The paper, published open access on 14 August 2026, tackles a puzzle that has been accumulating in the research literature for years. Some studies find that circularity strengthens resilience by reducing reliance on virgin materials and extending the availability of critical resources; work on electric vehicle battery supply chains, for example, has shown that circular strategies can ease dependence on scarce raw materials. Other studies warn of the opposite effect. Kennedy and Linnenluecke, in an influential 2022 research agenda, cautioned that efficiency-oriented circular strategies may remove the buffers, diversity, and slack resources that systems need to withstand and adapt to shocks. A third group of studies reports conditional results, finding that outcomes hinge on network topology, supply-risk exposure, institutional anchoring, business model design, and organizational capabilities. Rather than treating these findings as contradictory noise, the German team treats them as the phenomenon to be explained.

The key to their explanation is a distinction borrowed from resilience theory in social-ecological systems research: the difference between specified and general resilience, a distinction that traces back to Carpenter and colleagues’ famous question of resilience ‘of what, to what?’ Specified resilience refers to the capacity of a particular supply chain, infrastructure, territory, or material system to withstand an identifiable disturbance. General resilience refers to the broader capacity to absorb, adapt to, or reorganize under unfamiliar or cross-cutting disturbances. Once this distinction is applied, the heterogeneous findings in circular economy research fall into a coherent pattern. Positive results typically concern specified resilience to known risks such as raw-material scarcity or supply-chain interruption, while critical results concern losses of general resilience through reduced response diversity, diminished slack, and eroded adaptive capacity.

The mechanisms by which circularity erodes general resilience are concrete and, in some cases, counterintuitive. Closing loops can reduce import dependence but create dependence on specialized reverse-logistics systems that did not previously exist. Standardizing secondary-material streams improves efficiency and interoperability but reduces diversity and substitutability. Tight network integration improves the circulation of materials but also increases the speed at which a disruption at one node propagates around the loop, eliminating the exit option of sourcing outside the network. In a linear economy, interdependencies arise incidentally; in a circular economy, they are deliberately engineered. A disruption to a standardized secondary-material stream therefore cannot simply be bypassed, because the stream itself depends on ecosystem-wide participation.

To capture what is lost when these capacities disappear, the authors introduce the concept of ‘system options’: collectively valuable capacities that preserve alternative courses of action under disturbance. These include redundancy, modularity, response diversity, adaptive slack, and learning infrastructures. What makes system options distinctive, the authors argue, is their cost structure. Their benefits are diffuse, delayed, or system-wide, while their costs are concentrated on particular actors. Redundancy requires spare capacity, slack requires carrying costs, modularity requires design investment, and diversity may sacrifice economies of scale. Under competitive pressure, such capacities are systematically underprovided, because no single firm captures the full value of maintaining them. This is not a technical problem but a governance problem: which options should be preserved, who pays, how are costs and benefits distributed, and how are commitments sustained over time?

To organize this governance challenge, the study applies the ordonomic approach, an analytical framework developed by Pies that distinguishes three interdependent levels of social order: operations, governance, and semantics. At the operational level, circular strategies such as repair, reuse, remanufacturing, and recycling are enacted under given rules and competitive pressures. At the governance level, rules, standards, incentives, contracts, and collaborative institutions determine whether costly system options are designed, financed, monitored, and sustained. At the semantic level, ideas and narratives determine whether resilience costs are interpreted as reasonable and necessary, or dismissed as wasteful and inefficient. The framework’s diagnostic power lies in showing how failures at one level can masquerade as problems at another: treating a governance problem as an operational one leads to efficiency optimization that strips out system options, while treating a semantic problem as a governance one produces institutional designs that collapse under discursive contestation.

The framework yields testable propositions with direct policy relevance. Efficiency-oriented circular strategies are likely to strengthen specified resilience when they measurably reduce exposure to identifiable disturbances, but likely to weaken general resilience when they increase systemic interdependence, narrow response diversity, reduce adaptive slack, and deepen dependence on specialized infrastructures. General resilience is more likely to be preserved when governance arrangements match each system option to its cost structure, observability, and beneficiary structure: reserve obligations and capacity contracts for slack and redundancy, standards and procurement for modularity, ecosystem governance for shared infrastructures, and anti-concentration rules for response diversity. Mismatched governance fails in patterned ways, the authors predict: free riding when benefits are diffuse, resistance when costs are concentrated, capture when standards allocate rents, and the quiet dismantling of reserves during calm periods when disruption memories fade.

Perhaps the most provocative element of the paper concerns legitimation, the discursive work of making resilience costs publicly intelligible. Many circular economy discourses are strongly efficiency-coded, equating circularity with waste elimination, lean operations, and short-run cost minimization. Within such frames, redundancy appears as duplication, slack as waste, and diversity as fragmentation. The authors argue that resilience-oriented governance is more politically durable when the costs of system options are framed as preparedness, insurance, option value, fairness, continuity protection, or strategic autonomy. Notably, they suggest that post-2022 strategic-autonomy discourse in Europe has opened political space for interpreting circularity not only as environmental policy but also as material-security policy. They even caution against a reflexive assumption that broader stakeholder participation always strengthens governance: in circular contexts, widening participation can surface cost-distribution conflicts that resilience reframing had suppressed, potentially destabilizing otherwise workable arrangements.

The implications reach both boardrooms and ministries. For managers, the study recommends asking of every circular strategy which disturbance it protects against, which options it removes, whether it deepens dependence on a specific supplier, recycler, standard, or platform, and whether fallback pathways remain available. Because many system options cannot be maintained by individual firms alone, firms have a strategic interest in inter-firm and public-private arrangements that share the costs of reverse logistics, interoperable standards, and reserve processing capacity. For policymakers, the message is sharper still: resilience is not an automatic co-benefit of circularity. Policies that improve protection against one risk may weaken adaptability if they create dependence on a narrow infrastructure, a single technology, or a rigid recovery pathway. Policymakers should specify the resilience object and the disturbance, distinguish specified from general resilience, map costs and beneficiaries, and select governance mechanisms matched to each system option.

The study’s conclusion reframes the entire debate in a single sentence: circular systems remain resilient not simply because they close loops, but because they preserve alternative pathways when preferred loops fail. The authors call for future research to measure specified and general resilience separately, using indicators such as supply continuity and recovery time for the former, and response diversity, modularity, substitutability, network redundancy, and cross-shock performance for the latter. They also flag a critical failure condition: when a small set of actors bears concentrated, visible, and immediate resilience costs while system-wide benefits remain contingent and delayed, no amount of framing can sustain the arrangement without transfers or participation rules. The circular economy, on this reading, will deliver security not when it becomes perfectly efficient, but when it remains capable of acting otherwise under disturbance. In an era of geopolitical volatility and critical-material insecurity, that distinction may prove to be one of the most consequential ideas in industrial ecology.

Subject of Research: The relationship between circular economy strategies and specified versus general resilience, conceptualized as the governance of system options

Article Title: Circular economy resilience as the governance of system options: specified and general resilience in circular transitions

Article References: Schultz, F. C., Valentinov, V., & Pies, I. (2026). Circular economy resilience as the governance of system options: specified and general resilience in circular transitions. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00158-1

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00158-1

Keywords: circular economy, resilience, specified resilience, general resilience, system options, governance, supply chain, industrial ecology, critical raw materials, redundancy, adaptive capacity, strategic autonomy

Strategic foresight differs fundamentally from conventional forecasting. Where forecasting extrapolates present trends forward and assumes a broadly stable environment, foresight deliberately constructs multiple plausible futures, each shaped by different combinations of driving forces. These can include climate extremes, energy price swings, geopolitical disruption, trade fragmentation, technological breakthroughs and shifts in consumer demand. By developing scenarios that span this possibility space, researchers and policymakers can stress-test transition strategies before committing scarce public and private resources, identifying which elements of a climate-neutral farming pathway are robust across many futures and which are fragile bets on a single expected outcome.

The core insight of the research is that resilience and foresight are inseparable concerns for agricultural transformation. Farming sits at the intersection of ecological, economic and social systems, each with its own thresholds and feedback loops. A transition strategy that reduces greenhouse gas emissions on paper may nevertheless prove brittle if it depends on uninterrupted supply chains, stable subsidy regimes or benign weather. Strategic foresight provides a systematic way to expose these dependencies, revealing how plausible disruptions, from drought sequences to fertilizer market shocks, could interact with the transition process itself and either accelerate, slow or reverse progress toward climate neutrality.

Technically, the foresight approach typically proceeds through a sequence of steps. Analysts first scan for driving forces, categorizing them by their certainty and their potential impact on the system. The most consequential and most uncertain forces become the axes of scenario construction, producing a small set of internally coherent future worlds. Within each world, the dynamics of agricultural transition are explored: how farmers might adopt practices such as reduced tillage, cover cropping, improved nutrient management, agroforestry, precision fertilization or renewable-energy integration, and how those adoption patterns respond to the economic and institutional conditions of each scenario. The resilience of the transition is then assessed by comparing outcomes across scenarios and locating the points of common vulnerability.

One of the most important contributions of this framing is its treatment of time. Climate neutrality is usually expressed as a target date, but the journey toward that date is uneven and path-dependent. Early choices, such as which practices receive public support or which supply chains are reorganized first, can lock in certain configurations and foreclose others. Foresight makes these lock-in risks visible. It can show, for example, that a transition strategy optimized for a future of high carbon prices and stable trade may collapse under a future of price volatility and protectionism, whereas a more diversified strategy, combining multiple mitigation practices and revenue streams, retains functionality across both worlds.

The volatility emphasis is particularly timely. Recent years have confronted agriculture with a compound stress test: pandemic-era supply disruptions, energy and fertilizer price spikes linked to geopolitical conflict, recurrent droughts and floods, and shifting trade relationships. Each of these events strained farm businesses and policy frameworks alike. A transition to climate neutrality adds new layers of dependence, on carbon accounting systems, on emerging markets for low-emission products, and on technologies still moving down their cost curves. The research underscores that planning for the transition without accounting for such volatility would be a category error, because volatility is not an aberration but a defining feature of the operating environment.

Resilience, in this context, is unpacked rather than assumed. The analysis draws on the established conceptual vocabulary of resilience research, distinguishing the capacity of farming systems to absorb shocks, to adapt their structures and practices in response, and, where necessary, to transform into fundamentally new configurations. Applied to the climate-neutral transition, these capacities imply different design principles. Absorbency favors buffers such as financial reserves, diversified rotations and soil organic matter that cushions drought. Adaptability favors flexible policy instruments, learning networks among farmers, and monitoring systems that detect stress early. Transformability favors institutional space for experimentation, so that if climate or market conditions shift beyond what incremental change can handle, the sector can reorganize rather than collapse.

Strategic foresight also changes who is involved in planning. Because scenarios are built from assumptions about driving forces, the process benefits from the participation of a wide range of actors: farmers whose livelihoods embody the practical constraints, scientists who model biophysical processes, industry actors who control supply chains, and policymakers who set incentives. Participatory foresight exercises generate a shared vocabulary for discussing uncertain futures, which can reduce polarization and help stakeholders commit to transition strategies even when they disagree about which future is most likely. The research suggests this shared understanding is itself a resilience asset, enabling faster and more coordinated responses when real-world shocks arrive.

The implications for policy design are concrete. Strategies emerging from foresight-informed analysis tend to favor portfolios over silver bullets, combining emissions-reduction measures with adaptation measures and explicit contingency planning. They favor reversible and modular interventions, which can be scaled up or down as conditions change, over irreversible commitments whose value depends on a single forecast. They favor investment in information infrastructure, including monitoring, scenario updating and early-warning capacity, so that plans can be revised as evidence accumulates. And they favor attention to distributional consequences, because a transition that concentrates risk on vulnerable farms or regions is unlikely to sustain the social support it needs through a decade of turbulence.

The study also acknowledges the limits of foresight. Scenarios are not predictions, and there is a persistent risk that decision-makers treat the most comfortable scenario as the default. Foresight works best when it is iterative, revisited as conditions change, and when its outputs are explicitly linked to decision processes rather than filed away as reports. Maintaining that discipline requires institutional commitment, but the payoff, the authors argue, is a climate-neutral farming transition that is not merely planned but genuinely robust, one that can bend under pressure without breaking and can seize unexpected opportunities as the global environment continues to shift.

Beyond the immediate design of transition strategies, the foresight perspective carries implications for how agricultural research itself is organized. Much of agronomic science is built around optimizing individual practices under relatively controlled conditions, yet the resilience questions raised here concern combinations of practices interacting with turbulent external conditions. A scenario-based framing suggests value in research portfolios that evaluate practices not only for their average performance but for their performance under stress, including how cover cropping, nutrient management and energy integration behave when input prices, labor availability or weather patterns deviate sharply from historical norms.

The connection between soil processes and transition resilience deserves particular attention. Practices such as reduced tillage, diversified rotations and organic matter accumulation are frequently promoted for their mitigation benefits, but they also function as biophysical buffers. Soils with greater organic content hold more water during dry periods and recover more quickly from extreme rainfall, which means the same interventions that reduce emissions can simultaneously dampen the impact of climate shocks on yields. This dual character complicates simple cost-benefit accounting, because a practice that appears marginal when valued only for carbon may be clearly worthwhile once its risk-reduction role is included, a point that scenario analysis is well suited to surface.

Economic heterogeneity across the farming sector is another dimension that foresight exercises tend to expose. Farms differ enormously in size, capital access, tenure arrangements and exposure to international markets, so a transition pathway that is robust for a well-capitalized arable operation may be fragile for a small mixed farm carrying debt. When scenarios are populated with this heterogeneity rather than a representative average farm, the analysis can identify which policy instruments, such as targeted credit, insurance design or transition payments, determine whether the whole sector moves together or whether vulnerable segments fall behind and undermine collective targets.

The temporal structure of shocks also matters in ways that single-scenario planning obscures. Sequences of stressful years, rather than isolated extreme events, can deplete the financial and biological buffers that farms rely on, pushing systems past thresholds that individual disturbances would not. Foresight methods that explicitly model event sequences, including back-to-back droughts or coincident market and weather disruptions, therefore provide a more demanding and more informative resilience test than average-condition analysis, and they align closely with the absorb-adapt-transform vocabulary the study employs.

Finally, the iterative character of foresight connects naturally to emerging monitoring capacity in agriculture. Satellite observation, farm-level data platforms and improved biophysical models make it increasingly feasible to track indicators of transition health, such as adoption rates, soil carbon trends and input dependencies, and to compare them against scenario assumptions. When such signals diverge from the future world a strategy was designed for, that divergence becomes an early trigger for revision rather than a crisis discovered late. In this sense, foresight is less a one-time planning exercise than an ongoing navigation discipline, one that treats the climate-neutral transition as a course to be continuously corrected through volatile conditions rather than a route to be plotted once and followed regardless of weather.

Subject of Research: Using strategic foresight methods to assess the resilience of climate-neutral agricultural transition pathways under global volatility

Article Title: Strategic foresight provides insight into the resilience of climate-neutral farming transitions in a volatile world

Article References: Styles, D., Henn, D., Duffy, C., Black, K., & Martinez-Arce, A. (2026). Strategic foresight provides insight into the resilience of climate-neutral farming transitions in a volatile world. npj Sustainable Agriculture, 4(1), Article 73. https://doi.org/10.1038/s44264-026-00185-2

Image Credits: AI Generated

DOI: 10.1038/s44264-026-00185-2

Keywords: strategic foresight, climate-neutral agriculture, farming transitions, resilience, scenario analysis, sustainable agriculture, agricultural policy, volatility, food systems, climate mitigation, adaptive capacity, agroecology