The arable sector is a cornerstone of NZ agricultural production system, contributing to food security, economic stability, and environmental sustainability. It provides the nation’s staple crops—such as wheat, barley, maize, oats, and other cereals—which form the foundation of both human nutrition and livestock feed (Arable food Industry Council, 2022). Many of these crops also serve as essential raw materials for the food processing industry, including wheat, soybeans, nuts, and sugar, thereby adding value to the agricultural economy and supporting domestic food manufacturing (Indicators | Stats NZ, 2022). In addition, the sector plays a crucial role in supplying feed for NZ extensive dairy and livestock industries, particularly through maize silage and grain production, which are indispensable for sustaining dairy cows, beef cattle, and other livestock (Arable food Industry Council, 2022).

Although arable products directly account for only about 0.5% of NZ total export earnings, they underpin the much larger export sectors of dairy, meat, and processed foods, which depend heavily on locally produced grain and feed inputs (Ministry for Primary Industries, 2022). Arable farming practices also enhance long-term sustainability through crop rotation and system diversification, helping to maintain soil health, reduce pest and disease pressure, and improve system resilience (Antille et al., 2022). Economically, the arable sector supports rural communities by providing employment and generating income through the production and sale of crops, farm equipment, and associated services (Indicators | Stats NZ, 2022; Ministry for Primary Industries, 2022).

To help achieve NZ environmental and economic objectives, the arable sector plays an increasingly strategic role by delivering co-benefits across the food security, economic, and environmental nexus. Its capacity to produce locally sourced grains and feed reduces reliance on imports, supports national food resilience, and contributes to emission reductions by lowering the embedded carbon footprint of feed supply chains. At the same time, the sector offers complementarity and trade-offs with livestock production systems: arable crops can mitigate the environmental impacts of the dairy sector by providing lower-emission feed alternatives and reducing the costs and uncertainties associated with overseas grain purchases (Beukes et al., 2019; Horn and Isselstein, 2022). Due to its significant contributions to food security, economic prosperity, and potential for enhancing environmental sustainability, the arable sector holds a vital position within NZ agricultural landscape. Its continued growth and development are essential for meeting the challenges posed by global uncertainties and ensuring a thriving agricultural sector for the future (Ministry for Primary Industries, 2022).

Building on this foundational role, the following sections introduce the DST developed to model how the arable sector’s production systems can evolve under future scenarios and support stakeholder decision-making toward sustainable and low-emission pathways.

We developed a Decision Support Tool (DST) to explore different pathways and interventions for increasing the profitability, resilience, and sustainability of agriculture in NZ over the next 5–30 years. This user-friendly interface makes it possible to explore scenarios related to the development of a particular crop, changes to the whole sector, the evolution of prices, changes in yields, as well as the environmental effects of changes in agricultural practices (fertilization, irrigation, livestock feed).

Methods used for the national level multi-sector DST are detailed in Vannier et al. (2022a). Briefly, a linear statistical model, the first of its kind, was developed to represent the whole agricultural system of NZ at the national scale. The model brings together all the different sectors production, market values, land and water use, energy and fertiliser consumptions, and emissions. The model quantifies agricultural outputs relative to resilience, sustainability, and profitability, i.e., carbon emissions and offset consequences, irrigation water use, and water quality as influenced by land use, technology, agricultural production value, and other factors. The model runs with baseline data of 2019–2020, is validated using historical data, and is designed to integrate user assumptions and compute output indicators for 2050. Ultimately, the model aims to be used for building disruptive scenarios and explore pathways to reach government objectives of ensuring high export value production and carbon neutrality by 2050.

Beyond its technical capacity, the originality of the DST lies in its interactive and participatory design, which directly supports evidence-based decision-making. Through iterative and immediate (live) scenario simulations, stakeholders—including the Foundation for Arable Research (FAR)—used the DST to test assumptions about land use, emissions targets, and profitability under real policy and market constraints. This approach enabled a shared understanding of trade-offs and synergies across sectors, improving the transparency of strategic discussions and the alignment between scientific outputs and on-farm realities. The DST therefore serves not only as a modelling tool but also as a decision facilitation platform that bridges research and practical policy formulation.

This study involved collaboration with stakeholders from the Foundation for Arable Research (FAR), an applied research organisation involved in specific research programmes driven by the interests of NZ growers: maximising productivity and value; environmental and social best practices; and resilient cropping in farming systems. FAR supports NZ’s arable farmers by creating new knowledge, tools, and technologies to support responsible and profitable farming. The scenarios developed in this study emerged from an iterative co-design process with FAR. Through an initial workshop (June 2022), a subsequent work/study site visit (November 2022), continuous email and online interactions, and a final workshop (December 2022), a reliable partnership with FAR was established. Stakeholders were invited to identify the types of agricultural production most important to them, reflect on recent and long-term changes in the arable sector, and discuss current and anticipated challenges, including market dynamics, regulatory pressures, and the impacts of climate change on productivity and resource use. These exchanges helped clarify stakeholder priorities and decision needs, leading to the identification of three key themes for scenario development: food security (wheat self-sufficiency), climate change mitigation through arable–livestock interactions, and alternative protein production. For each theme, stakeholders contributed to defining the questions of interest, the elements to be included, and the assumptions to be tested. Researchers and stakeholders then jointly developed narrative descriptions of the scenarios, which were translated into quantitative inputs within the Decision Support Tool, ensuring that the scenarios were both scientifically robust and grounded in real-world industry contexts.

The co-development process ensured that model outputs reflected the information needs of end users rather than theoretical assumptions. During the workshops, stakeholders actively manipulated scenario inputs within the DST interface, which helped them evaluate the feasibility and economic consequences of different strategies. This hands-on exploration was critical for fostering ownership of the results and for integrating model outcomes into practical decision pathways at both farm and policy levels.

Production area and/or yields were increased to achieve the target of producing 700,000 tonnes of wheat in NZ. To illustrate the effect of multiple bad weather seasons (either droughts or very wet springs), one simulation showing lower yields than 2021 was run (with yield = 8 t/ha). Results show the need to grow significantly more wheat area to achieve grain self-sufficiency (Table 2). Keeping the current average yield of 9.9 t/ha or improving it to 12 t/ha (by using widely the technology of precision agriculture) will require an extra 13 k to 25 k hectares of wheat area. Irrigation water used requirement, if current irrigation standards are applied (i.e., a mean of 295 mm/year for wheat production) would increase by 8 to 30.5%. CO₂ equivalent emissions from Nitrogen (i.e., 267 Gg CO₂eq estimated in 2021) would increase by 9.3 to 31.8%. However, introducing this wheat production in a livestock system (i.e., Dairy) would have a positive impact, producing almost 8 times less CO₂eq biogenic emissions and using one-third less water for irrigation than irrigated pastures. A sensitivity analysis was performed to examine how the results respond to variations in key parameters, particularly crop yields and land area allocation. Results show that the total production and associated emission benefits are highly sensitive to yield assumptions: a 1 t/ha increase in average wheat yield changes national wheat self-sufficiency by approximately ±8–10%. Conversely, variations in the irrigated area have a smaller proportional effect on total emissions than on production. These findings underline the importance of technological and agronomic improvements, but also highlight that the model outcomes depend strongly on yield trajectories that are uncertain over multi-decadal timescales.

The upper bound of 15 t/ha (Table 2) was explored only as a hypothetical best-case limit, representing the combined effect of high-yielding cultivars, precision nutrient management, and favourable climate conditions. Although such yields have been occasionally achieved in experimental trials in Canterbury, NZ, and parts of the UK, they remain agronomically exceptional and unlikely to be achieved consistently at national scale by 2050.

Similar scenario analyses in Europe and Australia also highlight cereal self-sufficiency as a viable resilience strategy under climate uncertainty. For instance, the European Commission’s “Farm to Fork” projections show that modest increases in cereal area (10–15%) combined with input efficiency gains could offset grain import dependency while meeting emission targets (Menegat et al., 2022). Likewise, Australian modelling using the APSIM platform suggests that yield improvements from precision irrigation can increase significantly wheat output without proportionally raising water demand (Zhang et al., 2022; Richetti et al., 2024). These parallels support the NZ results, indicating that targeted expansion of irrigated cereals can enhance food security with manageable environmental trade-offs.

Two main levers were tested to reduce emissions, a decrease of herd numbers by 5, 10 and 15% (dairy and beef) and a significant introduction of alternative feed in the animal diet of about 10, 20 and 30%. The amount of methane and nitrogen emitted for those combinations were computed. Table 3 highlights the combinations that meet the government goals for 2030 (−10% of 2017 emission, i.e., 21.06 k Gg CO2eq) and 2050 (−24 to 47% of 2017 emission, i.e., 17.8 k to 12.4 k Gg CO2eq respectively) in terms of methane emissions. It also displays the nitrogen emission reduction for each combination. A herd reduction of about 10 or 15% combined with an increase of 30% of alternative diet (brassica and grains) in the animal feed allow to reach the objective for methane emissions in 2050. This combination also allows reductions of 21% to more than 23% emissions from nitrogen. A herd reduction of about 0 to 5% and an increase of alternative diet at about 20 to 30% allows to reach the 2030 objective for methane emissions. This combination reduces emissions from nitrogen by 15.2 to 18%. From the environmental side, introducing this alternative feed production in a dairy system could have a clear positive impact, as grain production results in almost 8 times less CO2eq biogenic emissions and uses one-third less water for irrigation than dairy pasture.

Comparable mixed-system mitigation scenarios have been tested internationally. In the Netherlands and Denmark, integrated modelling of reduced stocking rates and alternative feeds achieved 25–30% methane cuts, aligning closely with the reductions simulated here (de Klein et al., 2020). Studies in Ireland’s Teagasc Marginal Abatement Cost Curve project also show that combining herd efficiency with feed substitution yields stronger GHG benefits than technological fixes alone (Lanigan and Donellan, 2018). These findings confirm that NZ strategy—moderate herd reduction plus feed diversification—is consistent with best-practice international pathways for balancing productivity and emissions goals.

The total protein produced in NZ in 2019 was 97 g/capita/day (source: FAOSTAT). Out of the 97 g/capita/day, 56 g came from animal products and 41 g from vegetal products, i.e., 25 g from crops, 10 g from pulses, oils, roots, nuts and others 6 g from fruits and vegetables. Proteins from cereals mainly comes from wheat (69%). Currently, peas only supply about 1% of the proteins from cereal. Protein from peas in the NZ food supply play a minor role.

Scenarios of combinations of land areas (7 k ha, 17.5 k ha, 25 k ha, 105 k ha), yields (3.5 t/ha, 5 t/ha), and prices (960$/t, 1,200$/t, 3,000$/t) for growing peas to supply up to 10% of the protein needs in NZ have been simulated and presented in Table 4. The scenario parameters assumptions are based on the Feasibility of Pea and Fava Bean Protein Extraction in NZ report and discussion with the stakeholder. The scenario assumes an extraction facility capable of processing 15,000 tonnes of peas and that the cost for that facility is approximately NZD$50 million to establish. Results show that best combinations allow up to 7 extraction facilities by 2050. High environmental gains are expected: peas and beans required half the amount of irrigation water, and 5 times less nitrogen to grow than other mainstream crops, 3 times less than maximum authorized for pastures.

Global scenario work on alternative proteins, such as the Protein 2050 Initiative (Morach et al., 2021) and FAO foresight analyses (FAO, 2022), similarly project strong economic and environmental co-benefits when legumes substitute part of animal protein demand. European case studies in France and the UK found that scaling up pulse crops to 10–15% of cropland could reduce sectoral GHG emissions by 15–20% while boosting farm profitability. These patterns reinforce the NZ findings, confirming that investment in plant-protein processing and value-chain integration is essential to capture both domestic and export market opportunities.

Our DST allows to simulate and assess a wide range of future scenarios, but it does not consider the transition challenges of implementing the preferred scenarios. Stakeholders’ input and feedback in this study have allowed to highlight how the growth in wheat, alternative feed or pea/bean production increase could be achieved, what are the challenges and limitation to trigger these changes, who makes the decisions, and how it could be implemented. Those elements are discussed in the following paragraphs.

Interpretation of the scenario results has been analysed in light of the stakeholder perspectives that guided their development. The scenarios do not represent an exhaustive set of possible futures, but rather reflect the priorities, concerns, and decision contexts articulated by the stakeholders. Stakeholders evaluated scenarios not only on their biophysical and economic outcomes, but also on their perceived feasibility, alignment with existing farming systems, infrastructure constraints, and market realities. For example, scenarios involving increased wheat production or alternative feed integration were assessed by stakeholders in relation to labour availability, machinery requirements, irrigation capacity, and compatibility with dairy system operations, while alternative protein scenarios were considered in the context of processing infrastructure, market certainty, and price signals. As a result, scenario outcomes that appear optimal from a modelling perspective may face significant implementation barriers, whereas more moderate pathways may be viewed by stakeholders as more realistic and actionable. Incorporating these perspectives highlights the value of participatory process for identifying not only technically viable pathways, but also those most likely to be adopted in practice.

Growing grains with the help of the Dairy sector, for example, will require more contractors (work force), machinery, and may raise irrigation pressure points during key growth stages. Most of the 425,000 tonnes of wheat grown annually are produced in the Canterbury plains, where a combination of good soils and irrigation system allow high yields. This makes the region well set up for an increase of wheat production. If we consider a stocking rate reduction in the Dairy system to accommodate wheat, this would also benefit freshwater objectives and GHG emission reduction. To implement such a change, dairy farmers would have to be convinced about profitability margins, including considerations of any required emissions reductions. There are several options to implement this shift for specific farmers: working with their own machinery and tractor driver, doing a reasonable amount of the work themselves; or hiring a contractor for sowing, tillage and harvesting as required; or leasing the land to an arable farmer.

A second side impact of increasing grain production is increasing storage and infrastructure. There are specific requirements around storage and conditioning of grain which would result in a need for more facilities, an increase in capacity of some machinery and more transport. However, according to FAR stakeholders, domestic transport deficiencies and relative prices mean that sometimes it’s cheaper to bring wheat into the country than grow it in the South Island and transport it up to Auckland (internal transport costs can be higher than bringing product from Australia). Currently there’s not enough infrastructure and volume to make it happen. However, considering the effects of climate change, developing new arable land further south in Southland and south Otago as well as in the east and south of the North Island, Waikato and up to Northland, could provide the economy of scale.

Similar requirements apply when it comes to increasing brassica and grain production, i.e., increasing storage, infrastructure, and the need for a larger work force. Home-grown alternative feeds could also reduce our reliance on imported Palm Kernel Extract, which produces even higher levels of methane when digested than pasture. Moreover, nearly one-third less irrigation would be required for such a system, which could see changes in irrigation water used and associated environmental impacts.

Environmental benefits from alternative protein development alone are unlikely to sway growers according to FAR, as peas are not currently a high value crop. NZ is already importing both pea and fava bean protein. Placing greater value on locally grown protein may be a key strategy to develop this market. However, another challenge is the current lack of a protein processing plants in the country. Building the necessary plants is evaluated at $50 million (PwC, 2022), but crop areas will have to increase substantially to make the build worthwhile. Some serious co-operation between growers, processors and food manufactures will be needed to start investing in an alternative protein market, and a premium for the final products must be assured.

An important consideration in these scenarios is whether increased arable land area competes with other land uses, particularly natural ecosystems. In this study, arable expansion is assumed to occur mainly on high-quality soils with existing irrigation infrastructure, which are currently dominated by dairy production rather than native or semi-natural land cover. Given the large scale of the dairy sector, modest reductions in dairy cow numbers, combined with continued efficiency gains, could accommodate increased arable production without reducing overall food output. Such reallocation may also deliver environmental co-benefits, as arable crops typically require less irrigation and generate lower biogenic greenhouse gas emissions per hectare than irrigated dairy pasture.

The scenarios developed in this study reveal the urgent need to integrate spatially explicit modelling into national-scale analyses. While the current DST provides powerful insights into production, emissions, and resource use at an aggregated national level, its results cannot yet capture regional heterogeneity in land-use potential, climate risk, infrastructure, or water allocation. Understanding these spatial dimensions is critical for supporting targeted policy design, regional investment planning, and place-based adaptation strategies.

At present, fine-scale information on crop rotations, irrigation infrastructure, and land-use transitions remains fragmented or incomplete, which limits the capacity to test how scenarios could unfold across NZ diverse landscapes. As such, several assumptions were required regarding land suitability and crop distribution. These uncertainties point to a major research gap: the lack of integrated spatial datasets linking arable systems with environmental constraints and socio-economic drivers.

Future development of the DST should therefore focus on coupling the existing systems model with geospatial data layers (e.g., soil, climate, and irrigation maps) and remote-sensing products to enable spatially resolved simulations. This would allow decision-makers to visualise where and how scenario interventions—such as wheat expansion or alternative protein cropping—are most feasible, and where they may generate trade-offs with other sectors or environmental limits. It would allow the DST to evaluate multiple climate scenarios by translating projected regional climate changes into crop suitability, yield, and irrigation-demand responses. It would also enable region-specific feasibility and constraint analysis (soil capability, irrigation infrastructure, competing land uses) and catchment-level environmental assessment (water allocation, leaching/erosion risk), improving the tool’s capacity to test targeted policies and realistic transition pathways. Integrating these spatial components will transform the DST from a national diagnostic model into a spatial decision-support platform, capable of guiding regional transitions toward sustainable and climate-resilient agriculture.

The scenarios generated by the decision support tool reveal clear trade-offs between production, environmental performance, and implementation feasibility. In Scenario 1, increased wheat production improves domestic food security but leads to higher irrigation demand and nitrogen-related emissions when current management practices are assumed. However, these impacts are strongly context-dependent: where expanded arable cropping substitutes for irrigated dairy pasture, both water use and biogenic methane emissions may decline, highlighting the importance of system-level land-use reallocation rather than crop expansion in isolation. Scenario 2 illustrates a trade-off between emissions reduction and production structure, with the largest methane and nitrogen reductions achieved through a combination of reduced livestock intensity and alternative feed use, implying transitional and logistical constraints alongside environmental benefits. Scenario 3 presents lower-input legume systems as environmentally advantageous, particularly in terms of nitrogen use, but economically contingent on market development, processing infrastructure, and supply-chain coordination.

Comparable trade-offs have been observed in international agricultural scenario studies (Kanter et al., 2018; Paul et al., 2022; Sanou et al., 2023; Elia et al., 2025), where cereal expansion or livestock mitigation strategies deliver environmental benefits primarily when supported by efficiency gains, land-use substitution, and value-chain integration, rather than through single-lever interventions.

In New Zealand, several existing policy frameworks partially support the directions explored in these scenarios. The national Emissions Reduction Plan sets explicit methane and nitrous oxide reduction targets as part of the transition to net zero by 2050, including actions to support mitigation adoption in agriculture (Ministry for the Environment, 2022). Freshwater management instruments such as the National Policy Statement for Freshwater Management and the implementation of freshwater farm plans provide regulatory direction to manage water quality and nutrient losses from agricultural land use (Ministry for the Environment, 2025). Reviews of policy impacts further indicate that joint climate and freshwater frameworks influence land management decisions and related environmental outcomes, illustrating how regulatory drivers overlap with the trade-offs identified by the model (Djanibekov and Wiercinski, 2020). However, the scenarios also expose policy gaps, particularly in relation to food-security instruments for arable crops, investment support for processing infrastructure, and incentives for irrigation efficiency. Addressing these gaps through coordinated climate, water, and agri-food policies would enhance the feasibility and effectiveness of the pathways identified by the model, while recognising that transition costs and regional constraints remain important limitations (Zahedi et al., 2024; McElwee et al., 2024).