Abstract Finding environmentally conscious ways of storing energy is one of the largest challenges surrounding the regenerative energy movement. Sustainable approaches to this have many interesting parallels with biology—in particular the metabolism of carbon-based intermediates for energy transport and storage and synthesis of other materials. Photosynthesis, biological metabolism, and evolution present excellent models. Discussed are absolute requirements such as reduction in consumption and use; striving for true recyclability (no net harmful emissions of any kind from the human system); integration and economy of “metabolism,” that is cycling of energy and material; opportunism (making use of material and energy flows that would otherwise go to “waste,” and cause environmental damage); economy of scale and decentralized production in appropriate measures; diversity of technology; experimentation, close monitoring, and adaptation; preparedness to pay more for almost everything; and a new materialism.

Mixed enterprise farming systems that integrate more than one production system are important in agricultural production world-wide. Understanding and improving them can be made easier by modelling them with software tools. Modelling mixed enterprise farming systems can be a complex task as the interaction between the enterprises will introduce many dependencies. There are many software tools available that can model single enterprise systems, while there are few with the ability to model the biophysical systems in mixed farming. AusFarm has been designed and used to model mixed enterprise farming systems, integrating livestock, pasture, and crop models in one software tool and allowing flexible management of the whole farm. This paper demonstrates some key techniques that have been used for building and simulating mixed enterprise Australian farm systems in AusFarm. Examples of how to structure a cropping system and a livestock system are given. Key livestock and crop management tasks are implemented using flexible management rules.

Multi-model ensembles are becoming increasingly accepted for the estimation of agricultural carbon-nitrogen fluxes, productivity and sustainability. There is mounting evidence that with some site-specific observations available for model calibration (with vegetation data as a minimum requirement), median outputs assimilated from biogeochemical models (multi-model medians) provide more accurate simulations than individual models. Here, we evaluate potential deficiencies in how model ensembles represent (in relation to climatic factors) the processes underlying biogeochemical outputs in complex agricultural systems such as grassland and crop rotations including fallow periods. We do that by exploring the correlation of model residuals. We restricted the distinction between partial and full calibration to the two most relevant calibration stages, i.e. with plant data only (partial) and with a combination of plant, soil physical and biogeochemical data (full). It introduces and evaluates the trade-off between (1) what is practical to apply for model users and beneficiaries, and (2) what constitutes best modelling practice. The lower correlations obtained overall with fully calibrated models highlight the centrality of the full calibration scenario for identifying areas of model structures that require further development.

Context Growing of dual-purpose crops for grazing by livestock has increased in popularity in the high-rainfall zone of southern Australia, a livestock production zone traditionally based on permanent perennial grass species. Aims A systems experiment examined the impact on pasture forage availability, sheep grazing days and crop yields when one-third of a farmlet was sown to dual-purpose wheat (Triticum aestivum L.) and canola (Brassica napus L.) crops. Methods The experiment comprised nine experimental units (farmlets) divided into three treatments with three replicate farmlets per treatment: control farmlets sown to phalaris (Phalaris aquatica L.)-based pastures; and two treatments with grazing of crops prioritised for either ewes or their progeny. Control farmlets comprised four sub-paddocks (0.231 ha each) in 2013 and six sub-paddocks in 2014–2016. Farmlets in treatments that included dual-purpose crops comprised six sub-paddocks (0.231 ha), with two sub-paddocks sown to permanent pasture and the other four sub-paddocks supporting a pasture–pasture–canola–wheat rotation. Key results Crops were sown in February or early March and grazing commenced by mid-May in all years. Canola was grazed first in the sequence in 3 of 4 years. Treatments had similar total sheep grazing days per year, except for the progeny-prioritised treatment in 2014 when agistment wethers were introduced to utilise excess crop forage. Grazing did not affect wheat yields (3.9 vs 3.7 t/ha, P > 0.05) but did reduce canola yields (3.6 vs 3.0 t/ha, P = 0.007). Pasture availability (dry matter per ha in the pasture paddock at entry by sheep) was higher in the control during late summer and autumn when the crops were being established; however, resting of pastures during late autumn and winter while crops were grazed resulted in no difference in pasture availability among treatments during spring. Conclusion and implications The key feed-gap is in late summer and autumn when dual-purpose crops are included in the system. Early and timely sowing of crops increases the grazing opportunity from dual-purpose crops before lock-up. Growing wheat plus canola provided some hedge against poor establishment and/or slow growth rates in one of the crops.

Dual-purpose cropping (sowing crops with the intention of both grazing them during vegetative growth and harvesting grain thereafter) has become a widespread farming practice in southern Australia. This synopsis paper integrates research from a multi-institutional research project conducted at three nodes located near Hamilton (south-western Victoria), Wagga Wagga (southern NSW) and Canberra (ACT), and sets out 11 principles for the effective utilisation of dual-purpose crops in meat production systems to increase profit and manage risk. Dual-purpose crops can be used to overcome feed quality gaps in late summer–autumn or feed quantity gaps in late autumn/winter. They provide large quantities of high-quality forages for grazing in summer, autumn and winter and can provide a substantial contribution to the annual number of grazing days on a farm. Utilisation of the high-quality dry matter provided by dual-purpose crops is most effective when directed at young growing stock for sale or future reproduction rather than reproducing adult ewes. For example, sale weight of yearlings per ewe was increased by 16% in systems at the Canberra node when dual-purpose crops were prioritised for grazing by weaners. Wool production was also increased in systems that included grazing of dual-purpose crops. Grazing crops in winter does not necessarily reduce supplementary feeding costs for winter or spring lambing. Modelling suggests that inclusion of dual-purpose crops does not substantially change the optimum time of lambing for sheep meat systems. Financial analysis of the experimental data from the Canberra node showed that although cash expenses per hectare were increased in the crop-grazing systems, the overall profitability of those systems over the life of the experiment was greater by AU$207/ha.year than that of the pasture-only system. Factors driving improved profitability included income from grain, higher income from meat and wool, and lower supplementary feeding costs. However, increasing the area sown to crop from 10% to 30% of the farm area in this Southern Tablelands system appeared to increase risk. In south-western Victoria, spring-sown canola carried risk similar to or less than other options assessed to achieve ewe-lamb mating weight. It is likely that at least part of the reduction in risk occurs through the diversification in income from the canola produced as part of the system. It was concluded that the grazing of cereal and canola crops for livestock production can be profitable and assist in managing risk.

Context: Mixed crop-livestock farms are important production systems worldwide and dominate Australia's broadacre agricultural regions. While integration of crops and livestock can offer many benefits, these are often intertwined and are hard to quantify explicitly. Objective: This paper set out to examine specifically the financial risk and return implications from operating a farm portfolio involving segregated crop and livestock enterprises considering both production variability and commodity price variability. Methods: Crop and livestock production from representative systems were simulated over 40 years at six locations spanning Australia's crop-livestock zone using coupled biophysical production simulation models, APSIM for cropping enterprises and GRAZPLAN for livestock enterprises. Time series of varying prices and costs for the same period were derived using historical data. Annual gross margins for each enterprise and different proportional land allocations to the farm were calculated either allowing both production and price to vary or keeping either constant at average values. Results and conclusions: At all locations the livestock enterprise had less downside risk than the cropping enterprises (as measured by conditional value at risk). Across both enterprises, the impact of production variability was greater than price variability at 5 of the 6 locations. Annual gross margins from the modelled crop and livestock enterprises were not well correlated with each other. Hence, even in the absence of biophysical interactions, the risk-efficient frontier included mixtures of crops and livestock enterprises at most sites. At two sites, a mix of 20-40% crop resulted in the lowest downside risk, while at other sites there was a clear trade-off between maximising farm returns and minimising risk across a range of crop-livestock mixtures. Significance: This is the first study to explicitly quantify and show across a diversity of environments in Australia's mixed farming systems that operating a mixture of even segregated crop and livestock enterprises in a farming business can help farmers optimise their risk-return trade-off. Similar risk mitigation benefits may be achieved through crop-livestock systems in other agricultural regions exposed to high climate and price variability.

Context The use of dual-purpose crops (for grazing and grain) has increased in the high-rainfall zone in southern Australia. Aim A systems experiment examined the impact on livestock production and supplementary feeding when dual-purpose crops were incorporated into a production system based on Merino ewes producing yearling lambs for sale. Methods The experimental site near Canberra, ACT, was subdivided into nine experimental units (‘farmlets’) with three replicate farmlets for each of three production-system treatments. Each farmlet was managed as a self-contained unit with six Merino ewes and their progeny during 2013–16 (4 years). Ewes were joined in February, lambed in July and shorn in spring; the original cohort of ewes (born 2009) was replaced by a new cohort (born 2012) at the midpoint of the experiment. Six weaners were retained after weaning in each farmlet and sold as yearlings. Control farmlets were sown to pasture based on phalaris (Phalaris aquatica L.) and subterranean clover (Trifolium subterraneum L.) and comprised sub-paddocks to allow rotational grazing. Farmlets in treatments that included dual-purpose crops comprised six sub-paddocks (0.231 ha), with two sown to permanent pasture, and four supporting a rotation of pasture–pasture–dual-purpose canola (Brassica napus L.)–dual-purpose wheat (Triticum aestivum L.). In one of the crop–pasture production system treatments, crop-grazing was prioritised for ewes (ECG treatment); in the other, crop-grazing was prioritised for their progeny weaners (WCG treatment). Key results Greasy fleece weight from ECG (5.3 kg) and WCG (5.1 kg) ewes was higher (P < 0.001) than from control ewes (4.7 kg) averaged over the 4 years. The final sale weight of yearling weaners from the WCG system (44.3 kg) was higher (P < 0.001) than from the control (39.2 kg) or ECG (39.1 kg) systems when averaged over the 4 years. The benefit was predominantly due to greater weight gain during the period when weaners grazed the crop during late autumn and winter. Sale weight of lamb per hectare was higher (P = 0.003) in the WCG treatment (216 kg) compared with the ECG treatment (186 kg) when averaged over the 4 years of the experiment but did not differ (P > 0.05) to the control (201 kg). Meat production over the 4 years was higher (P < 0.001) in the WCG system (226 kg/ha) than other treatments when weight gain from wethers in 2014 was included. The impact of including dual-purpose crops on supplementary feeding was variable and depended on seasonal conditions. Conclusions Incorporation of dual-purpose crops into the high-rainfall production system can increase meat and wool production, with the highest meat production being obtained when crop grazing was prioritised for young carry-over livestock. Implications Prioritising dual-purpose crops for young growing livestock can increase meat production from the system while allowing other livestock classes (wethers or ewes) to graze the crops in better seasons when there was excess forage that would otherwise have been under-utilised.

Lucerne (Medicago sativa L.) is valued by producers with integrated crop-livestock systems. The multiple benefits of periods of lucerne leys to either livestock or to crop production have been widely reported; however, the importance of managing lucerne leys to whole farm profit and production has not and is best suited to a whole of system modelling study. This paper reports a simulation study aimed at better understanding the mixed farming systems that include short-term (3-year) phases of lucerne: specifically, the effects of terminating lucerne leys at different times prior to cropping. Simulations of mixed farming systems with the same soil type, crop rotation and proportional land use were conducted along a rainfall transect in a temperate environment in south-eastern Australia. Spring versus summer termination of the lucerne ley prior to cropping in autumn were compared. Although farming systems where lucerne was terminated in spring had higher crop production (mostly because of increased N at sowing) than those where lucerne was terminated in summer, the opposite was true for livestock production. Livestock production was higher in systems with summer termination mostly because of higher ewe condition scores at mating. When these sometimes positive and sometimes negative effects were evaluated at the whole of farm scale, in cases except the low rainfall site, allowing the lucerne ley to grow as late as possible prior to cropping was the most profitable management strategy in medium to high rainfall systems as it resulted in more lambs that were sold at heavier weights and the systems were more profitable, less costly, more efficient and less risky than those where leys were terminated in spring.

Croplands and grasslands are agricultural systems that contribute to land-atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE = -NEE/GPP) and C emission intensity (Int(C) = -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m(-2) yr(-1) (S5) while the observed mean was equal to 1763 m(-2) yr(-1) (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods).

Since about 2010 there has been an explosion in the interest and expectations for data-driven agriculture, often dubbed ‘digital agriculture‘. Digital agriculture is often used interchangeably with the term ‘smart farming’, which refers to the use of data to inform farm decisions and then automation and actuation to execute those decisions. Several technological drivers have converged to bring about this interest (Koch 2017):

Grazing land models can assess the provisioning and trade-offs among ecosystem services attributable to grazing management strategies. We reviewed 12 grazing land models used for evaluating forage and animal (meat and milk) production, soil C sequestration, greenhouse gas emission, and nitrogen leaching, under both current and projected climate conditions. Given the spatial and temporal variability that characterizes most rangelands and pastures in which animal, plant, and soil interact, none of the models currently have the capability to simulate a full suite of ecosystem services provided by grazing lands at different spatial scales and across multiple locations. A large number of model applications have focused on topics such as environmental impacts of grazing land management and sustainability of ecosystems. Additional model components are needed to address the spatial and temporal dynamics of animal foraging behavior and interactions with biophysical and ecological processes on grazing lands and their impacts on animal performance. In addition to identified knowledge gaps in simulating biophysical processes in grazing land ecosystems, our review suggests further improvements that could increase adoption of these models as decision support tools. Grazing land models need to increase user-friendliness by utilizing available big data to minimize model parameterization so that multiple models can be used to reduce simulation uncertainty. Efforts need to reduce inconsistencies among grazing land models in simulated ecosystem services and grazing management effects by carefully examining the underlying biophysical and ecological processes and their interactions in each model. Learning experiences among modelers, experimentalists, and stakeholders need to be strengthened by co-developing modeling objectives, approaches, and interpretation of simulation results.

Managed temperate grasslands occupy 25% of the world, which is 70% of global agricultural land. These lands are an important source of food for the global population. This review paper examines the impacts of climate change on managed temperate grasslands and grassland-based livestock and effectiveness of adaptation and mitigation options and their interactions. The paper clarifies that moderately elevated atmospheric CO2 (eCO(2)) enhances photosynthesis, however it may be restiricted by variations in rainfall and temperature, shifts in plant's growing seasons, and nutrient availability. Different responses of plant functional types and their photosynthetic pathways to the combined effects of climatic change may result in compositional changes in plant communities, while more research is required to clarify the specific responses. We have also considered how other interacting factors, such as a progressive nitrogen limitation (PNL) of soils under eCO(2), may affect interactions of the animal and the environment and the associated production. In addition to observed and modelled declines in grasslands productivity, changes in forage quality are expected. The health and productivity of grassland-based livestock are expected to decline through direct and indirect effects from climate change. Livestock enterprises are also significant cause of increased global greenhouse gas (GHG) emissions (about 14.5%), so climate risk-management is partly to develop and apply effective mitigation measures. Overall, our finding indicates complex impact that will vary by region, with more negative than positive impacts. This means that both wins and losses for grassland managers can be expected in different circumstances, thus the analysis of climate change impact required with potential adaptations and mitigation strategies to be developed at local and regional levels.

Maintaining the productive capacity of the agricultural soils of Australia's broadacre cropping zone requires careful management, given a highly variable climate and soils that are susceptible to degradation. Mixed crop livestock farming systems are the predominant land use across these regions and managers must operate farms for long-term sustainability as well as shorter-term profitability. Achieving profitable and sustainable businesses has required ongoing innovation and productivity gains, of which the integration of crop and livestock enterprises has been an important part. Production-soil erosion trade-offs associated with enterprise integration is critical information that has not been investigated to date at a whole-farm level. The objective of this study was to systematically evaluate management options developed in Grain and Graze (an integrated program of research, development and extension targeting mixed farms) to identify farm systems responses to soil erosion risks across seven regions spanning the mixed-farming area of Australia. To evaluate production-soil erosion trade-offs, we linked the APSIM soil water, soil nutrient cycling, annual crop and surface residue simulation models to the GRAZPLAN pasture and ruminant simulation models, using the AusFarm modelling software. Our results demonstrate that the management options tested in Grain and Graze support the principles of conservation agriculture and inform the sustainable intensification of mixed farming systems. Across the regions considered we found that: (1) Increasing pasture legume content and soil fertility can consistently benefit farm production and environmental indicators, (2) management interventions that target direct management of ground cover have the greatest potential to reduce soil erosion rates, (3) management during critical periods of naturally high soil erodibility and wind/water erosivity can substantially increase or decrease erosion risk; the timing of management interventions is therefore critical, and (4) grazing management to balance use of crop residues and pasture biomass is required to avoid developing hot spots of erosion and soil degradation.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations ( SD ) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield‐scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed.

Mathematical modelling is an essential component of understanding the challenge that climate change presents to livestock production systems. State-of-the-art climate change studies typically take a process-based approach that requires (i) selecting one or more modelled projections of future climate, (ii) downscaling these projections, (iii) simulating the agro-ecosystem (soils, plants and animals) under current and future climates and (iv) conducting an economic (and sometimes an environmental) analysis of the modelled outcomes. Within this long chain of models, relatively simple models of animal dynamics (from a nutritionist’s point of view) tend to be used in climate impact analyses; however using a livestock sub-model that is too simple can obscure the vitally important responses of livestock to variable forage supply and to climatic extremes.The analysis of climate change impacts and adaptation in livestock and integrated crop-livestock farming differs in important ways from similar analyses for cropping systems. Animal production systems typically rely on multiple land types and they have many more points of management intervention, increasing the complexity of the agro-ecosystem models that must be constructed. Livestock managers can adapt their management at two or more trophic levels, increasing the space of adaptations that needs to be evaluated. A rigid distinction between “impacts” and “adaptation” is hard to sustain; the human manager is more naturally viewed as a part of a livestock system.Filling 3 knowledge gaps in the modelling of livestock physiology would most advance our ability to assess climate change impacts and adaptation: a better quantification of the differences between animal breeds commonly used in OECD countries and those used in the rest of the world; better models for the behavioural determinants of daily forage intake, particularly under high temperatures; and connecting the cattle, sheep and goat genomes to their phenomes, to enable evaluation of breeding strategies under climate change.

Maintaining energy balance is necessary for longevity, and from this paradigm, Chaudhari and Kipreos develop their novel theory of ageing in this issue. 1 It's not such a coincidence that I find myself writing my next editorial essentially also on the disequilibrium between ATP and ADP – this time from the perspective of ageing. For here too, it is not so much the availability of ATP, per se, but rather the extent of the disequilibrium favouring ATP over ADP, that keeps life going. Seen in very crude terms, the smaller the disequilibrium, the “less life” is going on; and that is precisely what happens when organisms age. The evolution of the “order” of life (i.e. the characteristic formation of negentropy manifest in order that “preserves itself” against the inexorable universal flux of the Second Law) has a great deal in common with the preservation of order in extant living organisms. Or put another way, the mechanisms that originally created life (at least according to one theory) are the same as those that preserve it − both in general terms, and at the level of an individual organism. A decline in the mechanisms by which negentropy is maintained (according to the theory, the mechanisms that create and maintain disequilibria) is the thermodynamic way of saying “organisms age”. The massive disequilibrium between ATP and ADP is maintained in eukaryotic cells largely by the mitochondrion, and, as Chaudhari and Kipreos note, “the very long-lived insulin-pathway mutants have ATP levels that are over twofold higher than in wild-type animals.” Mitochondria are both “barometers” of aging, and − via declining efficiency − key “causative” agents. As organisms age, they invariably accumulate more damaged mitochondria, and the mechanisms of damage disposal (mitophagy in this case) are also compromised by the very process of aging of which the mitochondria are such a kay part. Mutants that − independently of the mitochondrion − can produce more ATP than wild type also tend to have longer lifespans (hence supporting the energy balance theory of aging); but, of course, the most practicable objects of study as far as humans are concerned are the mitochondrion and the control of energy metabolism through non-mutagenic routes! A key concept in the thesis of Chaudhari and Kipreos is that fused mitochondria have more efficient electron transport, and hence produce less ROS (reactive oxygen species, which damage life's fabric) than non-fused ones. At least in Drosophila, increased levels of elongated (fused) mitochondria are associated with increased longevity. In previous work, Chaudhari and Kipreos had shown that the transcription factor DAF-16 is necessary for the pathway that upregulates mitochondrial fusion protein expression; and DAF-16 is activated in response to decreased insulin signalling. Consistent with the strengthening paradigm that insulin signalling is an important determinant of lifespan, organisms that evidence increased lifespan under calorie restriction (mammals, worms, flies) display decreased insulin signalling. Observant readers might notice that Chaudhari and Kipreos1 do not discuss insulin sensitivity. In calorie-restricted animals, although insulin signalling decreases, insulin sensitivity increases − a feature long known to be associated with increased life-span. Hence not all of the insulin signalling pathway is downregulated: the distal targets are activated. To round off the “story”, so to speak, it's worth mentioning that all studies to date suggest that it is mitochondrial function that determines insulin sensitivity versus insulin resistance, and not that mitochondria themselves becomes more or less sensitive to the effects of insulin. So, increased mitochondrial fusion mediated by DAF-16 in response to lowered insulin signalling seems to be a hot contender for a novel paradigm in longevity research, not least because it also sits firmly within the disequilibrium paradigm used to explain life itself… Andrew Moore Editor-in-Chief

Soil organic carbon (SOC) in agricultural soils is vital for soil fertility for sustainable agricultural production and climate change resilience. Process-based farming system models are widely used to predict SOC dynamics in agricultural soils, but their application at regional scales is largely limited by computational requirements, data availability, and uncertainties in model predictions. Here we present an approach of combining a farming system model and a simplified surrogate model that emulates and mimics the behaviour of complex process-based models to predict SOC change (Delta SOC) and its uncertainty in Australian dryland cropping regions under anticipated climate change. We first calibrated and validated the farming system model APSIM for simulating Delta SOC (0-30 cm soil) using data from 90 farming-system trials at 28 sites across the study regions. Next we conducted a comprehensive simulation across the region using the validated APSIM model to predict Delta SOC over the period 2009-2070. Then simple surrogate models were developed based on the APSIM outputs. The surrogate models were able to explain > 96% of the variation in APSIM-predicted Delta SOC. Last the surrogate models were applied across the regions at the resolution of 1 km. In our simulations, Australian dryland cropping soils under farmers' common management practices and future climate conditions were a net carbon source (0.66 Mg C ha(-1) with the 95% confidence interval ranging from -5.79 to 8.38 Mg C ha(-1)) during the 62-year period. Across the regions, simulated Delta SOC exhibited great spatial variability ranging from -108.8 to 9.89 Mg C ha(-1) at the resolution of 1 km, showing significant (P < 0.05) negative correlation with baseline SOC level, temperature and rainfall, and positive correlation with pasture frequency (the duration of pasture in the rotation divided by the whole duration of the rotation) and nitrogen application rate. The uncertainty in Delta SOC and the underlying drivers were also assessed. This study presented a novel approach to efficiently predict future SOC dynamics and their uncertainty at fine resolutions, facilitating the development of site-specific management strategies for soil carbon sequestration.

Highly variable climates induce large variability in the supply of forage for livestock and so farmers must manage their livestock systems to reduce the risk of feed gaps (i.e. periods when livestock feed demand exceeds forage supply). However, mixed crop-livestock farmers can utilise a range of feed sources on their farms to help mitigate these risks. This paper reports on the development and application of a simple whole-farm feed-energy balance calculator which is used to evaluate the frequency and magnitude of feed gaps. The calculator matches long-term simulations of variation in forage and metabolisable energy supply from diverse sources against energy demand for different livestock enterprises. Scenarios of increasing the diversity of forage sources in livestock systems is investigated for six locations selected to span Australia's crop-livestock zone. We found that systems relying on only one feed source were prone to higher risk of feed gaps, and hence, would often have to reduce stocking rates to mitigate these risks or use supplementary feed. At all sites, by adding more feed sources to the farm feedbase the continuity of supply of both fresh and carry-over forage was improved, reducing the frequency and magnitude of feed deficits. However, there were diminishing returns from making the feedbase more complex, with combinations of two to three feed sources typically achieving the maximum benefits in terms of reducing the risk of feed gaps. Higher stocking rates could be maintained while limiting risk when combinations of other feed sources were introduced into the feedbase. For the same level of risk, a feedbase relying on a diversity of forage sources could support stocking rates 1.4 to 3 times higher than if they were using a single pasture source. This suggests that there is significant capacity to mitigate both risk of feed gaps at the same time as increasing 'safe' stocking rates through better integration of feed sources on mixed crop-livestock farms across diverse regions and climates.

Several models exist to predict lucerne (Medicago sativa L.) dry matter production; however, most do not adequately represent the ecophysiology of the species to predict daily growth rates across the range of environments in which it is grown. Since it was developed in the late 1990s, the GRAZPLAN pasture growth model has not been updated to reflect modern genotypes and has not been widely validated across the range of climates and farming systems in which lucerne is grown in modern times. Therefore, the capacity of GRAZPLAN to predict lucerne growth and development was assessed. This was done by re-estimating values for some key parameters based on information in the scientific literature. The improved GRAZPLAN model was also assessed for its capacity to reflect differences in the growth and physiology of lucerne genotypes with different winter activity. Modifications were made to GRAZPLAN to improve its capacity to reflect changes in phenology due to environmental triggers such as short photoperiods, declining low temperatures, defoliation and water stress. Changes were also made to the parameter governing the effect of vapour pressure on the biomass-transpiration ratio and therefore biomass accumulation. Other developments included the representation of root development and partitioning of canopy structure, notably the ratio leaf : stem dry matter. Data from replicated field experiments across Australia were identified for model validation. These data were broadly representative of the range of climate zones, soil types and farming systems in which lucerne is used for livestock grazing. Validation of predicted lucerne growth rates was comprehensive owing to plentiful data. Across a range of climate zones, soils and farming systems, there was an overall improvement in the capacity to simulate pasture dry matter production, with a reduction in the mean prediction error of 0.33 and the root-mean-square deviation of 9.6 kg/ha.day. Validation of other parts of the model was restricted because information relating to plant roots, soil water, plant morphology and phenology was limited. This study has highlighted the predictive power, versatility and robust nature of GRAZPLAN to predict the growth, development and nutritive value of perennial species such as lucerne.