Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates

Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3-11% historically to 10-20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler's experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in "trial-and-error" calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler's assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.

Modelling Waterlogging Impacts on Crop Growth: A Review of Aeration Stress Definition in Crop Models and Sensitivity Analysis of APSIM

Currently, crop physiological responses to waterlogging are considered only in a few crop models and in a limited way. Here, we examine the process bases of seven contemporary models developed to model crop growth in waterlogged conditions. The representation of plant recovery in these models is over-simplified, while plant adaptation or phenotypic plasticity due to waterlogging is often not considered. Aeration stress conceptualisation varies from the use of simple multipliers in equations describing transpiration and biomass to complex linkages of aeration-deficit factors with root growth, transpiration and nitrogen fixation. We recommend further studies investigating more holistic impacts and multiple stresses caused by plant behaviours driven by soils and climate. A sensitivity analysis using one model (a developer version of APSIM) with default parameters showed that waterlogging has the greatest impact on photosynthesis, followed by phenology and leaf expansion, suggesting a need for improved equations linking waterlogging to carbon assimilation. Future studies should compare the ability of multiple models to simulate real and in situ effects of waterlogging stress on crop growth using consistent experimental data for initialisation, calibration and validation. We conclude that future experimental and modelling studies must focus on improving the extent to which soil porosity, texture, organic carbon and nitrogen and plant-available water affect waterlogging stress, physiological plasticity and the ensuing temporal impacts on phenology, growth and yield.

Integrated Crop Management Practices Improve Grain Yield and Resource Use Efficiency of Super Hybrid Rice

Super hybrid rice genotypes have transformed the rate of genetic yield gain primarily due to intersubspecific heterosis, although the physiological basis underpinning this yield transformation has not been well quantified. We assessed the radiation use efficiency (RUE) and nitrogen use efficiency (NUE) of novel hybrid rice genotypes under four management practices representative of rice cropping systems in China. Y-liangyou 900 (YLY900), a new super hybrid rice widely adopted in China, was examined in field experiments conducted in Jingzhou and Suizhou, Hubei Province, China, from 2017 to 2020. Four management practices were conducted: nil fertilizer (CK), conventional farmer practice (FP), optimized cultivation with reduced nitrogen (OPT-N), and optimized cultivation with increased nitrogen (OPT+N). Yield differences across the treatment regimens were significant (p < 0.05). Grain yield of OPT+N in Jingzhou and Suizhou were 11 and 12 t ha-1, which was 14 and 27% greater than yields obtained under OPT-N and FP, respectively. Relative to OPT-N and FP, OPT+N had greater panicle numbers (9 and 18%), spikelets per panicle (7 and 12%), spikelets per unit area (17 and 32%), and total dry weight (9 and 19%). The average RUE of OPT+N was 2.7 g MJ-1, which was 5 and 9% greater than that of OPT-N and FP, respectively, due to higher intercepted photosynthetically active radiation (IPAR). The agronomic efficiency of applied N (AEN) of OPT+N was 17 kg grain kg-1 N, which was 9 and 68% higher than that of OPT-N and FP. These results show that close correlations exist between yield and both the panicles number (R 2 = 0.91) and spikelets per panicle (R 2 = 0.83) in OPT+N. We conclude that grain yields of OPT+N were associated with greater IPAR, RUE, and total dry matter. We suggest that integrated cropping systems management practices are conducive to higher grain yield and resource use efficiency through expansion of sink potential in super hybrid rice production.

How Does Crop Rotation Influence Soil Moisture, Mineral Nitrogen, and Nitrogen Use Efficiency?

Rice-wheat (RW) cropping systems are integral to global food security. Despite being practiced for decades, Chinese RW cropping systems often suffer from low productivity and poor nitrogen use efficiency (NUE), reflecting management approaches that are not well-contextualized to region and season. Here, we develop the best management guides for N fertilizer in RW systems that are designed to help raise the productivity, NUE, and environmental sustainability of winter wheat over the long term. 2-year field experiments were conducted with four N fertilizer rates (0, 135, 180, and 225 kg N ha-1), allowing contrasts of yields, soil moisture, and NUE of wheat in RW in the humid climates zones on the Jianghan Plain. We compared RW systems with soybean/maize dryland wheat (DW) systems that are similarly endemic to China: after soybean/maize is harvested, soils are often drier compared with moisture content following rice harvest. With high seasonal N application rates (180-225 kg N ha-1), wheat crop yields increased by 24% in RW which were greater than comparable yields of wheat in DW, mainly due to greater kernels per spike in the former. Across treatments and years, N accumulation in plant tissue and kernel dry matter of DW was higher than that in RW, although mean agronomic efficiency of nitrogen (AEN) and physiological efficiency of nitrogen (PEN) of RW systems were greater. As N application rates increased from 135 to 225 kg ha-1, AEN and PEN of DW decreased but changed little for RW. Soil ammonium N was much lower than that of nitrate N; changes in NH4 + and NO3 - as a consequence of increasing N fertilization were similar for RW and DW. We recommend that tactical application of N fertilizer continue seasonally until midgrain filling for both the DW and RW systems. At fertilization rates above 180 kg N ha-1, yield responses disappeared but nitrate leaching increased significantly, suggesting declining environmental sustainability above this N ceiling threshold. Collectively, this study elicits many functional and agronomic trade-offs between yields, NUE, and environmental sustainability as a function of N fertilization. Our results show that yield and NUE responses measured as part of crop rotations are both more robust and more variable when derived over multiple seasons, management conditions, and sites.

Crop traits enabling yield gains under more frequent extreme climatic events

Climate change (CC) in central China will change seasonal patterns of agricultural production through increasingly frequent extreme climatic events (ECEs). Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of ECEs on crop productivity. To reveal crop traits conducive to long-term yield improvement in the target population of environments, we created 8,192 virtual genotypes with contrasting but realistic ranges of phenology, productivity and waterlogging tolerance. Using these virtual genotypes, we conducted a genotype (G) by environment (E) by management (M) factorial analysis (G×E×M) using locations distributed across the entire cereal cropping zone in mid-China. The G×E×M invoked locally-specific sowing dates under future climates that were premised on shared socioeconomic pathways SSP5-8.5, with a time horizon centred on 2080. Across the simulated adaptation landscape, productivity was primarily driven by yield components and phenology (average grain yield increase of 6-69% across sites with optimal combinations of these traits). When incident solar radiation was not limiting carbon assimilation, ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation, crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1,010 kg ha^-1. Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.

iTRAQ Proteomic Analysis of Wheat (Triticum aestivum L.) Genotypes Differing in Waterlogging Tolerance

Transient and chronic waterlogging constrains crop production in many regions of the world. Here, we invoke a novel iTRAQ-based proteomic strategy to elicit protein synthesis and regulation responses to waterlogging in tolerant (XM 55) and sensitive genotypes (YM 158). Of the 7,710 proteins identified, 16 were distinct between the two genotypes under waterlogging, partially defining a proteomic basis for waterlogging tolerance (and sensitivity). We found that 11 proteins were up-regulated and 5 proteins were down-regulated; the former included an Fe-S cluster assembly factor, heat shock cognate 70, GTP-binding protein SAR1A-like and CBS domain-containing protein. Down-regulated proteins contained photosystem II reaction center protein H, carotenoid 9, 10 (9', 10')-cleavage dioxygenase-like, psbP-like protein 1 and mitochondrial ATPase inhibitor. We showed that nine proteins responded to waterlogging with non-cultivar specificity: these included 3-isopropylmalate dehydratase large subunit, solanesyl-diphosphate synthase 2, DEAD-box ATP-dependent RNA helicase 3, and 3 predicted or uncharacterized proteins. Sixteen of the 28 selected proteins showed consistent expression patterns between mRNA and protein levels. We conclude that waterlogging stress may redirect protein synthesis, reduce chlorophyll synthesis and enzyme abundance involved in photorespiration, thus influencing synthesis of other metabolic enzymes. Collectively, these factors accelerate the accumulation of harmful metabolites in leaves in waterlogging-susceptible genotypes. The differentially expressed proteins enumerated here could be used as biological markers for enhancing waterlogging tolerance as part of future crop breeding programs.

Negative relationship between dry matter intake and the temperature-humidity index with increasing heat stress in cattle: a global meta-analysis

Changes in frequency and severity of heat waves due to climate change pose a considerable challenge to livestock production systems. Although it is well known that heat stress reduces feed intake in cattle, effects of heat stress vary between animal genotypes and climatic conditions and are context specific. To derive a generic global prediction that accounts for the effects of heat stress across genotypes, management and environments, we conducted a systematic literature review and a meta-analysis to assess the relationship between dry matter intake (DMI) and the temperature-humidity index (THI), two reliable variables for the measurement of feed intake and heat stress in cattle, respectively. We analysed this relationship accounting for covariation in countries, breeds, lactation stage and parity, as well as the efficacy of various physical cooling interventions. Our findings show a significant negative correlation (r =  - 0.82) between THI and DMI, with DMI reduced by 0.45 kg/day for every unit increase in THI. Although differences in the DMI-THI relationship between lactating and non-lactating cows were not significant, effects of THI on DMI varied between lactation stages. Physical cooling interventions (e.g. provision of animal shade or shelter) significantly alleviated heat stress and became increasingly important after THI 68, suggesting that this THI value could be viewed as a threshold for which cooling should be provided. Passive cooling (shading) was more effective at alleviating heat stress compared with active cooling interventions (sprinklers). Our results provide a high-level global equation for THI-DMI across studies, allowing next-users to predict effects of heat stress across environments and animal genotypes.

Carbon myopia: The urgent need for integrated social, economic and environmental action in the livestock sector

Livestock have long been integral to food production systems, often not by choice but by need. While our knowledge of livestock greenhouse gas (GHG) emissions mitigation has evolved, the prevailing focus has been-somewhat myopically-on technology applications associated with mitigation. Here, we (1) examine the global distribution of livestock GHG emissions, (2) explore social, economic and environmental co-benefits and trade-offs associated with mitigation interventions and (3) critique approaches for quantifying GHG emissions. This review uncovered many insights. First, while GHG emissions from ruminant livestock are greatest in low- and middle-income countries (LMIC; globally, 66% of emissions are produced by Latin America and the Caribbean, East and southeast Asia and south Asia), the majority of mitigation strategies are designed for developed countries. This serious concern is heightened by the fact that 80% of growth in global meat production over the next decade will occur in LMIC. Second, few studies concurrently assess social, economic and environmental aspects of mitigation. Of the 54 interventions reviewed, only 16 had triple-bottom line benefit with medium-high mitigation potential. Third, while efforts designed to stimulate the adoption of strategies allowing both emissions reduction (ER) and carbon sequestration (CS) would achieve the greatest net emissions mitigation, CS measures have greater potential mitigation and co-benefits. The scientific community must shift attention away from the prevailing myopic lens on carbon, towards more holistic, systems-based, multi-metric approaches that carefully consider the raison d'être for livestock systems. Consequential life cycle assessments and systems-aligned 'socio-economic planetary boundaries' offer useful starting points that may uncover leverage points and cross-scale emergent properties. The derivation of harmonized, globally reconciled sustainability metrics requires iterative dialogue between stakeholders at all levels. Greater emphasis on the simultaneous characterization of multiple sustainability dimensions would help avoid situations where progress made in one area causes maladaptive outcomes in other areas.

Can seasonal soil N mineralisation trends be leveraged to enhance pasture growth?

BACKGROUND

Soil N mineralisation is the process by which organic N is converted into plant-available forms, while soil N immobilisation is the transformation of inorganic soil N into organic matter and microbial biomass, thereafter becoming bio-unavailable to plants. Mechanistic models can be used to explore the contribution of mineralised or immobilised N to pasture growth through simulation of plant, soil and environment interactions driven by management.

PURPOSE

Our objectives were (1) to compare the performance of three agro-ecosystems models (APSIM, DayCent and DairyMod) in simulating soil N, pasture biomass and soil water using the same experimental data in three diverse environments (2), to determine if tactical application of N fertiliser in different seasons could be used to leverage seasonal trends in N mineralisation to influence pasture growth and (3), to explore the sensitivity of N mineralisation to changes in N fertilisation, cutting frequency and irrigation rate.

KEY RESULTS

Despite considerable variation in model sophistication, no model consistently outperformed the other models with respect to simulation of soil N, shoot biomass or soil water. Differences in the accuracy of simulated soil NH₄ and NO₃ were greater between sites than between models and overall, all models simulated cumulative N₂O well. While tactical N application had immediate effects on NO₃, NH₄, N mineralisation and pasture growth, no long-term relationship between mineralisation and pasture growth could be discerned. It was also shown that N mineralisation of DayCent was more sensitive to N fertiliser and cutting frequency compared with the other models.

MAJOR CONCLUSIONS

Our results suggest that while superfluous N fertilisation generally stimulates immobilisation and a pulse of N₂O emissions, subsequent effects through N mineralisation/immobilisation effects on pasture growth are variable. We suggest that further controlled environment soil incubation research may help separate successive and overlapping cycles of mineralisation and immobilisation that make it difficult to diagnose long-term implications for (and associations with) pasture growth.

An Integrated Economic, Environmental and Social Approach to Agricultural Land-Use Planning

Agricultural land-use change is a dynamic process that varies as a function of social, economic and environmental factors spanning from the local to the global scale. The cumulative regional impacts of these factors on land use adoption decisions by farmers are neither well accounted for nor reflected in agricultural land use planning. We present an innovative spatially explicit agent-based modelling approach (Crop GIS-ABM) that accounts for factors involved in farmer decision making on new irrigation adoption to enable land-use predictions and exploration. The model was designed using a participatory approach, capturing stakeholder insights in a conceptual model of farmer decisions. We demonstrate a case study of the factors influencing the uptake of new irrigation infrastructure and land use in Tasmania, Australia. The model demonstrates how irrigated land-use expansion promotes the diffusion of alternative crops in the region, as well as how coupled social, biophysical and environmental conditions play an important role in crop selection. Our study shows that agricultural land use reflected the evolution of multiple simultaneous interacting biophysical and socio-economic drivers, including soil and climate type, crop and commodity prices, and the accumulated effects of interactive decisions of farmers.

Influence of climate variability and stocking strategies on greenhouse gas emissions (GHGE), production and profit of a northern Queensland beef cattle herd

Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

A review of whole farm-system analysis in evaluating greenhouse-gas mitigation strategies from livestock production systems

Recognition is increasingly given to the need of improving agricultural production and efficiency to meet growing global food demand, while minimising environmental impacts. Livestock forms an important component of global food production and is a significant contributor to anthropogenic greenhouse-gas (GHG) emissions. As such, livestock production systems (LPS) are coming under increasing pressure to lower their emissions. In developed countries, LPS have been gradually reducing their emissions per unit of product (emissions intensity; EI) over time through improvements in production efficiency. However, the global challenge of reducing net emissions (NE) from livestock requires that the rate of decline in EI surpasses the productivity increases required to satisfy global food demand. Mechanistic and dynamic whole farm-system models can be used to estimate farm-gate GHG emissions and to quantify the likely changes in farm NE, EI, farm productivity and farm profitability as a result of applying various mitigation strategies. Such models are also used to understand the complex interactions at the farm-system level and to account for how component mitigation strategies perform within the complexity of these interactions, which is often overlooked when GHG mitigation research is performed only at the component level. The results of such analyses can be used in extension activities and to encourage adoption, increase awareness and in assisting policy makers. The present paper reviews how whole farm-system modelling has been used to assess GHG mitigation strategies, and the importance of understanding metrics and allocation approaches when assessing GHG emissions from LPS.

Adoptability and effectiveness of livestock emission reduction techniques in Australia’s temperate high-rainfall zone

Significant research has been conducted on greenhouse gas emissions mitigation techniques for ruminant livestock farming, however putting these techniques into practice on-farm requires consideration of adoptability by livestock producers. We modelled the adoptability of a range of livestock greenhouse gas abatement techniques using data from farm case studies and industry surveys, then compared the effectiveness of several techniques in reducing emissions intensity and net farm emissions. The influence of the Australian Government Emissions Reduction Fund on adoptability was included by modelling techniques with and without the requirements of an Australian Government Emissions Reduction Fund project. Modelled adoption results were compared with data obtained from surveys of livestock farmers in northern Tasmania, Australia. Maximum adoption levels of the greenhouse gas mitigation techniques ranged from 34% to 95% and the time required to reach 90% of the peak adoption levels ranged from 3.9 to 14.9 years. Techniques with the lowest adoption levels included providing supplements to optimise rumen energy : protein ratio and feeding high-lipid diets. Techniques with the highest adoptability involved improved ewe reproductive efficiency, with more fertile flocks having higher adoption rates. Increasing liveweight gain of young stock so animals reached slaughter liveweight 5–7 weeks earlier (early finishing) and joining maiden ewes at 8 months instead of 18 months had the fastest adoption rates. Techniques which increased net emissions and reduced emissions per liveweight sold (emissions intensity) had higher adoptability due to profit advantages associated with greater meat and wool production, whereas some techniques that reduced both net emissions and emissions intensity had lower adoptability and/or longer delays before peak adoption because of complexity and costs associated with implementation, or lack of extension information. Techniques that included an Australian Government Emissions Reduction Fund project had reduced maximum adoption levels and reduced rate of adoption due to difficulty of implementation and higher cost. Adopting pastures with condensed tannins reduced net emissions, emissions intensity and had high adoption potential, but had a long delay before peak adoption levels were attained, suggesting the technique may be worthy of increased development and extension investment. These results will be of benefit to livestock farmers, policymakers and extension practitioners. Programs designed to mitigate livestock greenhouse gas should consider potential adoption rates by agricultural producers and time of implementation before embarking on new research themes.

Modelled greenhouse gas emissions from beef cattle grazing irrigated leucaena in northern Australia

Agriculture produces an estimated 14.5% of global anthropogenic greenhouse gases, with livestock emissions being the largest source of enteric methane. Reducing greenhouse gas (GHG) emissions from production and processing of beef cattle will become increasingly important with time, particularly in line with global efforts to mitigate rising GHG emissions. The present study compared several GHG emission scenarios from beef cattle grazing on irrigated Leucaena leucocephala (Lam.) de Wit cv. Cunningham (leucaena) in Queensland, Australia. Animals began grazing the leucaena paddocks when they were 16 months old and continued until ~240 days, before being sold to market. Three scenarios were modelled with cattle grazing leucaena and the resulting GHG emissions calculated, representing (1) the current leucaena paddock (current leucaena scenario), (2) clearing native vegetation and extending the leucaena paddock (extended leucaena scenario) and (3) extending the leucaena paddock onto previously cleared paddocks (alternative leucaena scenario). These were compared with a pre-scenario baseline, where the steers grazed on native vegetation until the time of sale. Herd GHG emission intensities (EI) were reduced in comparison with the baseline (EI of 8.4 tCO2-e/t liveweight sold) for all the leucaena scenarios, where reductions were modelled for the current, extended and alternative leucaena scenarios, which had an EI of 3.9, 3.7 and 3.6 tCO2-e/ t liveweight sold, respectively. Reductions were attributed to the higher growth rates of the steers on leucaena and the anti-methanogenic potential of leucaena. Where leucaena was planted on previously cleared paddocks, carbon stocks (t C/ha) nearly doubled a decade following planting, with most carbon sequestered in the soil. However, total carbon stocks on the property reduced over the modelled period (112 years), where native vegetation, e.g. eucalyptus woodland, was cleared for leucaena planting, but soil carbon yield increased. The combined sequestration of leucaena and the reduction of GHG emission intensities resulted in overall net reductions of GHG emissions for the three leucaena scenarios compared with the baseline. These results demonstrated that the use of leucaena for grazing can be an effective means for farmers to reduce the GHG emissions and increase productivity of their herds. The study also demonstrated that it would take 9 years of reduced emissions to compensate for the carbon lost as emissions from clearing the eucalyptus woodland, suggesting that farmers should use other methods of intensifying production from existing leucaena paddocks if their sole purpose is short-term emissions abatement.

Modelling enteric methane abatement from earlier mating of dairy heifers in subtropical Australia by improving diet quality

Milking cows typically dominate dairy farm greenhouse gas (GHG) emissions, but replacement heifers also contribute to farm emissions and can increase the emission intensity of milk production. In northern Australia, heifers generally graze poorer-quality subtropical pastures and in the absence of energy-dense supplementary feed during periods of low pasture growth, liveweight (LW) gain can be restricted. This modelling study examined the time required and enteric methane (CH4) emissions produced in raising dairy heifers to a target LW for first mating by feeding a diet assuming either constant (static) or variable (dynamic) nutritive values. Using a static approach (Australian Feeding Standards methodology), and assuming a target mating LW of 360 kg, growing heifers reached their target LW at ~18 months of age while consuming C4 grasses with a constant metabolisable energy content of 9.5 MJ/kg dry matter (DM) or 11 months of age on a diet of 11.0 MJ/kg DM. Enteric CH4 emissions were 1.2 and 0.8 t of carbon dioxide equivalents/heifer over the 18- and 11-month periods, respectively. To explore the extent with which climatic conditions influence seasonal pasture availability and nutritive value with a dynamic approach, we used a whole-farm biophysical model (SGS pasture model) to simulate diets with mean metabolisable energy values of 9.5 and 10.9 MJ/ kg DM. On average (±s.d.), heifers required 22 ± 4 and 17 ± 1 months, respectively, to reach target LW, with cumulative enteric CH4 emissions of 1.22 ± 0.20 and 0.72 ± 0.04 t carbon dioxide equivalents, respectively. The dynamic approach resulted in slower LW gain due to the variable nutritive value of the diet throughout the year, resulting in seasonal periods of LW plateauing or decline. Maintaining heifers on high-quality diets in subtropical northern Australia should result in increased daily LW gain, lower enteric CH4 emissions to mating LW and earlier calving. Together, these factors reduce their lifetime emission intensity of milk production.