated adaptive capacity. It also reduces the transaction cost of learning: people share uncertainty, unfinished ideas and failure more readily where relationships are trustworthy.

Social cohesion

Social cohesion extends beyond social capital, encompassing the quality of social relations, a sense of belonging, and dedication to the common good, as Schiefer and van der Noll (2017) identify. These aspects are vital during regenerative transitions, where disagreements often arise over purpose, livelihood, risk, authority, identity, and the distribution of costs and benefits. While strong bonds within groups can facilitate learning, they may also exclude outsiders or suppress legitimate differences. Therefore, regenerative governance requires bonding within communities, bridging across differences, and linking communities with institutions. Human capital gives individuals the ability to contribute, social capital supports collective effort, and social cohesion keeps diverse communities connected while shaping an alternative future.

Roles that make regenerative governance real

Regenerative governance cannot depend on goodwill alone. Responsibilities for capability, knowledge, principles and consequences must be visible and formally supported. Two roles are particularly important: Capability Owners and Stewards.

Capability Owner

A Capability Owner is accountable for the continuing health, coherence and future potential of a capability across organisational boundaries. The role extends beyond current service levels or process performance. People, relationships, knowledge, data, technology, routines, partners, and the social-ecological systems on which it depends sustain a capability.

A Capability Owner should:

maintain line of sight from purpose and governance principles to operational reality and consequence;
understand the people, knowledge, relationships, information, technology and external dependencies that enable the capability;
monitor both current performance and the condition of the underlying human, social, ecological and institutional capital;
identify depletion, fragility, harmful dependency, local optimisation and transferred consequence;
support investment in learning, succession, diversity, communities of practice and trusted information;
ensure that change strengthens rather than fragments the capability;
connect experience from Gemba to policy, strategy and investment decisions; and
leave the capability with greater capacity, knowledge and future options than it inherited.

The Capability Owner is not a central controller. The role provides coherence and accountability while enabling local agency and informed judgement. Its central question is: is this capability becoming more capable, or are we consuming the foundations on which it depends?

Stewards

Stewards are keepers of truth, meaning and continuity. They protect the integrity of principles, knowledge, relationships, place and future consequence within a defined domain. Stewardship is not the passive maintenance of documents. It is the active stewardship of shared understanding.

Stewards should:

co-create, interpret and maintain principles with those who apply them and those affected by them;
connect formal policy with lived experience, local knowledge and work-as-done;
make weak signals, contradictions and unintended consequences visible;
preserve uncomfortable knowledge rather than allowing it to be sanitised or withdrawn;
help decision-makers interpret competing principles and trade-offs in context;
recommend change when experience shows that policy, standards or assumptions are no longer fit for purpose;
protect regenerative intent from dilution, symbolic compliance and greenwashing; and
maintain continuity across projects, leadership changes and reporting cycles.

Davis et al.(1997) offer a valuable perspective as a counterbalance to governance models based solely on assumptions of opportunism and control. Their stewardship theory acknowledges that individuals can be intrinsically motivated, identify with collective goals, and act in the organisation’s best interests when structures foster trust, authority, and meaningful responsibility. They do not claim that stewardship is always suitable or that it eliminates agency risks. Instead, their key conclusion is nuanced: governance should distinguish between situations that require monitoring and control and those where excessive oversight undermines responsibility, motivation, and contribution.

The institutional role of Steward proposed here does not rest on blind trust. It combines explicit responsibility, transparency, access to evidence, dialogue, and appropriate assurance, with sufficient agency to act. Stewardship becomes credible when it is embedded in governance, recognised in workloads and measures, and linked to decision rights.

Guiding principles for adaptive regenerative governance

Govern for the vitality of the whole. Evaluate decisions by their effects on the organisation and the wider social-ecological systems on which it depends. Do not improve one component by invisibly transferring harm, risk or depletion elsewhere.
Treat adaptation, resilience and regeneration as complementary. Use adaptive governance to learn and respond, resilience to preserve essential function, and regenerative intent to restore depleted capacity and expand future options. The appropriate emphasis will vary by context.
Build communities that can learn their way into a different future. Complex transitions cannot be fully specified in advance. Create communities able to observe, inquire, experiment, reflect and adapt together while retaining disciplined accountability.
Anchor action in shared purpose and the common good. Purpose should provide a practical orientation for choices, not a promotional statement. Legitimate differences in interest remain, but shared purpose creates a basis for collective contribution and social cohesion.
Place agency close to knowledge and consequence. Give people near the work, community and ecological reality sufficient authority, information, time and capability to respond intelligently. Connect local agency to wider coordination and accountability.
Integrate deployment with discovery. Implement legitimate policy and standards while allowing practice to reveal limitations, unintended effects and better alternatives. Govern the policy-practice relationship as a continuing process of mutual adaptation.
Protect diversity and develop capability. Maintain ecological, cognitive, cultural, professional and experiential diversity. Invest in human capital, T-shaped capability, succession, communities of practice and the ability to work across boundaries.
Steward relationships, knowledge and future options. Treat trust, tacit knowledge, social networks, biodiversity and institutional memory as productive capacities requiring deliberate care, renewal and ownership.
Learn from consequence. Measure more than intention, activity and compliance. Return social, ecological and operational consequences to decision-makers and use them to revise assumptions, policies and practice.
Balance trust with appropriate control. Design controls to enable reliable work, transparency and learning rather than to presume universal bad faith. Use stronger control where interests diverge or harm is material, but recognise that coercive systems can suppress judgement and responsibility.
Work across boundaries and scales. Use polycentric and bridging arrangements to connect local knowledge, organisational capability, public authority, community interests and ecological scales. Neither centralisation nor decentralisation is sufficient on its own.
Maintain regenerative integrity. Continually test whether regenerative language is changing underlying relationships, incentives, capability and outcomes. Reject symbolic adoption, selective measurement and claims that cannot survive scrutiny.

Questions for reflection

What capacities does this system currently consume faster than it renews?
Whose knowledge and experience are missing from governance discussions?
Where is the greatest gap between policy and work-as-done?
Do current controls improve reliability, or do they suppress judgement and learning?
Which relationships, capabilities and ecological dependencies lack an accountable owner or steward?
Are our measures detecting whole-system consequence or only local performance?
Does this decision strengthen human capital, social capital and social cohesion?
What future options are being created, narrowed or foreclosed?
Are we maintaining an existing trajectory, or building the capacity to create a different one?

Closing proposition

Regenerative governance does not promise harmony or eliminate conflict, uncertainty, or the need for control. Instead, it represents a disciplined commitment to govern in a way that nurtures the renewal of the essential capacities underpinning future life, legitimacy, and performance. An example of this in practice is regenerative agriculture: a diverse community working within a living system, learning from their environment and consequences, sharing knowledge, questioning assumptions, and co-creating an evolving future. The organisational adaptation is not about copying farming methods but about developing governance systems that safeguard the same core capability.

Regenerative Governance positions communities to learn their way into a different future.

References

Buckton, S. J., Fazey, I., Sharpe, B., Om, E. S., Doherty, B., Ball, P., Denby, K., Bryant, M., Lait, R., & Bridle, S. (2023). The Regenerative Lens: A conceptual framework for regenerative social-ecological systems. One Earth, 6(7), 824–842.

Das, A., Mishra, S., & Bauri, K. P. (2026). Regenerative resource governance for sustainable social development: integrating safety, circularity, and community stewardship with insights from the Chilika Lagoon system. Green Technology, Resilience, and Sustainability.

Davis, J. H., Schoorman, F. D., & Donaldson, L. (1997). Toward a stewardship theory of management. Academy of Management Review, 22(1), 20–47.

Folke, C., Hahn, T., Olsson, P., & Norberg, J. (2005). Adaptive governance of social-ecological systems. Annu. Rev. Environ. Resour., 30, 441–473.

Fullerton, J. (2015). Regenerative capitalism. Capital Institute: Greenwich, CT, USA, 1–120.

Gibbons, L. V. (2020). Regenerative—The new sustainable? Sustainability, 12(13), 5483.

Gordon, E., Davila, F., & Riedy, C. (2023). Regenerative agriculture: a potentially transformative storyline shared by nine discourses. Sustainability Science, 18(4), 1833–1849. https://doi.org/10.1007/s11625-022-01281-1

Malcolm, R. (2025). Adapt, Survive and Flourish. Green Hill Publishing.

Mang, P., & Reed, B. (2020). Regenerative development and design. In Sustainable built environments (pp. 115–141). Springer.

Martin, J., Ellström, P.-E., Wallo, A., & Elg, M. (2025). Bridging the policy-practice gap: a dual challenge of organizational learning. The Learning Organization, 32(7), 18–34.

Schiefer, D., & Van der Noll, J. (2017). The essentials of social cohesion: A literature review. Social Indicators Research, 132(2), 579–603.

Seymour, M., & Connelly, S. (2023). Regenerative agriculture and a more-than-human ethic of care: a relational approach to understanding transformation. Agriculture and Human Values, 40(1), 231–244.

Søndergaard, N., Fernandes, J. F. A., Potent, J., Karl, K., Furtado, M., & Baethgen, W. (2023). A governance framework to manage the food-environment-livelihood trilemma of alternative proteins. One Earth, 6(7), 843–853.

Stewart, J. D., Bisot, C., Cargill, R. I., Van Nuland, M. E., Hawkins, H.-J., Oyarte Galvez, L., Klein, M., van Son, M., Terry, V., & Paré, L. (2026). Global density and biomass of arbuscular mycorrhizal fungal networks. Science(6803), 1171–1176.