The transition to climate-neutral agriculture is one of the most consequential undertakings of the twenty-first century, and a new analysis published in npj Sustainable Agriculture argues that the tools society uses to plan that transition matter as much as the technologies and policies behind it. The study examines how strategic foresight, a structured family of methods for exploring alternative futures, can illuminate the resilience of farming systems as they move toward climate neutrality in a world defined by volatility. Rather than treating the transition as a fixed pathway from present practice to a defined endpoint, the work frames it as a dynamic process exposed to shocks, surprises and competing pressures that can derail even well-designed plans.
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
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