Editorial: Cropping systems adaptation in the context of global change: current trends and future directions

Introduction

Agriculture is evolving amid accelerating environmental and socio-economic changes. Climate shifts, soil degradation, biodiversity loss, resource constraints and new socio-economic conditions are reshaping production environments and influencing farmers’ decisions. Rising temperatures, shifting rainfall patterns, extreme weather events, and altered distribution of pests and diseases contribute to variability in crop performance and affect the functioning of agro-ecosystems. In this setting, adaptation increasingly requires strategies that go beyond incremental adjustments and support the transformation of cropping systems while safeguarding food security, ecosystem health and human well-being, and rural livelihoods.

This Research Topic was conceived to capture the diversity of contemporary approaches to cropping systems adaptation in the context of global environmental and socio-economic change. We aimed to assemble contributions that span disciplinary boundaries (from plant physiology to climate modelling and socio-economic analysis) and that reflect the geographic breadth of adaptation challenges. We invited submissions that addressed both current adaptation practices and forward-looking strategies, with an emphasis on empirical evidence, predictive tools, and participatory approaches.

The eight contributions assembled in this Research Topic (Table 1) span four continents and encompass diverse production environments, featuring annual arable crops such as cereals and grain legumes, as well as drought-resilient perennials like cactus pears (Opuntia ficus-indica).

Table 1. Synthesis of contributions to the Research Topic on cropping systems adaptation to global change.

Employing approaches ranging from crop physiology and ecophysiology to climate modelling and socio-economic research, they demonstrated that successful adaptation is becoming increasingly proactive and interdisciplinary. Figure 1 frames adaptation science as an upward trajectory: stressors at the base, interdisciplinary convergence in the trunk, and current versus future levers branching into the canopy. The eight contributions map onto these branches but leave gaps, especially in systems-level transformation and neglected perennial, forage, and mixed crop–livestock systems.

Collectively, these studies illustrate the evolution of adaptation research and highlight important knowledge gaps. A notable pattern emerged: seven of the eight studies focused on annual arable crops (cereal and grain legumes), while other major agricultural domains (grasslands and rangelands, forage and mixed crop–livestock systems, agroforestry, orchards, vineyards, and other perennial production systems) remained largely absent. Despite their extensive global coverage and central role in the agro-ecological transition, these systems remain comparatively understudied, even though they underpin carbon storage, biodiversity conservation, soil protection and landscape resilience, and support millions of livelihoods. Their limited representation highlights a critical frontier for future studies.

Current trends in adaptation science

Across the Research Topic, climate adaptation science appears to be increasingly anticipatory. Four complementary levers stand out: (i) the strategic use of genetic resources, (ii) the identification of limiting climatic processes, (iii) the growing reliance on predictive modelling, and (iv) the central role of farmers in adaptation decisions.

Strategic use of genetic resources

Studies on oats in China (Tang et al.), common beans in Tanzania (Kalemera et al.), and cowpeas in West Africa and Peru (Adusei et al.; Murga-Orrillo et al.) show that selecting cultivars or genotypes suited to changing climatic conditions can substantially enhance resilience. These contributions underscore the convergence between plant breeding, crop modelling and climate science: spatial suitability analyses and crop simulations help identify where production zones may shift and which genotypes are likely to perform well under future conditions.

Identification of limiting climatic processes provides

Extreme low temperatures, rather than average seasonal conditions, have been identified as the principal constraint on winter wheat yields in northwestern China (Zhang et al.). Research on drought-resilient perennial species such as Opuntia ficus-indica (Hermassi et al.) shows how evapotranspiration dynamics can inform adaptation strategies in semi-arid environments. These studies demonstrate that identifying the specific processes driving crop vulnerability can provide more actionable guidance for targeted interventions than analyses based solely on mean climate trends.

Growing reliance on predictive modelling

Four contributions used modelling frameworks (including crop simulation, climatic suitability analysis, and spatial modelling) to explore how agricultural systems perfom under future climate (Adusei et al.; Tang et al.; Kalemera et al.; Zhang et al.). These approaches support breeding programmes, guide regional crop allocation, identify future production frontiers and inform adaptation investments. They also highlight the importance of ensemble approaches and transparent communication of uncertainty, given the influence of climate scenarios, bias adjustment procedures and model structures on adaptation recommendations. As climate services, remote sensing, artificial intelligence and digital agriculture advance, predictive decision support will become even more integral to climate-resilient farming. However, the reliance on modelling approaches also invites caution. Crop models are simplifications of complex biological and environmental processes, and their projections are contingent on the quality of input data, the appropriateness of model parameterisation, and the validity of assumptions about future management practices and atmospheric CO₂ concentrations. The sensitivity of adaptation recommendations to climate scenario selection and bias adjustment procedures, noted in several contributions, underscores the importance of ensemble approaches and transparent communication of uncertainty. Efforts to ground-truth model outputs against field observations and to incorporate farmer knowledge into model parameterisation would further strengthen the credibility and relevance of modelling-based adaptation guidance.

Central role of farmers in adaptation decisions

Evidence from Kenya shows that varietal choices reflect a balance of agronomic performance, market dynamics, seed availability, familiarity and perceived reliability (Mawia et al.). A systematic review of South Asian wheat systems demonstrated that successful adaptation rarely relies on a single measure but emerges from coordinated technological, agronomic and institutional interventions (Chakrabarti et al.). These findings reinforce the need for resilient agricultural systems that require strengthening seed systems, extension services, market incentives, and participatory innovation alongside advances in genetics and management.

Several broader trends characterize contemporary adaptation research. The field is becoming increasingly interdisciplinary, combining climate science, crop physiology, modelling, breeding and socio-economic analysis. Attention is shifting from average climatic conditions toward variability and extremes, with a growing focus on heat waves, drought episodes, rainfall variability and cold extremes. Adaptation research is also becoming more proactive, using predictive tools to anticipate risks and evaluate options before they become urgent issues. However, integration across cropping systems, ecosystems and the socio-economic dimensions of farming likewise remains under-explored.

Looking ahead

Adaptation science has entered a new phase. Significant progress has been made in identifying climate-resilient crops and cultivars, developing predictive modelling frameworks and improving our understanding of crop responses to environmental change. Further opportunities lie in strengthening the climate-predictive capacity of adaptation science. None of the contributions in this Research Topicengaged with sub-seasonal to seasonal climate prediction, yet coupling seasonal forecasts with crop models is a mature field (Hansen et al., 2006) with considerable potential to anticipate hazards and production risks before the growing season. Climatic teleconnections such as the El Niño–Southern Oscillation offer predictable signals that can be integrated into crop and systems modelling to support proactive decision-making. Advances in atmospheric science, particularly in cloud dynamics and surface albedo, further warrant attention: shifts in cloud regimes and land–atmosphere radiative exchanges shape the local energy balance, water availability and crop stress. Integrating these processes would enhance climate impact assessments and operational decision support, particularly in water-limited environments.

Ultimately, the next challenge extends beyond the identification of suitable crops or cultivars. It involves redesigning agricultural systems that are resilient to long-term climate change and responsive to year-to-year variability, while preserving biodiversity, restoring soil health, reducing emissions and losses, improving resource-use efficiency, and sustaining farmers’ livelihoods. This reframing from incremental to transformational adaptation (Rickards and Howden, 2012) and from crop-level to systems-level responses (Vermeulen et al., 2018) reflects a broader evolution in adaptation science. The scientific question is evolving from “how can individual crops adapt” to “how can agricultural systems transform”.

Conclusions

The eight articles assembled in this Research Topic illustrate the growing sophistication of adaptation research and the diversity of approaches for anticipating climatic risks and identifying resilient production strategies. They also reveal an evolution in the field, from a focus on individual crops to a broader concern with systems transformation. This shift brings new challenges: strengthening the resilience of agroecosystems as integrated systems is as important as improving their individual components, and interdisciplinary collaboration across biophysical and socio-economic domains will be essential. We hope that this Research Topic will contribute useful insights and encourage continued work to support productive, sustainable, and climate-resilient agricultural systems.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. During the preparation of this work, the author(s) used Paperpal to check grammar, and Gemini/Qwen AI was used to generate the image. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published work.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

Edited and reviewed by: M. Habib Ur-Rahman, University of Göttingen, Germany