Have we given up on IPM? Lessons from the Nordic cereal frontier - a critical review

Abstract

Integrated Pest Management (IPM) promises a sophisticated integration of biological, cultural, genetic, and chemical tactics to manage pests sustainably (Kogan, 1998;Ehler, 2006). This vision remains central to modern crop protection discourse (Barzman et al., 2015). However, the translation of this ideal into widespread practice has been uneven, especially in large-scale cereal production. The Nordic region presents a compelling paradox: despite strong scientific capacity and ambitious sustainability goals, agriculture continues to rely heavily on prophylactic chemical treatments. Current trends illustrate this disconnect (Figure 1A,B).While the EU aims for a 50% reduction in pesticide use, sales across the continent have plateaued (Figure 1A), and in Sweden, fungicide use remains stubbornly high, fluctuating with seasonal weather rather than showing a structural decline (Figure 1B). We contend that this discrepancy is not rooted in a lack of will but in formidable biophysical realities. In high-latitude cereal systems, the classical IPM model encounters a structural ceiling imposed by adaptation constraints, compressed seasonal timelines, and an incomplete decision-support infrastructure (Olesen et al., 2011;Peltonen-Sainio et al., 2016). Recent assessments also highlight how climate variability intensifies disease risk windows and complicates timing-sensitive interventions in northern European cereal systems (Newton, 2024;Lahlali et al., 2024). In the following sections, we therefore use a small set of representative examples, including polycyclic foliar diseases in cereals and aphid vectors of BYDV, to illustrate how specific biological constraints shape the feasibility and design of IPM in Nordic systems.In this paper, we use four related terms with specific meanings that build on established IPM literature. IPM is understood as a framework for systems-based crop protection that integrates biological, cultural, physical and chemical tactics to maintain pest populations below economically damaging thresholds while minimizing environmental risks, as formalized by the Food and Agriculture Organization of the United Nations (FAO) and the European Union (EU) (FAO, 2022; EU Directive 2009/128/EC). Within this framework, an IPM strategy denotes the decision logic governing how tactics are sequenced and combined over time. For example, prioritizing host resistance and cultural practices, with chemical or biological interventions deployed only when monitored pest pressure exceeds predefined action thresholds (Kogan, 1998; Barzman et al., 2015). We use IPM levers to describe the principal tactic classes available for manipulation in practice: cultivar selection, crop rotation, biological control agents, cultural methods, and pesticide application timing (Ehler, 2006;Parlevliet and Zadoks, 1977). Finally, the IPM network refers to the emergent system arising from interactions among multiple levers and pest complexes, encompassing both vertical integration of tactics within individual pesthost systems and horizontal integration across multiple pest groups; a concept central to recent critiques of insufficient integration in contemporary IPM implementation (Barzman et al., 2015;Stenberg, 2017). The theoretical power of IPM lies in its multi-lever approach, combining host resistance, cultural practices, biological control, and monitoring to keep pest pressure below economic thresholds. In northern cereal systems, however, several of these levers are inherently compromised. While IPM principles theoretically apply to all pest classes, the specific constraints and solutions discussed below (and summarized in Table 1) primarily reflect the region's most pressing challenges: polycyclic fungal pathogens (such as Zymoseptoria and Puccinia spp.) and insect vectors of viral diseases (such as Rhopalosiphum padi). These fungal and vector systems are not treated as comprehensive case studies here, but as illustrative examples of distinct bottlenecks, such as high regional inoculum for polycyclic foliar diseases and phenological mismatch between aphid flights, virus transmission, and natural enemy activity in spring cereals Effective IPM leverages host diversity through the rotation or mixing of cultivars with complementary resistance profiles. However, in countries like Sweden, the harsh climate, with its specific photoperiod and temperature demands, significantly narrows the pool of adapted cultivars for spring barley, oats, and wheat. The dominant varieties often share similar vulnerabilities, diminishing the effectiveness of resistance rotation strategies. This genetic bottleneck allows polycyclic foliar pathogens, such as leaf blotch in wheat and net blotch in barley, to escalate rapidly under high regional inoculum pressure, even with careful variety selection (Jalli et al., 2020). Continued emergence of fungicide resistance and shifts in pathogen virulence spectra underscore the need for diversified resistance portfolios and coordinated stewardship (FRAG-UK, 2025; Minadakis et al., 2025). Cultural tactics are similarly constrained by climatic and phenological limits. Short seasons compress sowing and harvesting into tight windows, making practices like delayed sowing to avoid early infection a high-risk strategy that can lead to significant yield penalties. Cover crops and green manures often struggle to accumulate enough biomass to effectively alter soilborne disease dynamics, and the cool, slow decomposition of crop residues allows pathogens like Zymoseptoria and Fusarium to persist between seasons. While the agronomic logic of these practices is sound, their efficacy and feasibility are greatly diminished in these environments (Aronsson et al., 2016;Peltonen-Sainio et al., 2016). Biological control agents are frequently out of phase with pest and pathogen life cycles. As illustrated in the Nordic spring barley model (Figure 1C), natural enemies of cereal aphids, for instance, often build up their populations too late to prevent the initial flights of Rhopalosiphum padi and Sitobion avenae, leaving young crops vulnerable to Barley Yellow Dwarf Virus. We highlight this aphid-BYDV system because its phenology is relatively well characterized in Nordic spring cereals and thus offers a concrete, data-informed example of the broader timing mismatch that also constrains other biological control opportunities. Similarly, many microbial antagonists show inconsistent performance at the low temperatures typical of Nordic springs.While research into cold-tolerant strains is ongoing, field-scale reliability remains a significant hurdle under typical Nordic spring conditions (Smera et al., 2021). Furthermore, the ecological dependency of biological control efficacy greatly reduces its role in disease management, compounded by pathogen adaptation problems that, while potentially as severe as those affecting chemical control, receive considerably less attention and research focus (He et al., 2021;Dehbi et al., 2023). This dual challenge of environmental synchronization and pathogen evolution further constrains the practical deployment of biocontrol strategies in Nordic cereal systems. The development of seed-applied endophytes, antagonistic microbial consortia, and residuedecomposing microbiomes selected for their ability to thrive in cool conditions is a promising frontier, but current results are highly context dependent. Field reliability is constrained by several failure modes, including reduced activity at low temperatures, mismatches in timing between application, pathogen infection and crop growth, formulation stability, and the ability of introduced strains to establish in resident microbiomes (Dehbi et al., 2023;Newton, 2024).These approaches can therefore complement other IPM tactics only when their performance has been validated through multi-year, on-farm trials that capture the variability of short Nordic seasons and management regimes. Beyond these biological constraints, commercial development of biocontrol products faces a structural economic barrier in Nordic systems: the region represents a relatively small market compared to major cereal-producing areas in southern and central Europe, North America, and Asia. Consequently, commercial BCA formulations are typically optimized for persistence, shelf stability, and efficacy under the temperature and moisture regimes characteristic of these larger markets, rather than for the cooler, shorter growing seasons of northern latitudes (Alabouvette et al., 2009;Parnell et al., 2016;Köhl et al., 2019). This market-driven mismatch between formulation design and local environmental conditions compounds the inherent biological challenges, rendering many otherwise-promising BCAs unreliable under Nordic field conditions unless region-specific development programs are pursued; an investment that remains economically marginal for most commercial producers. A lack of locally validated data hinders risk-based decision-making. Many forecasting models used in advisory systems were developed for different climates and often fail to accurately predict infection dynamics under Nordic weather patterns. In the absence of reliable, local risk indicators, prophylactic spraying becomes the default, economically rational choice for many growers. Although Nordic-tuned models and surveillance systems are being developed and refined, their widespread implementation is still a work in progress (Folkedal and Brevig, 2003;Jørgensen et al., 2020;Hjelkrem et al., 2021). Recent advances in spatial decision-support systems and precision agriculture platforms demonstrate potential for field-specific risk advisories, although adoption barriers persist in advisory pipelines and data integration (Yi et al., 2024;Lanucara et al., 2024). Crop rotation, often the cornerstone of IPM, has reduced leverage in regions where break crops are agronomically or economically challenging. In much of Sweden and Finland, agroclimatic conditions and market factors limit the cultivation of grain legumes and oilseeds. Marketing challenges for alternative crops create additional barriers, as farmers may struggle to find reliable buyers and stable prices for non-cereal crops. Furthermore, transitioning to new crops requires substantial investment in specialized machinery and equipment, alongside the acquisition of new agronomic knowledge and management skills for crops that farmers may be less familiar with growing. These economic and technical barriers compound the agronomic limitations. Recent studies indicate that while diversified rotations improve yields and ecosystem services in many environments, the magnitude and feasibility of such benefits are ). As a result, the knowledge base available to operationalize IPM 2.0 is structurally richer for some disease systems than for most arthropod pests, and this asymmetry has to be acknowledged in any realistic redesign of IPM. Acknowledging these limitations allows us to move beyond an idealized IPM framework and design a more pragmatic approach: IPM 2.0. Unlike the classical model, which often assumes a fully functional toolkit of rotational and biological levers, IPM 2.0 in the Nordic context is defined as a system-redesign focused on compensatory resilience. It abandons the universal application of IPM in favor of a functional subset of tactics-specifically intra-crop diversity and digital precision-that collectively compensate for the lack of rotation and biological control options. At the same time, IPM 2.0 must explicitly integrate context-dependent ecology and genetics, which can shift roles between 'pest' and 'ally' as host genotype, climate and management change (Table 2).A practical example is wheat leaf blotch management in the Nordic-Baltic region. Under current practice, fungicide use is often guided by coarse calendar windows and visual scouting, with limited integration of cultivar resistance profiles or modelled risk, leading to both under-and over-treatment in different years (Jalli et al., 2020;Hjelkrem et al., 2021). Under an IPM 2.0 approach, mixtures of varieties with quantitative resistance, combined with locally calibrated leaf blotch DSS and spore-based surveillance, would allow growers to adjust both the need for and timing of fungicide applications at field scale (Jørgensen et al., 2020;Hjelkrem et al., 2021). This shift does not eliminate chemical control, but reframes it as a targeted, model-informed intervention embedded within a more diverse and resilient cropping system (Parlevliet and Zadoks, 1977;Brown, 2015;Rimbaud et al., 2019).For insect vectors such as cereal aphids transmitting BYDV, the transformation is necessarily more incremental because the empirical base is thinner. At present, many decisions in Nordic spring cereals default to prophylactic early-season insecticide use whenever aphids are observed or expected, in the absence of robust, locally validated thresholds or DSS (Larsson, 2005;Ghita, 2015;Sigvald, 2015). An IPM 2.0 scenario would combine existing phenology and flight information, simple field monitoring, and emerging BYDV risk tools to focus insecticide interventions on years and locations with demonstrably high risk, while omitting treatments when monitored risk is low (IPM Decisions, 2024; IPM Decisions BYDV DSS factsheet). Here, the same pillars (diversified host backgrounds where feasible, higherresolution surveillance, and participatory evaluation) still apply, but the operational framework is built around a smaller and more uncertain dataset than for fungal leaf blotch. Thus, a redesigned IPM 2.0 for constrained environments must prioritize the following: When diversification between crops is limited, we must focus on diversification within crops.Cultivar mixtures and multiline blends, which combine varieties with similar phenology but different resistance profiles, can effectively slow epidemics and the evolution of pathogen virulence (Yang et al., 2019;Huang et al., 2024). For Swedish spring barley and oats, where adapted cultivar choice is narrow, developing mixture-ready lines would embed IPM at the seed level, shifting from a reactive to a proactive strategy. This is particularly relevant for diseases like crown rust in oats, where even modest, stable reductions in pathogen reproduction can provide significant protection over a short growing season (Østergård, 2005 The credibility of IPM hinges on replacing risk-averse, prophylactic spraying with data-driven interventions. This transition relies on the integration of precision agriculture technologies (specifically the Internet of Things (IoT), automated surveillance, and cloud-computing), into cereal disease management. Current forecasting models often fail because they lack local granularity. However, the emerging generation of Spatial Decision Support Systems (SDSS) offers a solution by processing real-time environmental data to generate site-specific risk advisories. Recent reviews of precision agriculture emphasize that shifting from regional forecasts to field-level predictions is essential for reducing pesticide loads in volatile climates (Lanucara et al., 2024;Yi et al., 2024). Where basic phenological and flight data exist for key insect vectors (for example, cereal aphids involved in BYDV transmission) these can be integrated alongside pathogen risk models to design unified, field-specific decision support around narrow early-season windows.In the Nordic context, credible DSS must be validated under local climates and cropping systems, not only calibrated elsewhere. This implies multi-year, multi-location evaluations that test whether models correctly identify both situations where interventions are needed (high sensitivity) and where they can safely be omitted (high specificity), and that quantify yield We need to advance ecological regulation that is effective at low temperatures. The development of seed-applied endophytes, antagonistic microbial consortia, and residue-decomposing microbiomes selected for their ability to thrive in cool conditions is a promising frontier, but current results are highly context dependent. Field reliability is constrained by several failure modes, including reduced activity at low temperatures, mismatches in timing between application, pathogen infection and crop growth, formulation stability, and the ability of introduced strains to establish in resident microbiomes (Dehbi et al., 2023;Newton, 2024).These approaches can therefore complement other IPM tactics only when their performance has been validated through multi-year, on-farm trials that capture the variability of short Nordic seasons and management regimes.Recent work with the fungal biocontrol agent Clonostachys rosea illustrates both the potential and the complexity of deploying microbial allies in IPM 2.0, as summarized in Table 2. such that an isolate recovered from Uppsala may fail to establish or perform consistently in western Norway, southern Finland, or Danish coastal soils, even when applied to the same crop species (Harkes et al., 2020;Trivedi et al., 2020). Taken together, these findings underscore that ecological fit (encompassing host genotype, resident microbiome composition, and temperature regime) is central to BCA performance in IPM 2.0, and that, unlike chemical fungicides, there are currently no decision-support tools to predict which isolate-cultivar-location combinations will be both effective and safe. IPM 2.0 implementation in Nordic cereal systems requires continuous optimization through participatory on-farm research that quantifies the cumulative effects of deploying multiple tactics simultaneously under commercial conditions. Unlike prescriptive checklists, this approach treats IPM as an adaptive learning system where growers, advisors, and researchers jointly evaluate performance and refine decision rules based on observed outcomes (Kogan, 1998; Barzman et al., 2015).Concrete examples demonstrate this principle in action. In Norway, multi-year on-farm trials coordinated through NIBIO (Norwegian Institute of Bioeconomy Research) have tested cultivar mixtures combined with DSS-guided fungicide applications across diverse environments, documenting both yield stability gains and instances where mixtures underperformed monocultures under specific disease pressures, thereby refining recommendations for regional contexts (Jørgensen et al., 2020;Abrahamsen et al., 2020). Similarly, Swedish field trials evaluating seed-applied biocontrol agents for cereal pathogens have transparently reported both successful disease suppression and failures linked to environmental conditions, providing the empirical basis for defining deployment windows and compatible management practices (Jensen et al., 2016). These participatory frameworks ensure that tactical refinements -such as adjusting spray thresholds for Zymoseptoria tritici based on cultivar resistance profiles or recalibrating BYDV risk models for regional aphid phenology-emerge from systematic field observation rather than theoretical extrapolation (Jørgensen et al., 2020;Hjelkrem et al., 2021).Critical to this process is transparent reporting of both successes and failures, which allows the research community to identify context-dependent constraints and avoid overgeneralizing from site-specific results (Wolfe et al., 2008;Huang et al., 2024). For instance, Danish evaluations of reduced fungicide programs in organic spring barley revealed that while cultivar resistance delayed infection, economic thresholds still required intervention in high-disease years, underscoring the limits of single-tactic reliance even in low-input systems (Jalli et al., 2020). Such iterative learning cycles, embedded within regional advisory networks, enable IPM 2.0 to function as a continuously evolving system calibrated to local climate variability, pest pressure dynamics, and grower risk tolerance (Roitsch et al., 2022;Yang et al., 2024). Operationally, IPM 2.0 in constrained Nordic cereal systems is defined by three core elements:(i) prioritizing intra-crop genetic diversity (cultivar mixtures) and quantitative resistance as the foundational tactic, (ii) using locally validated surveillance and decision-support systems (DSS) to determine if and when chemical or biological interventions are justified, and (iii) continuously updating decision thresholds through participatory on-farm evaluation (Parlevliet and Zadoks, 1977;Barzman et al., 2015;Wolfe et al., 2008). In practice, this shifts grower decision-making from calendar-based spraying to dynamic risk assessment: the number and timing of fungicide applications, the composition of cultivar mixtures, and the interpretation of DSS outputs become the active variables adjusted each season based on monitored disease pressure and cultivar-specific resistance profiles (Kogan, 1998;Hjelkrem et al., 2021).The pathway to widespread DSS adoption hinges on embedding these tools within existing advisory infrastructure and demonstrating value through transparent validation. The Norwegian VIPS platform (Plant Protection Information System) exemplifies this approach: developed through collaboration among NIBIO, agricultural extension services, and grower cooperatives, VIPS integrates weather-based disease models, regional pest monitoring data, and cultivar resistance ratings to generate field-specific spray recommendations (Folkedal and Brevig, 2003;Hjelkrem et al., 2021). Adoption has been facilitated by (i) multi-year field validation demonstrating that VIPS-guided interventions reduce fungicide use by 20-30% in low-disease years without yield penalty, (ii) seamless integration with farm management software used by cooperatives, and (iii) continuous model refinement based on feedback from advisory agronomists who flag prediction failures (Jørgensen et al., 2020).Similarly, the pan-European IPM Decisions platform has demonstrated that grower trust and routine DSS use require transparent reporting of validation contexts (climate zones, cropping systems, disease thresholds), easy access to localized weather and crop phenology data, and active co-design with advisors to ensure model outputs align with on-farm decision constraints (IPM Decisions Consortium, 2024; Lanucara et al., 2024;Yi et al., 2024). For Nordic cereals, this suggests a stepwise integration model where national advisory services (e.g. The Swedish Board of Agriculture in Sweden) host DSS platforms, aggregate data from on-farm weather stations and public monitoring networks, and coordinate participatory trials that evaluate economic thresholds, usability, and compatibility with regional pest pressures before broader rollout (Ficke et al., 2022). Critically, this infrastructure must accommodate regional variation: a leaf blotch DSS validated for southern Sweden may require recalibration for northern Finland, where spring phenology compression and lower temperature thresholds alter infection windows (Hjelkrem et al., 2021). Only through such context-aware deployment can IPM 2.0 deliver credible, farmer-adopted decision support in constrained northern cereal systems. The Nordic cereal frontier exposes a fundamental tension in contemporary IPM: the classical model assumes a functional toolkit of diverse rotations, biological control, and cultural practices that simply cannot be fully realized under climatic and agronomic constraints characteristic of northern latitudes. Short growing seasons, narrow crop diversity, phenological mismatches between pests and natural enemies, and limited economic scale for region-specific biocontrol formulations collectively render several foundational IPM levers inoperable or unreliable. This does not constitute a failure of IPM as a concept, but rather reveals that its universal application has reached ecological and practical limits in constrained agroecosystems. IPM 2.0 for Nordic cereals (Figure 2) offers a context-adapted framework built on three pillars: (i) prioritizing intra-crop genetic diversity through cultivar mixtures and quantitative resistance as the baseline tactic, compensating for limited rotation options; (ii) deploying locally calibrated surveillance networks and decision-support systems to replace prophylactic chemical interventions with risk-based, threshold-driven applications; and (iii) embedding continuous participatory learning through multi-location on-farm trials that transparently document both successes and context-dependent failures. This redesign explicitly acknowledges that some classical IPM tactics are functionally unavailable in Nordic systems, while concentrating resources on the subset of interventions that deliver measurable, cumulative resilience under constraint.The expected near-term outcomes of IPM 2.0 implementation are concrete and measurable. For insect pest management, the integration of aphid flight monitoring, cultivar resistance ratings, and emerging BYDV risk models (IPM Decisions Consortium, 2024) can shift grower decisions from routine prophylactic seed treatments to targeted foliar insecticides applied only when monitored aphid pressure and virus risk exceed validated thresholds, reducing insecticide use in low-risk years while maintaining protection in epidemic seasons (Sigvald, 2015;Ghita, 2015). For fungal pathogen management, combining cultivar mixtures with DSS-guided fungicide applications -exemplified by the Norwegian VIPS platform-has demonstrated 20-30% reductions in fungicide applications in favorable years without yield penalty, while maintaining intervention capacity when weather-driven disease pressure warrants treatment (Jørgensen et al., 2020;Hjelkrem et al., 2021). Critically, these outcomes depend on resistance stewardship: deploying quantitative resistance within mixtures slows pathogen adaptation compared to single-gene deployment, extending the functional lifespan of both genetic and chemical tools (Parlevliet and Zadoks, 1977;Rimbaud et al., 2019).Realizing these outcomes requires moving IPM 2.0 from concept to operational practice through the stepwise adoption pathway outlined in Figure 2. Research institutions (e.g. NIBIO, LUKE, SLU) must continue multi-location validation of DSS under Nordic climates, ensuring models correctly identify both high-risk situations requiring intervention and low-risk scenarios where treatments can be safely omitted. Advisory services and grower cooperatives (e.g Lantmännen, agricultural extension networks) must integrate validated DSS into existing decision workflows, providing training and on-farm demonstrations that build grower confidence in risk-based management. Crucially, this transition requires transparent reporting of failures alongside successes: documenting when and why DSS predictions underperform, or when cultivar mixtures fail to suppress disease, generates the empirical feedback necessary to refine models, adjust thresholds, and identify the environmental boundaries within which each tactic remains reliable (Wolfe et al., 2008;Huang et al., 2024). By reframing IPM not as a static checklist but as an adaptive, data-driven system calibrated to regional constraints, we ensure that pest management remains scientifically credible and practically viable even in agroecosystems where classical IPM assumptions do not hold. This evolution is essential for maintaining the relevance of IPM as a discipline: if IPM principles cannot be operationalized in constrained systems through redesign, they risk becoming aspirational rhetoric disconnected from grower realities. The Nordic experience demonstrates that acknowledging ecological limits, concentrating on functional tactics, and embedding continuous learning within advisory infrastructure can deliver tangible pesticide reductions and enhanced system resilience: outcomes that justify IPM 2.0 as a legitimate evolution of integrated pest management for the climate frontiers of modern agriculture. thresholds and calibrate DSS, (ii) integration into existing advisory infrastructure with on-farm demonstrations and usability testing, and (iii) iterative scaling with continuous feedback loops for regional refinement. Bottom panel: Expected benefits include reduced prophylactic pesticide applications, maintained yield stability, enhanced resistance durability through strategic deployment, and climate-adapted pest management responsive to regional constraints.