The methodological challenge of evaluating agroecological transitions stems from their inherently multidimensional and multiscale nature. A comprehensive review by Darmaun et al. (2023) evaluated 14 existing multiscale assessment methods (with academic publications in French and English) against five key requirements: local adaptability, social interaction analysis, conceptual clarity, temporal dynamics, and bottom-up participation. Analyses revealed that no single existing method currently covers all five criteria, often forcing a trade-off between standardizing for benchmarking and adapting for local settings. This underscores the need for novel interdisciplinary frameworks that can create bridges between different dimensions of sustainability. Moreover, agroecological transitions hold significant promise for sustainability gains, but when implemented without attention to social context and the human condition, they risk reproducing the mistakes of past industrial agricultural transformations (HLPE, 2019).

One strategy for bridging dimensions and avoiding past mistakes is to embed well-being indicators, both scientifically validated and community-defined, into agroecological innovation from the onset Gratton et al., (2024). Monitoring well-being alongside agronomic outcomes could allow practitioners to detect social or psychological stressors early and adjust interventions accordingly, while also permitting the incorporation of variable definitions of well-being set by the communities themselves. Moreover, attention to well-being can help agroecological initiatives establish a clear and integrative understanding of what success means, providing actionable indicators to guide socio-ecological reorganization through resource allocation and investment in the specific social and ecological components that brought about the said success.

Agroecological transitions are not only technical or ecological processes; they are profoundly social and psychological. While agroecology emphasizes sustainability, resilience, and justice in food systems, its success ultimately depends on the capacity and willingness of individuals and communities to enact and sustain new practices (Marchand et al., 2014; Sanchez-Mata et al., 2026). In this context, well-being is not a secondary outcome but a central goal and a primary driver of agroecological transformation (Matson et al., 2016). Individual well-being and self-awareness, community well-being and other-centeredness, as well as the agroecological well-being of nature as a whole are all strongly interdependent (Bezner Kerr et al., 2023; Buckton et al., 2023), which suggests that they must be jointly cultivated to be sustainable.

This dynamic is critical. Well-being acts as a driver for systemic change by enabling crucial social processes. Place-making research, for example, suggests that transitions happen through social processes, as they involve the construction of institutions that foster self-governance and social cohesion necessary for overall systems' change. The active and deliberate building of transformative capacities (collective capacity-building, self-efficacy, self-directedness, and new narratives) in specific places is essential to transforming socio-ecological systems (Horlings et al., 2020). Transitions toward sustainable food systems have been shown to be more effective and enduring when grounded in improvements to biopsychosocial health, social cohesion, and a shared sense of meaning and agency (Méndez et al., 2013; Gliessman, 2016), often realized through local processes that assert a multi-dimensional view of good farming and empower collective agency (Darnhofer et al., 2016; Strauser et al., 2022; Strauser and Stewart, 2024).

Progress toward greater well-being enhances the adaptive capacity of farmers and rural communities and is linked to essential biopsychosocial resources, such as efficacy, resilience, and motivation, that are needed to navigate the uncertainties and trade-offs inherent to systemic change (Keshavarz and Masoomi, 2026). Cloninger's biopsychosocial personality model supports the cultivation of such resources. By highlighting three character traits—self-directedness, cooperativeness, and self-transcendence—this framework clarifies which psychological capacities are most crucial for adaptive change and collective action during the challenges of the 21st century (Cloninger, 2013). For instance, self-directed individuals are more likely to initiate and persist in pro-environmental practices, exercising agency in the face of challenges. Cooperativeness fosters collaboration and trust within farming communities, enabling people to work together toward common sustainability goals. Self-transcendence contributes to a sense of connectedness to nature and future generations (Cloninger, 2013), values that together underpin the long-term orientation of agroecology and the canonical definition of sustainability (Brundtland, 1987). In other words, individuals who have higher scores in these character traits, as measured by the Temperament and Character Inventory (TCI), are better equipped to embrace agroecological practices that require personal change, collective action, and a forward-looking mindset.

However, as studies in epigenetics show, there is no gene, or set of genes, that unequivocally trigger such traits of well-being (Kandler and Instinske, 2025; Zwir et al., 2021). Such capacities are potentials for all. But they are encouraged, or discouraged, by differing forms of lifestyle and socio-ecological organization. For example, a context of economic and ecological insecurity with little community and governmental support for those harmed will likely encourage just the opposite of these traits: hopelessness and despair, rather than self-directedness; conflict and competitiveness, rather than cooperativeness; individualism and self-centeredness, rather than self-transcendence. Recognizing the role of the context alerts us to the scope of policies and forms of agroecological governance that might shift personalities in more helpful directions.

At the meso level, community well-being, other-centeredness, and cohesion are equally critical. Agroecological practices often depend on cooperation, shared resources, and social learning, which are only possible in communities that are both socially integrated and psychologically supported. Strong community ties facilitate the co-creation and dissemination of knowledge while providing emotional and material support to mitigate the risks of changing environments. An example of this is community-based watershed management, where high social cohesion and trust (i.e., social capital) are essential for motivating farmers to collectively implement soil and water conservation practices—such as soil bunds and vegetative barriers—to reduce erosion and water contamination, an effort that would fail if undertaken by individuals acting alone (Pretty and Ward, 2001; Hailu et al., 2021). When individuals feel embedded in supportive, meaningful social structures, they are more likely to engage in long-term, collective sustainability efforts and embrace transitions that may initially be costly or uncertain. This underscores a central premise of our sustainability framework: technical innovation will falter without being people-centered, that is if we ignore the human dimensions of systemic agroecological transformation (Gliessman, 2016).

Centering well-being in agroecological transitions is thus both a practical necessity and an ethical imperative (Bezner Kerr et al., 2022). Moreover, debates over regenerative agriculture (which shares ecological goals with agroecology but often lacks its socio-political emphasis) suggest that regenerating relationships is part of the equation, reflecting the importance of the relational dimension of social well-being (Bell et al., 2024). Gosnell (2022) reframes sustainability not merely as an environmental or economic goal, but as a deeply rooted dimension of the human condition. She further highlights that the realization of ecological health requires integrating the inner transformation that fosters farmers' feelings of kinship with nature, arguing that regenerating soil goes hand in hand with the regeneration of farmers' dignity, sense of purpose, and connection to land and community. Our framework responds to this need by integrating well-being as a core dimension of sustainability, operationalized through both standardized and participatory indicators. In doing so, we aim to provide a tool that respects local knowledge, enhances agency, and fosters long-term engagement in agroecological change.

To conceptually anchor our framework, we draw on Cloninger's biopsychosocial model of personality and his research on well-being. As stated earlier, well-being emerges from the development of three interrelated character dimensions: self-directedness, the capacity for autonomous purpose and responsibility; cooperativeness, the capacity for empathy, social tolerance, and community integration; and self-transcendence, the ability to see oneself as an integral part of a larger whole, fostering spirituality, meaning, and connection beyond the self (i.e., nature, God or the universe)⁴. Cloninger's theory, grounded in decades of empirical research (e.g., neurological, large population studies, interventions, psychometrics, etc.), consistently links these traits to improved mental health, resilience, and prosocial behavior (Cloninger et al., 1993; Cloninger, 1994, 2013; Zwir et al., 2021). By viewing well-being as a character developmental process, rather than a static or subjective condition, it becomes possible to align personal growth with sustainability transitions and goals. In the context of agroecology, Cloninger's model provides a conceptual bridge between individual biopsychosocial development and collective ecological outcomes. Self-directedness supports agency, persistence, and responsibility in adopting new practices; cooperativeness fosters trust, collaboration, and collective learning within farming communities; and self-transcendence encourages long-term, intergenerational concern for land, nature, and future generations. These traits are not fixed dispositions but developmental potentials that are encouraged or discouraged by socio-ecological organization. Contexts characterized by insecurity, isolation, or lack of institutional support may suppress these capacities, whereas supportive, participatory, and relational environments can foster them—highlighting the importance of governance and social conditions in shaping well-being during agroecological transitions.

That inner transformation does not take place ex nihilo, however. It develops in response to the conditions of one's context, including social structures, cultural influences, community ties, and ecological conditions a person experiences. Consider that no inner transformation is likely in circumstances that might require a person to radically change their social relations of identity—what Bell et al. (2024) calls a phenomenological rupture—without the opportunity to embrace a different network of identities. For example, for a conventional farmer to switch to organic farming typically requires more than implementing the legally approved standards in their area. For the transformation to organic to be lasting, it also entails thinking about one's identity differently, and finding networks of social support and friendship with a considerably different group of people.

A crucial part of that new identity is whether it enhances self-directedness, strengthening a farmer's sense of agency, self-efficacy, and autonomy in adopting sustainable practices, rather than a more passive embrace of dominant agricultural narratives. Fostering cooperativeness can increase community solidarity, and facilitate collective learning and joint experimentation, which are critical for strengthening social networks and enabling self-governance institutions necessary for overall systems change (Kernecker et al., 2021; Magliocca et al., 2025). Nurturing self-transcendence can deepen environmental stewardship and foster a long-term, intergenerational perspective, consistent with the outward-looking orientation implied by self-transcendence. Consistent with this orientation, research on self-transcendence values (i.e., biospheric values and, to a lesser extent, altruistic values) shows that these values are among the strongest and most consistent predictors of pro-environmental concern and behavior (De Groot and Steg, 2008, 2009, 2010; Steg, 2016; Steg et al., 2014). Indeed, Cloninger argues that an “outlook of unity” enables functioning “with plasticity and virtue,” thereby supporting sustainable harmony with nature and other people (Cloninger, 2004, 2013; Zwir et al., 2022). Importantly, evidence from personality research using the TCI indicates that physical, mental, and social well-being depend strongly on profiles of self-directedness, cooperativeness, and self-transcendence (Cloninger, 2004, 2013; Cloninger et al., 2010; Cloninger and Zohar, 2011; Josefsson et al., 2011). Beyond the TCI literature, cooperative and prosocial orientations are also associated with higher well-being across cultures (Aknin et al., 2013). In line with this broader evidence base, higher self-directedness is associated with greater perseverance and resilience under stress (Vosloo and Van Staden, 2024), and higher cooperativeness correlates with more adaptive emotion-regulation strategies when coping with challenges (Chae et al., 2019).

The causality of these associations is two-way, as is typical in social life. The nurturing of self-directedness, cooperativeness, and self-transcendence encourages the socio-ecological relations that in turn encourage these traits of well-being—and vice versa. Recognizing how causes affect effects that in turn cause causes, in a never-ending interplay, provides a wider range of options for stimulating agroecological transformations, as we will come to later.

Although these traits and their socio-ecological contexts have not been widely studied in farming populations, their known relationships with healthy and prosocial behaviors suggest they would influence which farmers would engage most effectively in sustainability transitions. By explicitly incorporating self-directedness, cooperativeness, and self-transcendence into our proposed indicators (for instance, through the TCI), we ensure the framework captures these key biopsychosocial drivers of sustainable behavior. Cloninger's model thus provides a unifying backbone for interpreting both individual and community well-being metrics. Each indicator can be viewed through the lens of purposeful agency, social connectedness, and a sense of greater meaning, within the context of conditions that encourage or discourage them.

In line with Cloninger's theory, no single character trait alone defines well-being. Rather, well-being emerges from the integrated development of personality and its expression in multiple domains of context. In this paper, we refer to well-being as feeling good (i.e., happiness), doing good (i.e., mature and actively virtuous living), physical health (i.e., vigor, vitality, absence of disease or infirmity), and prosperity (i.e., success, good fortune, and flourishing) (Cloninger, 2004). This theory-informed, integrative perspective on well-being represents a novel contribution to agroecological assessment, grounding the individual and social dimensions of sustainability in a rigorous model of human personality development and its contextual inducements. It places biopsychosocial development in the context of agroecological vitality as an essential aspect of what gives life meaning and value. Each metric in the assessment not only measures a relevant outcome, but also reflects an underlying facet of the human condition, factors essential for fostering lasting well-being and driving sustainable transitions.

We propose a two-pronged framework for evaluating well-being in agroecological transitions, combining standardized, theory-informed indicators with participatory, context-specific metrics. This approach balances comparability across sites (and countries) with responsiveness to local contexts, cultures, and values, offering a robust model for multi-scalar, integrative assessment.

Pillar 1: The first pillar of the framework consists of one standardized survey instrument designed to evaluate the state of and changes in individual and community well-being over time. To ensure the applicability across diverse agroecological settings, this pillar will involve a core suite of validated, cross-culturally relevant tools that collectively capture well-being, psychological stress, and character development. The pool of validated instruments that can be drawn from is shown in Table 1.

Together, this suite of validated instruments offers a multidimensional, theory-informed profile of well-being. While some tools may appear overlapping, each has been selected to reflect distinct facets of our working definition of well-being—feeling good, doing good, physical health, and prosperity—and to enable flexibility across different research and community contexts. The final goal of the evaluation framework is to determine the best-suited indicators to keep across contexts.

For example, the Satisfaction with Life Scale (SWLS) offers a concise global measure of life satisfaction, valuable for capturing cognitive evaluations of well-being. In contrast, the WHO-5 Well-Being Index focuses on recent emotional states, allowing for short-term tracking of mood and affect. These tools together help differentiate between stable life judgments and transient emotional states—both important for understanding how agroecological transitions are experienced over time.

The Harvard Flourishing Index spans broader domains such as health, character, purpose, and financial stability. It offers a valuable composite measure aligned with our “doing good” and “prosperity” dimensions, but its breadth may obscure specific changes in stress or psychological functioning. To complement this, we include the Perceived Stress Scale (PSS), which captures environmental and psychological pressure—key for identifying vulnerabilities or trade-offs during periods of systemic change.

Finally, the TCI uniquely operationalizes Cloninger's model, directly measuring self-directedness, cooperativeness, and self-transcendence—the core psychological capacities that support sustainable behavior. While these traits may overlap with elements of flourishing or resilience, they serve a distinct purpose in our framework: linking personal character development to agroecological context.

In short, the selected tools are not redundant but complementary, each illuminating different temporal, emotional, or psychological aspects of well-being. Together, they allow for both breadth and depth in assessment, aligning with our commitment to a nuanced, pluralistic understanding of well-being that can be adapted to site-specific goals and constraints.

Pillar 2: The second pillar of the framework is a participatory “vital signs of place” toolkit that supports communities in co-defining what well-being means in their contexts. More specifically, “vital signs of place” are a small set of locally meaningful indicators co-defined by communities through participatory processes. They complement standardized well-being measures by identifying place-specific priorities and stressors that serve as decision-support signals for adaptive agroecological governance. Analogous to clinical vital signs (e.g., blood pressure), which flag the need for attention without prescribing treatment, “vital signs of place” indicate when social or ecological conditions in a specific context warrant adaptive response. Their number is intentionally limited (typically 6–8) to maintain parsimony and feasibility. While likely qualitative or ordinal, these “vital signs of place” metrics can be documented with clear definitions and can be tracked over time.

Note that this second pillar builds on the first, by allowing communities to clarify what is most important to them in terms of the community-level indicators of well-being and sustainability. Using participatory processes, researchers will be able to help generate metrics that center local values, lived experience, and situated knowledge in agroecological transitions and food system sustainability projects. As in medicine, these vital signs inherently provide critical information about the overall state of a community. Is a community thriving? Is the current state of the community durable long term? How does community well-being depend on and shape the local agroecosystem or environment? Perhaps one community sees collective action and a voice or role in local environmental policy as key components of both well-being and environmental sustainability. Agroecological transitions will not be sustainable in this context without ensuring farming communities have autonomy and agency in decision-making.

Community-led advisory boards or similar local groups can guide the identification and co-development of these community-level well-being indicators through methods such as storytelling circles, Photovoice projects, and participatory mapping exercises (Newman et al., 2011; Sachet et al., 2021). In this way, community members identify what well-being means to them in the context of their agroecosystem. For instance, photovoice invites participants to document their experiences through photography and discuss them, which has been shown to elevate surfacing values such as mutual aid, food fairness, and connection to land (Huber et al., 2023). Likewise, community mapping and group discussion activities can help identify shared priorities, stressors, or markers of local flourishing (Berg, 2022).

Outputs from this process might include indicators like “sense of belonging in the farming community” (rated by residents), “presence of mutual aid networks”, “perceived fairness in local food distribution”, or “spiritual connection to the land”. These “vital signs of place” indicators are collaboratively defined and refined through iterative feedback, then documented with clear definitions and, where possible, locally appropriate methods for tracking change over time or differences from one setting to another (e.g., community surveys or focus group ratings)⁵. The result is a flexible but rigorous tool for surfacing and measuring community-centered dimensions of well-being that standardized metrics alone may miss. Community-driven development of these measures also serves to promote community engagement and mutual service to one another.

Importantly, community-defined “vital signs of place” are intentionally designed to reflect locally meaningful dimensions of both well-being and sustainability; therefore, they are not expected to be identical across sites. Rather than aggregating these indicators directly, our framework supports combining them, when useful, according to how they align under larger well-being categories. For example, locally defined indicators can first be mapped onto a shared set of higher-order well-being categories (e.g., agency, social cohesion, environmental attachment, livelihood security) that are consistent across sites and aligned with standardized indicators and relevant SDG categories. This allows distinct local indicators (such as youth engagement in farming, mutual aid networks, or perceived fairness) to be interpreted within a common analytical structure without erasing contextual specificity.

Aggregation should then occur within these categories, using appropriate ordinal or normalized scoring approaches (e.g., Likert-scale means), depending on data type and feasibility. Cross-site comparisons can therefore be conducted across categories and trajectories of change over time, rather than through direct comparison of individual community indicators or the creation of opaque composite indices. This approach preserves the multidimensional character of well-being, supports interpretability, and enables learning across contexts while ensuring local relevance.

These outputs can be combined in modular fashion to align with context-specific needs and constraints. Together, they provide a multidimensional and theory-grounded profile of well-being, suitable for tracking the effects of agroecological transitions over time. This pillar also addresses emerging biopsychosocial challenges in farming communities—such as climate-related emotional stress. To assess phenomena like eco-anxiety, climate anxiety, or solastalgia (distress caused by environmental change, Galway et al., 2019), the proposed framework incorporates elements from emerging tools such as the Climate Change Anxiety Scale (Clayton and Karazsia, 2020), the Eco-Anxiety Questionnaire (Hogg et al., 2021), and the Environmental Distress Scale (Higginbotham et al., 2006). While still under development in some settings, these tools allow researchers and communities to capture how ecological disruption impacts mental health and adaptive capacity.

To operationalize the framework, Table 2 below presents illustrative indicators at each level, individual, community, and ecological, organized by source: standardized tools and community-defined metrics. The standardized set includes validated instruments discussed earlier (e.g., WHO-5, Harvard Flourishing Index), while the participatory set reflects context-specific insights drawn from Photovoice, mapping, and community dialogues.

Although many community-defined indicators are unique to their local setting, they often align with the framework's well-being categories such as social connectedness, environmental attachment, or collective agency. By organizing both indicator types side by side, Table 2 clarifies how cross-site comparability and contextual relevance can be jointly supported within a multi-scale assessment.

This table is not exhaustive, but illustrates the dual logic of the framework. For each scale, standardized indicators provide top-down consistency and scientific validity, while community-defined indicators provide bottom-up relevance and meaning. For instance, at the individuals level, a standardized survey might show an improvement in average life satisfaction scores, while participatory Photovoice might reveal why—perhaps farmers feel less isolated due to new peer networks. At the community level, a formal social cohesion index might be complemented by local narratives about how a new farmers' cooperativeness increased trust and mutual aid. At the ecological level, scientific measures of soil health could be paired with farmers' own observations of wildlife returning to their fields, which they interpret as a positive sign. In practice, the standardized and participatory measures inform each other, creating a richer picture of well-being outcomes than either alone.

Prior to rolling out the framework, standardized (core) metrics will be determined by a research team via preliminary research and development (e.g., literature review of relevant metrics, expert consultation, and identification of survey items). The framework is then built on this pre-defined set of broad well-being domains that align with key sustainability goals and the SDGs. These core domains (such as physical health, mental health, social connectivity, economic security, and ecosystem vitality) are applied consistently across all projects to provide a common foundation for assessment.

Implementing the framework involves a structured yet flexible process that balances scientific rigor with local relevance. The approach combines standardized monitoring with community-based insight generation, guided by a decision-tree logic that supports iterative refinement. The process unfolds by the following key steps:

By following this process, the framework systematically integrates standardized and participatory methods—an approach that remains rare (Béné et al., 2024). Each step ensures that both scientific rigor and community voice are maintained. The emphasis on parsimony at Step 4 is critical: many sustainability assessments fail because they attempt to track too many indicators, leading to data fatigue and confusion. By carefully selecting a minimal essential set of metrics, we make the framework practical for real-world use while still comprehensive in covering key well-being dimensions. To provide a clear visual roadmap of this implementation strategy, Figure 2 summarizes the operational workflow. The diagram illustrates how the parallel streams of standardized (Step 1) and community-defined (Step 2) data converge into a single integration phase (Step 3). It depicts the iterative feedback loop inherent to Step 4.

This study puts forth a framework that systematically links well-being with agroecological sustainability at multiple scales. A key strength is its theoretical integration of a psychobiological model (Cloninger's dimensions) with agroecological context. Although recent agroecology and food-system sustainability assessments typically include multi-dimensional human and social well-being indicators, our overarching framework that draws on personality-based well-being typologies is novel (see Bezner Kerr et al., 2022; Friedrichsen et al., 2025; Janker and Mann, 2020; Orou Sannou et al., 2023). By doing this, we seek to address a critical gap: the lack of understanding of how individual biopsychosocial factors contribute to sustainable behavior and outcomes in farming communities—and vice versa. Our framework also pioneers a means to combine standardized psychometric measures with participatory, community-defined indicators in one assessment system. Even the unique community-defined “vital signs of place” can be used to compare well-being across locales, given that indicators can be aggregated under broader well-being categories. For example, defined metrics might use different language or outcomes, but all be related to agency. By assessing directional changes in agency across several vital signs, the impacts of agricultural transition on well-being can be compared and understood even more deeply.

Previous approaches have tended to use either standardized metrics and instruments in a top-down, prescriptive manner or bottom-up procedures tailored from the beginning by local communities⁷. We offer a practical way to integrate approaches, complete with a decision procedure for indicator selection and emphasis on parsimony to keep it manageable.

Moreover, the framework explicitly bridges scales—connecting individual-level outcomes (e.g., personal well-being) to the context of community-level processes and ecological conditions. This multi-scale coherence is rarely seen in sustainability metrics, yet it is crucial for capturing the full picture of agroecological transitions. By capturing feedback loops (how improved well-being can spur better environmental stewardship and vice versa), we hypothesize the framework could yield insights into leverage points for accelerating sustainability transitions.

Although this goes beyond the scope of our presentation, our framework's design can also facilitate longitudinal tracking of change. By incorporating baseline, midline, and endline assessments (and potentially follow-ups), it could enable the study of trajectories in well-being and sustainability. This would be particularly important for establishing causal relationships and learning over time. For example, we can observe whether improvements in well-being precede improvements in ecological practices (or vice versa), shedding light on the directionality of the sustainability-well-being nexus. Few agroecology studies have this temporal component, as many are cross-sectional. Implementing our framework in pilot projects over time could generate valuable longitudinal case studies.

Notwithstanding its strengths, the framework faces several challenges. One major challenge is measurement diversity vs. standardization. While the inclusion of community-specific indicators is a strength, it complicates comparability. Different communities may choose indicators that are not directly comparable or quantifiable. We mitigate this by also collecting a core set of standardized data, but integrating the two data types for analysis requires careful methodological work⁸. As mentioned earlier, developing protocols to translate qualitative outputs into quantitative insights is an open area for innovation. We have suggested grouping local indicators under common well-being domains (health, agency, environment, etc.) to allow some higher-level comparison, but this remains a delicate process subject to interpretation.

The strategic selection of indicators must be tailored to the specific goals of the assessment. Good indicators must exhibit validity, objectivity, consistency, and sensitivity to change, while remaining accessible and representative of the community. For community-led systematization (where the objective is to analyze lessons learned and plan local agroecological transitions) the framework should prioritize indicators with high sensitivity and ease of determination. Participatory 'vital signs of place' fit this need, as they allow communities to capture qualitative shifts that standardized metrics might miss. These indicators are therefore particularly valuable for bottom-up planning, as they are defined by the actors themselves, ensuring high representativeness and local relevance. Conversely, for evaluating public policies or conducting cross-regional comparisons, the standardized part will better ensure objectivity and consistency. Instruments from our first pillar provide more rigorous, comparable, data necessary for national monitoring and reporting, all while being informed by the instruments from the second pillar. Similarly, indicators related to standardized economic and ecological proxies allow policymakers to benchmark progress across diverse contexts, while the participatory ones can indicate the potential for policy acceptance and uptake. By distinguishing between these application scales, we contend that the toolkit remains both scientifically robust and practically useful for a wide range of uses.

Another challenge is ensuring cultural validity and sensitivity of standardized instruments. Scales like SWLS or WHO-5 have been used globally, but their interpretation can vary by culture. Responses may be influenced by cultural norms about expressing satisfaction or mental health. Additionally, in many languages the exact phrasing of well-being concepts can change meaning. We must invest effort into translating and validating these instruments in each local context (perhaps conducting cognitive interviews or pilot testing in the community to ensure questions make sense). This challenge is well noted in healthcare science—measurement invariance is not always achieved across different populations (Cruchinho et al., 2024). Our approach to address this includes involving local partners in questionnaire design and potentially adjusting standardized tools (while maintaining as much consistency as possible). Certain standardized metrics might have to be dropped or replaced in a given context if they prove inapt, which could affect cross-site comparability. Thus, there is a tension between global standardization and local adaptation that will need to be continuously navigated, including the recognition of different paradigms, epistemologies and cosmovisions when implemented in Global South and non-Western contexts.

We also acknowledge challenges in data collection and resource requirements. Our approach means more extensive data gathering—surveys, interviews, group workshops, etc. This demands time, funding, and expertise (e.g., facilitators for participatory sessions, psychologists for survey analysis). In a world of resource and time-limited projects, there might be pressure to simplify. We argue that the added value of understanding the place-based definition of well-being justifies the effort, but future users of the framework will need adequate capacity. Training community members as co-researchers (e.g., to conduct surveys or facilitate discussions) could help, reframing data collection as a participatory process that could support local empowerment. Still, ensuring quality and consistency of data from participatory methods is not straightforward, and we must be vigilant about documentation and researcher biases.

A further challenge lies in interdisciplinary and transdisciplinary collaboration. By its nature, our framework operates at the intersection of social sciences, health sciences and agroecology. Successful implementation requires collaboration between agronomists, ecologists, psychologists, sociologists, and the community. Such collaborations can be hindered by differences in terminology, methods, and even values (Anderson and McLachlan, 2016; Lopez-Merino and Lamine, 2024). We have to create a common language (e.g., what “well-being” entails) and mutual respect among team members. On the upside, this challenge is also an opportunity: transdisciplinary teamwork can foster creative solutions and methodological advances. For instance, combining remote sensing for land health with community well-being mapping could produce new integrated indicators. We see our framework as a living project that will evolve through these collaborations, potentially yielding methodological innovations in mixed-methods integration and participatory science.

Despite these challenges, we maintain that centering well-being is essential. The potential risks of not doing so are evident: agroecological projects might fail if farmers are too stressed, alienated, or unsupported to implement changes. By contrast, addressing well-being can create a positive feedback loop—happier, healthier communities are more resilient and innovative, which enhances sustainability, which in turn further improves well-being. Our framework is an attempt to measure and ultimately leverage that positive feedback.

Embedding well-being into agroecological indicators has significant implications for policy and governance at multiple levels. First, it broadens the objectives of agricultural and rural development policy: success is not only higher yields or improved soil metrics, but also healthier, more resilient communities. Policymakers may need to redefine targets and KPIs (key performance indicators) for agroecology initiatives to include well-being outcomes (e.g., farmer retention rates, mental health improvements, community empowerment indices). This shift could catalyze more holistic programs that combine agronomic support with health and social services. For instance, an agroecology extension program might partner with rural health agencies to simultaneously address sustainable farming techniques and farmer stress management—a cross-sectoral approach we would support.

Our framework also emphasizes participation and local knowledge, implying changes in governance structures. Governments and development agencies would benefit from creating formal channels for community input when designing sustainability metrics and interventions. This aligns with the growing trend of co-production of knowledge in policy; indeed, a study in Australia (Zyngier et al., 2024) showed that convening diverse stakeholders to identify indicators and solutions led to a rich matrix of options and revealed areas of consensus and conflict, improving policy relevance. Similarly, by involving Community Advisory Boards in defining “vital signs,” local governance capacity is strengthened. Communities essentially become partners in monitoring and evaluation, not just subjects of it. This can increase trust in government programs and ensure interventions are culturally appropriate. It also helps decentralize sustainability governance, empowering local entities (cooperatives, municipalities, farmer unions) to take ownership of well-being goals that feed into national targets.

Multi-level governance is also crucial. The two-way, interactive causality of our framework invites coordination between national/international bodies (which set standardized metrics and SDG commitments) and local actors (who innovate and contextualize metrics). Policymakers might establish frameworks where a core set of well-being indicators is mandated for all agroecology projects (for comparability), while also mandating a participatory indicator-development process for each project to capture local priorities. Resources and guidelines would need to be provided for these participatory processes, e.g., ministries of agriculture could issue toolkits (like our “vital signs” guide) and fund training for facilitators. Over time, as data is collected, there could be feedback loops: local innovations in indicators that prove useful could be scaled up or inform the evolution of national indicators, just as appropriate national level interventions may encourage local innovations. In this way, governance becomes more adaptive and iterative (Folke et al., 2005), reflecting field realities.

There are also implications for funding and program evaluation. Donors and agencies often require measurable outcomes; by providing well-being metrics, we give them additional criteria to evaluate success. This could unlock funding for integrated programs (for example, rural development grants might start to require a well-being assessment component). Moreover, policy frameworks like the EU's Common Agricultural Policy or national agricultural strategies might incorporate farmer well-being explicitly as a goal, once tools to measure it are available. It is conceivable that in the future, something like a “Well-being Impact Assessment” could be conducted alongside environmental impact assessments for agricultural projects, to evaluate potential social effects on communities before implementation.

From a governance perspective, one challenge will be to ensure equity and representation in the participatory aspects. It is important that the voices of marginalized groups (e.g., smallholders, women, indigenous communities, farm and food workers, youth, LGBTQ+) are included when defining well-being indicators. Policy can mandate inclusive approaches—for instance, requiring that participatory sessions include a certain percentage of women farmers or youth. This ensures the resulting metrics and subsequent decisions do not inadvertently reflect only the most powerful stakeholders' views. Such inclusive processes contribute to social justice, echoing the emphasis on epistemic or cognitive justice in our framework (Fricker, 2007; Anderson and McLachlan, 2016).

Finally, the integration of well-being calls on intersectoral governance. Agricultural authorities must collaborate with public health, education, and environment sectors. For example, improving farmer mental health might involve rural healthcare provision (telemedicine, counseling services), which is outside the typical remit of agriculture departments but essential for sustainable farming communities. Our framework's data can be a catalyst for these conversations, eventually providing evidence that interventions in one domain (like mental health services) have payoffs in another (like use of conservation practices). It encourages breaking down silos in governance, fostering a more coordinated approach to rural well-being and sustainability. In summary, using this framework could lead to more human-centered agricultural policies, participatory governance models that empower communities, and cross-sector collaborations that together create a more enabling environment for agroecological transitions.

This article is an effort by an interdisciplinary collective of scholars to bring together disparate elements that collectively can advance the inclusion of well-being in the analysis of (agroecological) transitions. At the time of writing, a number of research projects are taking shape that will allow our team to start testing and implementing the framework in different settings. If validated through pilot applications, the framework could inform future agroecological transition efforts. The production of an open-access “well-being in agroecology” toolkit is an important expected outcome of this work, to provide standardized surveys, workshop guides, and analysis templates that any project can adapt and adopt. Such a toolkit would help mainstream the inclusion of well-being in sustainability assessments. Over time, accumulating data from different contexts could allow for meta-analyses: e.g., to test whether certain well-being factors (like community cooperativeness) consistently predict agroecological success, or to compare well-being outcomes of different types of interventions (e.g., organic farming vs. food sovereignty initiatives). Furthermore, the framework enables “before-and-after” assessments of specific interventions, allowing researchers to compare the efficacy of different approaches—such as organic certification vs. food sovereignty movements—in diverse agricultural contexts.

Through iterative refinement, our objective is to address the challenges outlined: fine-tuning indicator sets, improving protocols for data integration, and ensuring the process is scalable. We will also explore the use of decision-support tools to visualize results for stakeholders (e.g., dashboards that show changes in well-being alongside ecological metrics). By doing so, we aim to make the data actionable. For example, local cooperatives could use the results to lobby for policy support, or a project team might shift strategy upon seeing a certain well-being metric decline.

Ultimately, this discussion highlights that while embedding well-being in agroecology assessments is complex, doing so offers a transformative lens. Well-being's inclusion prompts all involved to consider farmers and communities not just as beneficiaries of sustainability, but as co-creators and central actors whose quality of life is inseparable from the health of the land.