Enteric methane (CH4) emissions from ruminant livestock are a major source of greenhouse gases in northern Australian grazing systems, where the extensive, low-input nature of production limits the applicability of alternative mitigation strategies such as feed additives. Tropical forage legumes therefore represent one of the few practical abatement options available, offering mitigation through both direct suppression of rumen methanogenesis and indirect improvements in animal productivity. This review synthesises evidence from in vitro, in vivo and farm-scale studies and integrates these findings with production-system modelling and agronomic assessments to evaluate CH4 abatement potential under extensive grazing conditions. In vitro studies demonstrated an average 12.1% reduction in CH4 yield across tropical legume species, while in vivo studies reported a comparable mean reduction of 13.8%. Legume inclusion rate (% of dietary dry matter) emerged as the primary predictor of CH4 response. Production-system modelling across low-, medium- and high-productivity grazing systems showed that legume incorporation reduced emissions intensity by an average of 28%, with approximately 82% of the reduction attributable to productivity gains and 18% to direct suppression of enteric CH4. A multi-criteria prioritisation framework combining CH4 abatement potential with agronomic suitability identified a small number of high-potential species. Leucaena leucocephala consistently produced the greatest direct CH4 suppression, whereas Desmanthus and Stylosanthes spp. offered broader environmental adaptation and greater scalability despite more modest direct abatement. These findings suggest that effective CH4 mitigation in northern Australian grazing systems will require a portfolio of legumes tailored to regional conditions. Tropical legumes are an immediately deployable mitigation strategy, although their full potential will depend on overcoming constraints to establishment, persistence and adoption in commercial grazing systems.

Understanding nutrient fluxes across ecosystems is critical for sustainable land management, climate adaptation, and food security. However, current ecosystem models face challenges in integration, data consistency, and scalability across spatial and temporal domains. This review outlines the rationale and design principles for a unified modelling framework to support integrated nutrient budgeting. We identify key barriers—including model coupling, semantic alignment, data harmonization, and temporal-spatial scaling—and discuss opportunities to overcome them through modular design, interdisciplinary collaboration, and open-source platforms. Building on these insights, we propose the rationale and design principles for a unified, scale-aware modeling framework that supports flexible coupling among vegetation, soil, and hydrological components while explicitly accounting for uncertainty and data limitations. The framework emphasizes transparent variable semantics, scale-aware information exchange, and the integration of observational constraints from monitoring networks and remote sensing products. By balancing process complexity with operational usability, it addresses the needs of both researchers and decisionmakers, enabling more robust, transparent, and interoperable approaches to terrestrial nutrient budgeting across scales. This work establishes a foundation for advancing integrated, user-oriented nutrient modeling capable of supporting scientific inquiry, land management, and policy development under global environmental change.

Matching nitrogen (N) supply with available soil water is a major challenge in dryland conservation cropping systems, where rainfall infiltration and soil hydraulic conductivity control the depth and availability of surface-applied fertilizer N. However, the extent to which fallow rainfall can redistribute surface-applied fertilizer N into deeper soil layers under residue-retained dryland systems, and how this process is influenced by residue retention and subsoil hydraulic continuity, remain poorly understood. This study examined how residue addition, subsoil hydraulic conductivity and fertilizer application timing regulate the redistribution and fate of surface-applied N during fallow and its recovery by a subsequent wheat crop. A controlled lysimeter experiment using 15N-labelled urea evaluated residue management (residue vs. no-residue), subsoil hydraulic conductivity (unrestricted vs. restricted), and fertilizer application timing (early, mid, and late fallow) under simulated fallow rainfall. Fertilizer-N movement followed rainfall infiltration through mass flow, but residue addition and subsoil hydraulic discontinuity modified its depth and retention. Residue enhanced profile water storage by reducing evaporative loss yet promoted near-surface fertilizer-N retention and delayed losses, while the hydraulically restricted profile limited infiltration depth. Mid-fallow application maintained recovery comparable to early application while producing relatively low apparent loss, reflecting a favourable balance between N mobility and retention. Under early-fallow application, 19–46% of applied fertilizer N was redistributed below 20 cm by the end of fallow, with crop recovery comparable to mid-fallow under similar residue and hydraulic conditions. In contrast, late application after simulated fallow rainfall ceased resulted in minimal redistribution, the lowest crop recovery (<5%) and the highest apparent N loss (35–39%). The findings indicate that treating fertilizer application timing as a hydrological rather than calendar decision can improve fertilizer N recovery and reduce loss risk in dryland conservation agriculture.

According to current global trends, there is little prospect of achieving either the IPCC’s target reduction of carbon emissions needed to hold temperature increases to both 1.5 and 2.0 degrees or the UN’s Sustainable Development Goal’s target of preserving 30

Simulation models are an important tool to predict how farming practices influence utilisation and loss of nitrogen (N). However, many simulation exercises lack sufficient validation of N dynamics from both soil and fertiliser sources and rely on single or a few measurable N pools, potentially shifting bias from one pool to another. This study evaluated the capacity of Agricultural Production Systems sIMulator (APSIM) to simulate N fertiliser budgets in dryland sorghum and wheat systems of eastern Australia using an extensive 15N dataset from 18 field trials with up to four N rates. Key metrics included 15N fertiliser recoveries at harvest in soil and plant, and 15N fertiliser losses. Fertiliser N in APSIM was calculated as the balance between simulated N in the non-fertilised control and the respective applied N rate, and compared to relevant 15N data. APSIM’s performance for fertiliser N budget simulation was tested with (i) conventional calibration fitting plant N uptake and (ii) improved calibration including the denitrification and mineralisation parameters to fit fertiliser N loss. Simulations with conventional calibration showed good agreement with phenology, soil water and plant N uptake data but largely underestimated the measured fertiliser N loss (RMSE: 23 kg N ha−1, PBIAS: − 75

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks of carbon markets, but their application suffers from model-specific differences that keep any one model from working well across all combinations of soils, climates, crops, and agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management and climate impact on crop productivity, provide an opportunity to better estimate changes in soil organic carbon (SOC) outcomes for agronomic practices that have the potential to mitigate SOC loss at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4-km2 to assess the aggregate ability of different regenerative practices to sequester SOC at this scale compared to their dynamic baselines. MME was validated with long-term experimental data and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 +/- 0.12 Mg ha-1 yr-1 aggregated across the entire U.S. Midwest cropland. At the regional scale, this corresponds to a net SOC gain of 16.4 Tg C yr-1 compared to business-as-usual baselines. These benefits are approximately halved when each management change is practiced individually, and the modest gains are only fully realized when continued over the long-term in soils with low initial carbon stock. Results demonstrate the power of MMEs run at high resolution for providing robust estimates of environmental outcomes following agricultural practice change, and for pinpointing locations for most effective intervention. This approach can alleviate many producer carbon market participation barriers and help address market issues while ultimately supporting large-scale regenerative agriculture initiatives. ### Competing Interest Statement Bruno Basso is a cofounder of CIBO Technologies. Keith Paustian and Yao Zhang have financial interest in Indigo Ag. The other coauthors declare no conflict of interest.

Intensively managed pasture systems receive large inputs of nitrogen (N) in the form of fertiliser and through the deposition of ruminant urine, creating hot-spots for denitrification which results in variable amounts of nitrous oxide (N2O) and dinitrogen (N2) emitted. Here we investigated the potential of increased irrigation frequency to reduce N2O and N2 emissions from an intensively managed pasture in the subtropics after ruminant urine deposition. Irrigation volumes were estimated to replace evapotranspiration and were applied either once (Low-Frequency) or split into four applications (High-Frequency). This irrigation schedule was applied 3 times over the 60 day monitoring period, and fluxes of N2O and N2 were measured using the 15N gas flux method. In line with farming practice, simulated urine patches (equivalent of 80 g N m-2 applied) were also fertilised three times with 2 g urea N m-2 to show the combined effects of urinary and fertiliser N on N2O and N2 emissions. Highest N2O emissions of up to 60 mg N2O-N m-2 day-1 were observed briefly after urine deposition, decreasing thereafter, resulting in cumulative N2O losses of 169.9 mg N2O-N m-2 from the Low-Frequency treatment. Denitrification was dominated by N2, accounting for more than 89% of N2O+N2 emitted. Irrigation treatments had no effect on cumulative N2 losses of more than 2700 mg N2-N m-2. However, High frequency irrigation reduced cumulative N2O losses by 35%. Our findings suggest that under conditions of high N availability, increased irrigation frequency can reduce the environmental impact (N2O) of denitrification, but not overall N losses via this pathway. The response of N2O emissions may further indicate that less frequent, but more intense rainfall events will shift the product ratio of denitrification towards N2O, increasing environmentally harmful N losses from intensively managed pasture systems.

Soil organic carbon (SOC) plays an important role in sequestering CO2 and assists in reducing atmospheric greenhouse gases in addition plays a critical role in maintaining the sustainability of grasslands. The valuable roles of SOC, make its accurate measurement critical however temporal changes in SOC are small and spatially vary. Therefore, a large number of samples are required to detect the SOC changes which makes it a complex and costly task. Stratification is capable of improving the efficiency of sampling by reducing the number of samples and increasing the accuracy of SOC measurement. Stratification relies on assessing the relationship between SOC and environmental factors. Vegetation has the potential to be used as a proxy to spatially predict SOC.This experiment aimed to assess the relationship between SOC and vegetation characteristics as a key factor in small areas with uniform climate and soil type. The three study sites were located in southern Queensland with subtropical climate. Short-term data was collected using the BOTANAL method and biomass harvesting over two years period in different seasons which included biomass, pasture composition, and vegetation type. Long-term data was extracted from various satellite images for up to 30 years which indicate the long-term effect of vegetation on SOC. Remote sensing data contained vegetation and soil indices.The kriging method was applied to both soil and vegetation data to interpolate unsampled points for the study areas, then K-means clustering was used to cluster the data. Spearman rank-order correlation coefficient was used to assess the correlation between SOC clusters and vegetation factor clusters.While some of the vegetation parameters have a significant correlation with SOC, the correlation is not consistent between different sites and different seasons. It can be concluded from this study that vegetation factors are not capable of using landscape clustering for SOC sampling on small scale.

Soil carbon (C) sequestration by restoring degraded grasslands with adequate management practices offers significant opportunities for climate change mitigation while remaining highly uncertain. In this study, a combination of a biogeochemical model DayCent-CABBI and eddy covariance (EC) flux towers was applied to evaluate soil C sequestration potential (at a depth of 0-0.3 m) of management strategies in subtropical grasslands. DayCent-CABBI was calibrated for grasslands in northeast Australia using biomass and soil organic carbon (SOC) data from a long-term trial and then fine-tuned using EC flux tower data from seven sites in the region. The model was then validated with cumulative net ecosystem exchange, biomass, and SOC, resulting in root mean square errors of 1.16, 0.88, and 2.81 Mg C ha-1, respectively. The model was used to project long-term changes in SOC stocks under innovative management practices (time-controlled grazing and pasture legume incorporation), estimating soil C sequestration by 0.37-0.48 and 0.15-0.26 Mg C ha-1 year-1 toward 2050 with the respective practices. This study confirms the validity of the Measure, Model, and Verification (MMV) approach to estimate and project soil C sequestration for evaluating SOC methodologies by grassland management within a shorter period than soil sampling-measuring the baseline SOC, modeling the C dynamics with the calibrated DayCent-CABBI, and verifying the projected soil C sequestration with EC flux tower data.

Voluntary carbon offset markets play an important role in climate change mitigation by deploying technologies in order of lowest abatement cost. The objective of this study is to identify the key drivers of changes in the volume of carbon credits issued in voluntary registry offset markets from 2006 to 2020 using a decomposition analysis framework. The results show that the volume of issued carbon credits related to forestry and land use increased from 2006 to 2015 due to priority increases and scale expansions in REDD+ projects. In addition, the reasons for the priority changes in carbon credits issued varied according to the scale of carbon offset programs in each region. The comparison of scale effect and carbon offset program priority is a useful tool for understanding changes in carbon credits issued according to project technology and region. The very rapid increase in forestry carbon credits issued does however pose important policy implications given it has been accompanied by widespread indications of poor governance and questionable outcomes in terms of CO2 reduction. In light of the IPCC's reliance on carbon credits the need for thoroughgoing policy reform is underlined.

Aims The aim of this study was to determine the effectiveness of natural (NatZeo) and acid-treated (AcidZeo) zeolites in increasing the nitrogen (N) recovery of sugarcane grown under conditions highly conducive for N losses. Methods This glasshouse trial replicated the pedoclimatic conditions typical of the Australian sugarcane industry in the Wet Tropics to evaluate the capacity and economic feasibility of using NatZeo and AcidZeo to reduce leaching and increase plant and soil N recovery in a highly permeable sandy-loam soil. Nitrogen fertiliser was applied at two rates (84 and 120 kg N ha(-1)) as N-15-enriched urea. Results Compared with the unamended treatments, AcidZeo led to significantly higher average fertiliser N recoveries in both the soil (+24%) and plant (+54%), which resulted in significantly lower overall N losses (-22%). However, the significantly higher capacity of AcidZeo in retaining ions limited the availability of potassium and sulphur to the plants and led to a 4% yield reduction. The use of NatZeo led to lower abatements of N losses (-6%) but increased N recoveries in the plant (+22%). NatZeo did not result in as much cation immobilisation, which, combined with the increased plant/soil N recovery, resulted in the highest yield of the trial (+8% compared with the unamended treatments). The economic analysis indicated that only NatZeo could potentially increase farmer's income when applied in 20 cm wide strips around the fertiliser band. Conclusions This study highlights that zeolites have potential to improve the environmental sustainability and profitability of sugarcane cropping systems.

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Context Agricultural soils are a major source of emissions of the greenhouse gas nitrous oxide (N2O). Aim Quantify direct N2O emissions from Australian agricultural production systems receiving nitrogen (N) inputs from synthetic and organic fertilisers, crop residues, urine and dung. Method A meta-analysis of N2O emissions from Australian agriculture (2003–2021) identified 394 valid emission factors (EFs), including 102 EFs with enhanced efficiency fertilisers (EEFs). Key results The average EF from all N sources (excluding EEFs) was 0.57%. Industry-based EFs for synthetic N fertiliser (excluding EEFs) ranged from 0.17% (non-irrigated pasture) to 1.77% (sugar cane), with an average Australia-wide EF of 0.70%. Emission factors were independent of topsoil organic carbon content, bulk density and pH. The revised EF for the non-irrigated cropping (grains) industry is now 0.41%; however, geographically-defined EFs are recommended. Urea was the most common N source with an average EF of 0.72% compared to urine (0.20%), dung (0.06%) and organo-mineral mixtures (0.26%). The EF for synthetic N fertilisers in rainfed environments increased by 0.16% for every 100 mm over 300 mm mean annual rainfall. For each additional 50 kg N ha−1 of synthetic fertiliser, EFs increased by 0.13%, 0.31% and 0.38% for the horticulture, irrigated and high rainfall non-irrigated cropping industries, respectively. The use of 3,4 dimethylpyrazole-phosphate (DMPP) produced significant reductions in EFs of 55%, 80% and 84% for the horticulture, non-irrigated and irrigated cropping industries, respectively. Conclusions and implications Incorporation of the revised EFs into the 2020 National Greenhouse Accounts (NGA) produced a 12% increase in direct N2O emissions from the application of synthetic N fertilisers. The lack of country-specific crop residue decomposition data is a major deficiency in the NGA.

Denitrification is a key process in the global nitrogen (N) cycle, causing nitrous oxide (N2O) and dinitrogen (N-2) emissions. Biogeochemical models allow field-scale estimates of N2O and N-2, extrapolating important yet often limited experimental results. However, such predictions rely mostly on N2O data, and the lack of N-2 data hinders validating total denitrification, which remain a major uncertainty for N budgets. This study investigated denitrification losses and N budgets in two tropical sugarcane systems using the Agricultural Production Systems sIMulator (APSIM) and the LandscapeDNDC (LDNDC) simulation framework using a unique dataset of both N2O and N-2 emissions measured in the field over a complete growing season. Key soil N parameters influencing N2O and N-2 emissions in APSIM and LDNDC were identified via global sensitivity analysis, followed by generalised likelihood uncertainty estimation to determine their posterior distributions using (i) N2O data only and (ii) both N2O and N-2 data. The simulation of N2O emissions in APSIM and LDNDC were improved in both calibration approaches, resulting in 0.7-1.3 kg N ha(-1) of RMSE. However, simulated N-2 emissions increased and agreed better with the observed values only when calibrated with both N2O and N-2 (RMSE 30.1-45.0 kg N ha(-1) before calibration and 19.3-19.9 kg N ha(-1) after). The simulated N loss pathway shifted from leaching to N-2 emissions after calibration including N-2. The simulated N balance was larger when sugarcane residues were retained as compared to burning consistently across the different soil N parameter configurations. These findings indicate that biogeochemical models, when used with default soil N parameters or calibration limited to N2O data, are likely to underestimate denitrification losses (>50 %), leading to a bias in N budgets simulation. Accurate N loss estimates are essential for understanding the long-term management impacts on soil organic matter dynamics, as demonstrated by the improved N budgets from both simulation models denote N mining when sugarcane is burnt, and the potential to sequester N when cane residues are retained. These outcomes emphasise the importance of integrating in-situ measurements of N2O and N-2 in simulation exercises, ensuring more accurate N budget estimates across scales.

In 2023, the Australian Government issued similar to 250,000 soil carbon credits following a measurement period characterised by high rainfall (Decile 10). The inferred soil organic carbon (SOC) sequestration rates during this period, ranging from similar to 2 to 8 t C ha-(1) yr-(1), significantly exceed rates reported in Australian scientific studies (similar to 0.1 to 1.2 t C ha-(1) yr-(1)). Our analysis, incorporating SOC and biomass measurements alongside remote sensing of NDVI, reveals that these SOC gains were largely attributable to above-average rainfall rather than project interventions. Moreover, these gains were not sustained when rainfall returned to average levels, raising concerns about the durability of credited sequestration and its additionality beyond natural climatic variability. Our findings demonstrate that current safeguards within the Soil Carbon Method-such as withholding 25% of credits during the first measurement period-are likely insufficient to account for climatic variability. To strengthen the integrity of the carbon crediting system, we recommend extending the minimum measurement period for credit issuance to at least five years. Additionally, governments should establish science-based 'reasonable bounds' for expected long-term SOC gains from management practices to sense-check reported outcomes. These measures will ensure that credited SOC sequestration is more closely tied to management-driven outcomes rather than short-term climate-driven fluctuations.

Grasslands store approximately one-third of the global terrestrial carbon (C) stocks. However, intensified grassland management over the last decades has resulted in soil degradation and subsequent soil organic C (SOC) losses as well as enhanced greenhouse gas emissions. Restoring grassland soils with adequate management practices offers huge opportunities for climate change mitigation with the potential to globally sequester ~150 megatons of CO2 eq per year in the soil. Emerging C credit markets further stress the importance of effective grassland management practices to restore SOC stocks. Despite that several improved management practices have been tested, their efficacy on soil C sequestration largely varies depending on environmental conditions. Soil C sequestration potential of grassland management practices under climate change scenarios is therefore highly uncertain. To this end, biogeochemical models, such as DayCent, offer a powerful tool to investigate the efficacy of grassland management practices, simulating the complex interaction between management and environmental conditions. Furthermore, Eddy Covariance (EC) flux towers provide opportunities to calibrate and validate the model’s C cycling with its high-frequency C balance measurements accounting for high spatial heterogeneity in pasture systems. In this study, DayCent was calibrated for pasture systems in the Brigalow belt region in Australia using EC flux tower data. The model was then validated with SOC data and used to project SOC stocks under combinations of different management practices and climate change scenarios. The calibrated parameters on soil organic matter decomposition reflected the deeper soil depth boundary down to 30 cm and the higher ratio of mineral-associated organic matter observed in Australian pasture systems. The calibrated DayCent model showed the potential to sequester C for the long term under climate change scenarios by introducing deep rooting legume and time-controlled grazing, restoring the degraded pasture soils due to historic intensive management. These simulated C sequestration estimates strongly correlated with C inputs and thus were limited by rather rainfall, grass productivity or grazing management than clay content. This study suggests Measure, Model and Verify (MMV) approach to estimate and project soil C sequestration for evaluation of SOC methodologies by pasture management within a shorter period than soil sampling – measure the baseline SOC, model the C dynamics with the calibrated DayCent and verify the projected soil C sequestration with EC flux tower data.

Acid-sulphate sugarcane soils in the subtropics are known hot-spots for nitrous oxide (N 2 O) emissions, yet the reduction of reactive N 2 O to non-reactive dinitrogen (N 2 ) via specific pathways remains a major uncertainty for nitrogen (N) cycling and loss from these soils. This study investigated the magnitude and the N 2 O:N 2 partitioning of N 2 O and N 2 losses from a subtropical acid-sulphate soil under sugarcane production using the 15 N gas flux method, establishing the contribution of hybrid (co- and chemo-denitrification) and heterotrophic denitrification to N 2 O and N 2 losses. Soils were fertilised with potassium nitrate, equivalent to 25 and 50 kg N ha −1 , watered close to saturation then incubated over 30 days. An innovative, fully automated incubation system coupled to an isotope-ratio mass-spectrometer enabled real time analysis of 15 N 2 O and 15 N 2 at sub-diel resolution. Peak losses of N 2 O and N 2 reached 6.5 kg N ha −1 day −1 , totalling > 50 kg of N 2 O+N 2 -N ha −1 . Emissions were dominated by N 2 , accounting for more than 57% of N 2 O+N 2 losses, demonstrating that the reduction of N 2 O to N 2 proceeded even under highly acidic conditions. Over 40% of N 2 O, but only 2% of N 2 emissions, were produced via hybrid pathways. These findings demonstrate hybrid pathways are generally limited to N 2 O production, likely driven by high organic matter content and low soil pH, promoting both biotic, and abiotic nitrosation. Regardless of the underlying process, the magnitude of the N 2 O emissions demonstrates the environmental, but also the potential agronomic significance, of hybrid pathways of N 2 O formation for N loss from fertilised acid-sulphate soils.

The livestock industry accounts for a considerable proportion of agricultural greenhouse gas emissions, and in response, the Australian red meat industry has committed to an aspirational target of net-zero emissions by 2030. Increasing soil carbon storage in grazing lands has been identified as one method to help achieve this, while also potentially improving production and provision of other ecosystem services. This review examined the effects of grazing management on soil carbon and factors that drive soil carbon sequestration in Australia. A systematic literature search and meta-analysis was used to compare effects of stocking intensity (stocking rate or utilisation) and stocking method (i.e, continuous, rotational or seasonal grazing systems) on soil organic carbon, pasture herbage mass, plant growth and ground cover. Impacts on below ground biomass, soil nitrogen and soil structure are also discussed. Overall, no significant impact of stocking intensity or method on soil carbon sequestration in Australia was found, although lower stocking intensity and incorporating periods of rest into grazing systems (rotational grazing) had positive effects on herbage mass and ground cover compared with higher stocking intensity or continuous grazing. Minimal impact of grazing management on pasture growth rate and below-ground biomass has been reported in Australia. However, these factors improved with grazing intensity or rotational grazing in some circumstances. While there is a lack of evidence in Australia that grazing management directly increases soil carbon, this meta-analysis indicated that grazing management practices have potential to benefit the drivers of soil carbon sequestration by increasing above and below-ground plant production, maintaining a higher residual biomass, and promoting productive perennial pasture species. Specific recommendations for future research and management are provided in the paper.

Purpose The reduction of the greenhouse gas nitrous oxide (N 2 O) to dinitrogen (N 2 ) via denitrification and N 2 O source partitioning between nitrification and denitrification remain major uncertainties in sugarcane systems. We therefore investigated magnitude and product stoichiometry of denitrification and production pathways of N 2 O from a tropical sugarcane soil in response to increasing soil nitrate (NO 3 − ) availability. Methods Microcosms were established using a tropical sugarcane soil (Qld, Australia) and emissions of N 2 O and N 2 were measured following fertilisation with 15 NO 3 − –N equivalent to 25, 50 and 100 μg N g −1 soil, simulating soil NO 3 − contents previously observed in situ, and mimicking flood irrigation by wetting the soil close to saturation. Results Cumulative N 2 O emissions increased exponentially with NO 3 − availability, while cumulative N 2 emissions followed an exponential increase to maximum. Average daily N 2 emissions exceeded 5 µg N 2 –N g soil −1 and accounted for > 99% of denitrification. The response of N 2 O suggests preferential NO 3 − reduction with increasing NO 3 − availability, increasing N 2 O even when NO 3 − levels had only a diminishing effect on the overall denitrification rate. The fraction of N 2 O emitted from denitrification increased with NO 3 − availability, and was a function of soil water, NO 3 − and heterotrophic soil respiration. Conclusions Our findings show the exponential increase of N 2 O driven by excess NO 3 − , even though the complete reduction to N 2 dominated denitrification. The low N 2 O/(N 2 O + N 2 ) product ratio questions the use of N 2 O as proxy for overall denitrification rates, highlighting the need for in-situ N 2 measurements to account for denitrification losses from sugarcane systems.

CONTEXT: Cotton is an economically important crop in Australia that requires high resource application, particularly that of nitrogen (N) fertilizers. Determining optimal N fertilizer rates that reach both economic and environmental objectives is a key challenge in cotton systems because of the inherent within-field variability and relatively low N fertilizer use efficiency (NFUE).OBJECTIVE: This study aimed to model optimal N fertilizer rates by accounting for within-field variability through management zone (MZ) delineation across a cotton field in Queensland, Australia. METHODS: MZs were delineated using satellite-derived normalized difference vegetation index (NDVI) and the crop simulation model, Decision Support System for Agrotechnology Transfer (DSSAT), was automatically calibrated with a grid-search optimization algorithm and validated across two cotton seasons. A total of 336 different N fertilizer scenarios were subsequently evaluated at pre-planting and top-dressing to observe the effect on profit margin and NFUE. RESULTS AND CONCLUSIONS: The MZ delineation analysis determined that within-field variability could be best represented by two MZs, one of which displaying subsoil constraints due to high carbonate concentrations. The use of the auto-calibration algorithm led to a successful validation of the model with a Wilmott d-index of agreement ranging between 0.75 (soil nitrate) and 0.96 (aboveground biomass and plant N), respectively. The subsequent N scenario simulations indicated that by reducing N fertilizer rates by 80 and 30 kg N ha-1 across the two MZs, respectively, compared to the current industry average, profits could be maximized through maintaining yields while reducing N inputs.SIGNIFICANCE: Overall, these results demonstrate the potential of combining remote sensing-derived MZs and crop model auto-calibration techniques to support the cotton industry in achieving improved resource efficiency and profit margins.