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This paper presents a comprehensive substance flow analysis (SFA) of phosphorus (P) for a six-year period (2008–13) in Gippsland, a key agricultural region of Australia with high economic and environmental significance. The analysis has revealed that around 71% (10,904 t) of the mean annual total inflow of P was stored in this region. This finding is different from other published regional scale SFAs, where more than 50% of the P in annual total inflow eventually left the region. Per capita P inflow in Gippsland is also found substantially higher compared to available SFAs. In Gippsland, the annual inflow of P primarily occurred as commercial fertilizer (66% or 10,263 t) and livestock feed (29% or 4443 t), and the outflow mainly occurred as livestock products (94% or 4181 t); while the majority (66% or 7218 t) of the P storage occurred in soils of the livestock farming area. A comparative analysis of the magnitude of P flow in different subsystems indicates that more than 80% of the annual total inflow, outflow, and storage of P in this region is associated with the livestock (mainly dairy and meat cattle) farming subsystem. For the Gippsland region as a whole and almost all subsystems, significant annual variations in the magnitudes of P inflow, outflow, storage and internal flow have been observed. Between 2008 and 2013, both the annual total inflow (mainly as commercial fertilizer) and the annual total storage (mainly in soils) of P in this region showed a substantial decrease (41% and 54% of the 2008 level, respectively), while the annual total outflow (mainly as livestock and crop products) remained nearly the same, indicating an improvement towards sustainable P management. Despite such a positive sign, there is still adequate room for improvement. This analysis indicates that over the study period, about 65,424 t P were accumulated (mainly as soil storage) that is approximately six times the mean annual P inflow as commercial fertilizer in this region; while approximately 3241 t P lost as soil erosion and runoff, indicating substantial adverse economic and environmental implications. Based on the findings of the current analysis, this paper outlines a wide range of policy and management interventions to reduce the downstream loss of P and other nutrients as well as the region's dependency on imported commercial fertilizers and grain based feed. This paper also presents new criteria for data quality analysis and a set of P concentration data of various materials that could be readily utilized in future SFAs of P at any geographical scale. This paper suggests that considering the inter-annual variations in P flow as assessed in this SFA, future research should focus on identifying the influence of socio-environmental, technological and political factors on the magnitude P flow in Gippsland. [ABSTRACT FROM AUTHOR]

Annual forecasts for the Australian macadamia crop have been issued since 2001, with varying (and not always improving) degrees of accuracy. Regression models using climate variables have formed the basis for these forecasts, with general linear model (GLM) ensembles being adopted more recently. This has proven to be a challenging task, as there are only a small number of observations (18) combined with a large number (90+) of independent variables – these being different climate measures for different times of the year (representing 'key physiological periods for macadamia trees'). Also, these 'assumedly-independent' variables contain various degrees of correlation. This study uses cross-validation, with the most recent data for the two dominant production regions of Australia (Lismore and Bundaberg), to investigate the relative performance of alternate modelling methods. These modelling methods were GLMs, partial least squares (PLS) regression and LASSO (least absolute shrinkage and selection operator) penalised regression. Model ensembles, which have been shown to be beneficial in many alternate disciplines, are used to advantage. Both GLMs and PLS produced quite-disappointing results, failing to meet the project's benchmarked accuracy of ±10% error. The optimal LASSO models performed notably better, with a further improvement when ensembles were incorporated. The lowest mean absolute error (MAE) rates here were 9.0% for Lismore and 5.9% for Bundaberg. Hence LASSO ensembles will be adopted for future forecasts of the Australian macadamia crop. • Since 2001 crop forecasts have been provided for the Australian industry to facilitate macadamia operations. • This paper reviews this process, and conducts a cross-validation comparison of some of the more modern regression methods. • These are also incorporated in with the new ensemble modelling methods, also known as 'wisdom of the crowds'. • Results from the ensemble LASSO penalised regressions show a marked improvement over the previous methods. • This method is now being adopted for the 2019 macadamia crop forecast. [ABSTRACT FROM AUTHOR]

Abstract: Driven principally by government regulation and societal expectations, mining companies around the world are seeking to mitigate the environmental impacts of mining through mined land rehabilitation programs. The ultimate goal of rehabilitation is to establish an acceptable and sustainable post-mining land use. Mining companies worldwide face the challenge of specifying just what a sustainable post-mining land use will be. The problem is that while regulations require mining companies to assess post-mining land use sustainability, the mechanism for doing so and the factors that should be considered are not specified. We propose a risk-based approach to post-mining land use assessment with the aim of reducing the uncertainty of mine closure and the potential cost of repair of land degradation caused by inappropriate post-mining land use. Grazing is a commonly suggested post-mining land use, particularly in Australia where most mining activities occur on land previously used for cattle grazing. Grazing is also seen as a use suited to rehabilitated mined land because of the lower land productivity required compared to cropping. In this paper we develop a conceptual model of the factors influencing the land degradation risk posed by grazing on rehabilitated mined land. This was done through a literature review to identify potentially important risk factors, followed by a survey of graziers surrounding six open cut mines within the Bowen Basin Region of Queensland, Australia. The survey results were used to develop a profile of the risk factors likely to influence the land management behaviour of graziers within the Bowen Basin. The results of the research highlight that there are three main sets of factors that affect grazing risk on rehabilitated mined land. These are site biophysical characteristics that influence land productivity and commercial grazing viability, factors that influence the land management style of a grazier (principally stocking rate decisions), and factors that influence the commitment of a grazier to comply with any caveats placed on the management of the land. The profile of risk factors obtained for Bowen Basin graziers showed that grazing is likely to be a low risk post-mining land use where land productivity is high enough to support commercial cattle grazing and where land is managed by local graziers. Both the conceptual model and the profile of risk factors described in this paper are precursors to the development of a predictive risk assessment model. [Copyright &y& Elsevier]

Abstract: The worldwide need to improve water use efficiency within irrigated agriculture has been recognised in response to environmental concerns and conflicts in resource use. Within the Australian cotton industry, the imperative to reduce water use and optimise irrigation management through the understanding of risk, using information generated by computerised decision aids was identified and subsequently developed into the HydroLOGIC irrigation management software. This paper summarises the attributes of the HydroLOGIC irrigation management software, with particular emphasis on functionality and its application to irrigation decisions within the Australian cotton industry. The software development process is documented to provide direction for future software application initiatives, with particular emphasis on a process of user feedback, evaluation and support requirements providing direction to software development. On-farm experiments throughout the development period allowed the validation of internal software logic, irrigator decision processes, and the OZCOT cotton growth model. The software demonstrated the ability to improve yield and water use efficiency by optimising strategic and tactical irrigation decisions in the Australian furrow irrigation cotton production system. In 7 of the 11 on-farm experiments conducted, the use of HydroLOGIC helped improve overall field water use efficiency by optimising the timing of irrigation events or by indicating further irrigations would not provide yield or maturity benefits. The paper also presents useful insights into the development of software targeted for irrigation utilising in-field measurements of soil water, crop growth and a crop growth simulation model. [Copyright &y& Elsevier]

Public and private research institutions are grappling with the challenges and opportunities of embedding dimensions of responsible innovation within their research and development programs, including those seeking to transform agricultural productivity and sustainability through digital technologies. Central to meeting this challenge is building institutional, organisational and professional capacity for anticipation and reflexiveness within multidisciplinary research communities. Foresighting methodologies provide a means by which this might be usefully and practically enabled, whilst also shedding light on the broader social and ethical implications of alternative agricultural technology development pathways under uncertain environmental and industry futures. This paper presents the results of a participatory foresighting exercise undertaken as part of a large, publicly funded multi-disciplinary research initiative designed to build a common big data infrastructure to harness the benefits of the digital revolution for the Australian agricultural and land sectors. We seek to explore what role digital technology will play in the future of Australian agriculture and to consider the social and ethical implications. We ran a one-day foresighting workshop comprised of four steps – 1) horizon scanning to identify trends 2) selecting two drivers of change 3) producing a matrix to generate scenarios 4) building and refining scenarios. Participants explored different possible futures of farming in Australia, with a focus on scenarios involving socio-technical dimensions of digital agriculture to consider the implications of these futures for research practice and for farming communities. Four scenarios were developed, distinguished by the interplay of two critical but uncertain drivers of change identified by participants, namely: the degree of resource security or insecurity that future agricultural enterprises are likely to experience; and the degree to which farming sectors maintain traditional farm business models and associated value chains or transition to more diverse or innovative business models. The process highlighted the need to increase the capacity and opportunity for more reflexivity in research and development, if positive outcomes were to be achieved. The scenarios we produced provide a catalyst for conversation about the implications of digital technology development in Australia and globally, for industry, policy and research and development. In particular, the scenarios highlight potential changes in farm business models, decision making, and beneficiaries and inequities of new technologies and other components of food value chains. The paper also serves as a guide and prompt for others, by demonstrating one way reflexivity can be achieved in organisations attempting innovation. [Display omitted] • We present findings from a workshop to develop four scenarios of digital agriculture futures in Australia. • The aim of the workshop was to identify trends about digital technologies for different forms of agriculture in Australia. • A crucial issue for digital technology is avoiding unintended adverse effects but foresight and reflexivity can help. • Our contribution is outlining a possible method to improve responsible digital innovation through foresighting. • We aim to start the conversation with researchers, industry and policy about achieving responsible digital innovation. [ABSTRACT FROM AUTHOR]

Over the past three decades major changes have occurred in Australia's beef industry, affecting productivity and potentially the amount of resources used and environmental impacts from production. Using a life cycle assessment (LCA) approach with a 'cradle-to-farm gate' boundary the changes in greenhouse gas (GHG) emission intensity and key resource use efficiency factors (water use, fossil fuel energy demand and land occupation) are reported for the 30 years from 1981 to 2010, for the Australian beef industry. The analysis showed that over the three decades since 1981 there has been a decrease in GHG emission intensity (excluding land use change emissions) of 14% from 15.3 to 13.1 kg CO2-e/kg liveweight (LW). The improvement was largely due to efficiency gains through heavier slaughter weights, increases in growth rates in grass-fed cattle, improved survival rates and greater numbers of cattle being finished on grain. However, the increase in supplement and grain use on farms, and the increase in feedlot finishing, resulted in a twofold increase in fossil fuel energy demand for beef production over the same time. Fresh water consumption for beef production dropped to almost a third from 1465 L/kg LW in 1981 to 515 L/kg LW in 2010. Three contributing factors for this dramatic reduction in water use were: (i)an increase in the competitive demand for irrigation water, resulting in a transfer away from pasture for cattle to higher value industries such as horticulture, (ii) an initiative to cap free flowing artesian bores in the rangelands, and (iii) an overall decline in water available for agriculture compared to industrial and domestic uses. While there was higher uncertainty relating to estimates of land occupation and emissions from land use (LU) and direct land use change (dLUC), an inventory of land occupation indicated a decline in non-arable land occupation of about 19%, but a sevenfold increase in land occupation for feed production, albeit from a low base in 1981. GHG emissions associated with LU and dLUC for grazing were estimated to have declined by around 42% since 1981, due largely to legislated restrictions on broad-scale deforestation which were introduced progressively between 1996 and 2006. This paper discusses the prospects and challenges for further gains in resource use efficiency and reductions in greenhouse gas intensity for Australian beef production. [ABSTRACT FROM AUTHOR]

The question addressed in this paper is whether the agronomic efficiency of cropping sequences can be improved in the northern grain zone of Australia. Analysis of whole systems over multiple seasons is particularly important in cropping regions such as Australia's northern grain zone, where farmers have the option of growing a variety of winter and summer crops and where fallowing is required to store water to safeguard yields of following crops. The study is based on a detailed longitudinal survey of the inputs and yields of 94 farmers' fields over 7 seasons. The Agricultural Production Systems Simulator (APSIM) was used to benchmark the 94 cropping sequences and to determine if the productivity of these cropping sequences can be improved through changed management, particularly of nitrogen nutrition and timely sowing of individual crops. Comparison of surveyed and simulated yields were then used to determine the yield gap that can be explained by factors unaccounted for in APSIM, i.e. biotic stresses such as weeds, pests and diseases or inadequate operational management. Using a generalised N response curve, data from the simulation analysis were plotted relative to a normalised input-output relationship to determine their position relative to an efficiency frontier representing the simulated production function. This analysis was conducted separately for both individual crops and for whole sequences in individual fields. The analysis of 193 individual crops showed that the average yield of 1.90t/ha was 65% of the simulated water and nitrogen-limited yield potential of 2.92t/ha. Investigation of nitrogen unlimited and early sowing management options revealed that there was relatively little yield advantage (0.15t/ha) to be gained from these management improvements. The remaining gap between observed yields and what the simulations suggest may be attributed to factors such as weeds, pests and diseases, sub-optimal operations or extreme weather events. Three production criteria were used to compare cropping sequences: (1) dollar income, (2) metabolisable energy yield, and (3) crude protein yields. While the income from 36% of the individual crops in the study was found to be more than 80% of their production frontier values, only 29% of whole cropping sequences achieved this benchmark. Similar results were achieved when crops and crop sequences were evaluated in terms of their metabolisable energy and crude protein yields. It is concluded that in order to increase the agronomic efficiency of cropping in Australia's northern grain zone, attention should be focussed on the intensity and configuration of cropping sequences and on the management of fallows in addition to the management of individual crops. [ABSTRACT FROM AUTHOR]

Digitalization and the use of Smart Farming Technologies are considered a major opportunity for the future of agriculture. However, realisation of full benefits is constrained by: (1) farmers' interest in and use of big data to improve farm decision making; (2) issues of data sovereignty and trust between providers and users of data and technology; (3) institutional arrangements associated with the governance of data platforms. This paper examines the case of Australia's dairy herd milk recording system, arguably one of agriculture's first cases of 'big data' use, which collects, analyses and uses farm-level data (milk production, lactation and breeding records) to provide individual cow and herd performance information, used by individual farmers for farm management decisions. The aim of this study was to 1) examine the use of big data to add value to farm decision making; and 2) explore factors and processes, including institutional arrangements, which influence farmer engagement with and use of big data. This paper traces the Australian history of the organisation of dairy herd recording (established in 1912 and digitalized in late 1970s) and then uses findings from a longitudinal study of 7 case study dairy farms, which were incentivised to become involved in herd recording in 2015. Applying a conceptual framework linking path dependency in farm decision making and collaborative governance capacity, we find three new important dimensions of the farm user context influencing farmer demand for big data applications: 1) the transition to a new business stage; 2) the additionality farmers seek from data generated in one component of the farm system to other subsystems, and 3) the use of data in long term or strategic decision making. Further, we identified critical attributes of support services in addressing digital literacy, capacity and capability issues at farm level, including diversity in data presentation formats and facilitation of the on-farm transition process through intermediary herd test organisations. The role of farmers as governance actors, or citizens in the decisions of the trajectory of big data applications, adds to understanding of the nature of collaborative governance arrangements that support farm engagement. • Farmer interest in data relates to business stage and the decision's importance. • Cooperative governance structures facilitate farmer trust and use of big data. • Support services reduce the impact of low digital literacy, capacity and capability. • Inter-dependence occurs between existing data processes and optimising data use. [ABSTRACT FROM AUTHOR]

The nutritive value of annual pasture legumes changes with phenology during each season, with a progressive decrease in feeding value as plants accumulate structural carbohydrates and nutrients are diluted. However, these changes differ widely among annual legume species, affecting the pattern of nutrient availability and production in a grazing enterprise. This paper set out to examine the implications of differences in the nutritive value of annual pasture legumes in relation to their economic value for mixed farming systems of southern Australia. Calibrated GrassGro™ plant models with data generated from field experiments to represent Dry Matter Digestibility (DMD) profiles of six annual legume species; Medicago truncatula Gaertn. (barrel medic), B. pelecinus L. (biserrula), Trifolium spumosum L. (bladder clover), Ornithopus sativus Brot. (French serradella), Medicago littoralis Rhode ex Loisel. (strand medic) and Trifolium subterraneum L. (subterranean clover). The plant models were used in a modelling study to support a self-replacing Merino sheep enterprise, which was simulated at seven locations across southern Australia, where annual pasture species are heavily relied on for livestock production. Modelled values of DMD of green material, averaged across all phenological stages, ranged from approximately 62% (French serradella) to 73% (bladder clover), with little variation due to location. Pastures with higher nutritive value had a reduced requirement for supplementary feeding of sheep. Variation in nutritive value had a greater effect on supplementary feeding costs and gross margins than differences in biomass production among the annual legume species. Differences in the levels of supplementary feeding required in systems with the different legumes was most pronounced during the period from May to July (late autumn to winter). For sheep enterprises compared at the same stocking rate, the total supplementary feed required was 18% lower with bladder clover pastures, and 9% lower in subterranean clover pastures, compared with an average of the remaining four pasture species. This is the first study to compare the effects of variation in nutritive value among the annual pasture legumes developed for the soils and climatic conditions of southern Australia. Our results demonstrated that the magnitude of differences in nutritive value among annual pasture legumes are economically important and that the establishment of higher nutritive value legumes will reduce supplementary feeding costs in extensive grazing systems, in some cases even where their biomass production is lower. [Display omitted] • The nutritive value of annual pasture legumes varies widely among species and varieties. • We calibrated Dry Matter Digestibility in six annual legume models to represent their year-round nutritive value. • Mean Dry Matter Digestibility of pastures ranged from 62% to 73% over the year among the six species modelled. • The supplementary feeding cost in a sheep enterprise decreased by up to 20% when higher quality legumes species were grown. • Differences in nutritive value among pasture legumes are important in extensive livestock production. [ABSTRACT FROM AUTHOR]

Abstract: The intensity of milk production from pasture based dairy farming systems is often related to nitrogen (N) losses. This paper investigates dairy farming systems in the Scotts Creek catchment, an intensive farming region in south-eastern Australia, to assess aspects of productive potential and environmental footprint as a result of nutrient loss. A detailed survey of farming systems was coupled with regional data and a dairy farming systems simulation model (DairyMod) to better understand the N flows in farming systems over a range of different input and production intensities. Simulations of representative farming systems – farming system typologies – were run for 100years to provide information on the consistency and proportion of N loss in various pathways over a range of different weather and soil moisture conditions. The typologies covered a very wide range in intensity of stocking rate, inputs (e.g. concentrates, fertiliser). In general N transformations, plant and animal production and the efficiency of conversion of N into animal and plant products were related to the level of N inputs of the farming systems and milk production, or intensity. The long-term average total predicted N loss (via leaching, denitrification and volatilisation) ranged from 24(±6) to 227(±73)kgN/ha/yr and increased relative to the intensity of milk production (L/ha). Over the long term, annual average N losses by leaching ranged from 4 to 143kgN/ha/yr, volatilisation from 17 to 66kgN/ha/yr and denitrification from 2 to 18kgN/ha/yr. In an average system there were similar amounts of N exported from the farming system by leaching (44% of total N), as lost through volatilisation (47%), whereas losses by denitrification were comparatively minor (9%). The inputs were principally related to a potential milk production capacity of the farming system which was not wholly related to stocking rate. The efficiency of N utilisation for milk synthesis (L milk/kgN-consumed) increased with system intensity, however the relative loss (gN loss/kg milk N) also increased. With the current farming system typologies, improvements in animal efficiency due to intensification appear to be offset by the capacity of the system to retain surplus N. In order to meet regional production targets, there are various potential ways to further intensify the current farming systems. However the implications of achieving such targets on N losses (via leaching, denitrification and volatilisation) are important when considering the environmental implications of further intensification. [Copyright &y& Elsevier]

Abstract: Australia has a long history of mixed farming. This paper examines the integration of Australian cropping and livestock production from three perspectives: as a factor in land use change, a consequence of individual management practices and a means of meeting farmers’ multiple objectives. Since about 1995, the proportion of cropped land has increased on Australian cropping farms while livestock numbers have decreased. Land use in the north-eastern, central and south-western regions of the cropping zone have diverged. Despite these changes, mixed farms still dominate Australia’s broadacre farming regions. Previous accounts of the dimensions in which farming enterprises are integrated can be simplified for Australian broadacre agriculture. For most purposes it is sufficient to consider a nested set of four integration options: “specialization” (not integrated organizationally), “separation” (integrated organizationally only), “rotation” (integrated organizationally and spatially, but not temporally) and “synchronization” (integrated in all three dimensions). We illustrate these integration options with a short survey of agronomic practices that affect crop–livestock integration. We review the farmer objectives that enterprise integration can meet and the constraints that limit it, seeking to balance social, economic and agronomic factors. We use a dynamic simulation model to make a first quantification of the economic risk reduction provided by enterprise diversification. Constraints imposed by limited labour, capital, and management attention cannot be overlooked; this is especially relevant in Australia where labour is increasingly in short supply. We characterize our surveyed set of agronomic practices with respect to the farmer objectives they affect. We find that farmers generally have the option of meeting a particular objective through different practices that affect different dimensions of integration. Practices that result in closer integration in time and space generally require greater management attention; practices that do not integrate in space typically require an increase in external inputs. History suggests that current commodity price ratios may be sufficient to slow or reverse the overall land use trend away from livestock production. In the longer term, forecast increases in worldwide demand for meat, energy costs and soil resource constraints will all encourage Australian cropping farmers to maintain mixed systems; however reduced availability of labour relative to capital will push land use toward specialized systems. Valuing the benefits and costs associated with differing degrees of enterprise integration is a major research challenge that will require insightful application of both biophysical and economic models. [Copyright &y& Elsevier]

Abstract: This paper reports on the use and effectiveness of two tools used for the ex-ante evaluation of a suite of crop-livestock farming-systems R&D (research and development) projects proposed for Australian grain-growing districts. The focus is on determining the value of two tools developed for this purpose—a bio-economic whole-farm analysis tool (BENEFIT) and an adoption and diffusion prediction tool (ADOPT). Designed to be used by researchers, project managers, extension agents and research, development and extension managers, ADOPT predicts speed and extent of adoption, while BENEFIT models physical and financial effects of the practice change on the farm. The tools were used as a prerequisite to the approval of R, D & E projects seeking funding from a new round of Australia’s Grain and Graze program. Each tool provides information that is useful for making decisions about investments in agricultural R, D & E that is not easily obtainable by other means. The benefits of the ex-ante evaluation processes were that those proposing and delivering the projects learnt more about the drivers of project impact. The results of the study show that, when used together, these tools can lead to better investment decisions and project-level delivery strategies, particularly where impact is highly dependent on participatory and local, context-specific delivery. [Copyright &y& Elsevier]

Abstract: The FARMSCAPE Information System emerged in a long-running research program aimed at making simulation models useful to Australian farmers in managing climatic variability. This paper is about how well it has worked. This is reported in relation to two standards: (1) the value to thinking and action expressed by farmers and their consultants, (2) correspondence with theory about learning and judgement in uncertain external environments. The former utilises recorded narrative interviews with participants over many years. The latter uses a cognitive framework drawn from theory of judgment and decision making featuring the relationship between intuition and analysis (). The cognitive theory framework makes sense of several evaluation surprises. The first was high enthusiasm by largely-intuitive farmers for an analytic approach to soil water in conjunction with a newly-appreciated “bucket” metaphor for water balance. The second surprise was the virtual absence of soil water measurement 10years later. This had been replaced by various intuitive estimates, calibrated to maintain a heuristic relationship with regard to the “bucket” as a resource. Farmers and their advisers were facilitated in using simulation for thought experiments and planning under climatic uncertainty. Benchmarking enabled problem solving in documented conditions. Scenario analysis using historical climate records supported thought experiments by providing probability distributions that were valued for shaping expectations as a “history of the future”. In retrospective evaluation interviews, researchers were surprised to find that yield forecasting and tactical decision making, anticipated to be analyses that were both site- and season-specific forecasts, had served farmers as “management gaming” simulations to aid formulating action rules for such conditions, thus reducing the need for an on-going decision-aiding service. Equipped with their soil monitoring techniques and with their heuristic rules, farmers still reserved a place for simulation “when you’ve got a planting situation out of the ordinary.” [Copyright &y& Elsevier]

Abstract: Policy makers in the agricultural sector are confronted with challenges which might drive land use change and ultimately agricultural profitability to a substantial degree. The challenges include questions around climate variability, demographic changes, use of land for bio-fuel production and ensuring an increase in food production. As profitability triggers many agri-business decisions, knowledge about the existing socio-economic landscape and the economic profile of a region as well as potential impacts on profits provides useful contextual information when agricultural policies are designed. Given the upcoming challenges and their associated uncertainties, it is important to ensure that a map of agricultural profit can be reproduced in a scenario and simulation setting which will allow exploring uncertainties around the impacts on agricultural profits as well. There is however currently no flexible system in operation which allows for a consistent update of a map of agricultural profits in Australia or elsewhere. This paper describes a process that has been developed to produce a map of agricultural profit for Australia for the year 2005/2006. The process involves a complex data architecture that accounts for heterogeneous information that is collected by a variety of institutions across different scales. All information can be comfortably queried and query results can be forwarded for immediate processing and subsequent visualisation in a geographic information system (GIS). To facilitate the production of profit maps in the future, the system provides flexibility regarding an update of new economic information but it can also be linked to maps that show an updated distribution of land use. A map of agricultural profit on a large scale and regular updates thereof will help understand profit trends in time and across space. It will help identifying regions that have a lower economic profile and will inform decisions regarding the design of regulatory policies. As these maps are developed using national scale data, we do not recommend using the results at the farm level but we suggest using separate catchment scale profit assessments to calibrate the national scale profit map. The proposed system is well suited to be used in various land use management and economic scenarios and will represent a step forward regarding a scenario impact assessment on agricultural profits. It will also help understand the economic benefit of land use on a large scale. [Copyright &y& Elsevier]

Abstract: Dairy systems in southern Australia rely on grazed feed from pasture to supply between 50% and 70% of total herd feed requirements on an annual basis. However, the dominant pasture type in the region, which is based on perennial ryegrass (Lolium perenne), commonly results in feed deficits in summer which must be filled with supplements purchased off-farm, and feed surpluses in spring which must be conserved. Both of these strictures impose costs on farm businesses. It is likely, therefore, that additional grazeable feed available to dairy herds in southern Australia may have different economic value when interactions between season, stocking rate, calving date, and locality are taken into account. The analysis reported in this paper aimed to estimate, using the farm systems simulation model UDDER, the effect of these interactions on the efficiency with which extra feed can be converted to extra milk production, and therefore the possible gross economic value of the additional feed. ‘Base’ farm simulations for ‘average’ and ‘top 10%’ farms (ranked according to farm profitability) in two localities (Terang: average annual rainfall 796mm, 8month growing season; and Ellinbank: average annual rainfall 1085mm, 9–10month growing season) were created to mimic the physical production and profitability of these farms as seen in regional farm benchmark datasets. These simulations were then altered to add the equivalent of 10% of the total annual herbage accumulation used in the Base simulation either on a pro-rata basis all year round, or in autumn only, in winter only, in spring only, or in summer only. The additional feed amounted to 620 and 780kg DM/ha for Terang average and top 10% farms respectively, and 735 and 905kg DM/ha for Ellinbank average and top 10% farms respectively. The management policies used in the Base simulations were then adjusted to harvest as much of the extra feed as possible, either by direct grazing or through silage conservation, while keeping the key system state indicators of cow condition score and average farm pasture cover within the limits known to result in long-term sustainable production. The efficiency with which extra feed was utilised was greatest in summer in all scenarios (80–100% of the extra feed supplied was harvested, all by direct grazing). This translated into consistently high gross economic returns of between $0.26 and $0.34per kg DM of extra feed added to the model. Utilisation efficiency was lower in all other seasons and/or required marked increases in silage conservation, both of which resulted in lower gross economic returns per kg DM of additional feed. The impact of interactions between locality, season, stocking rate (higher in top 10% farm simulations than average farm simulations) and calving date (earlier at Terang than at Ellinbank) were clearly captured in the model. These interactions have very large effects on the profitability of growing extra feed at different times of the year. Agronomic research for the southern Australia dairy industry should focus on low-cost ways for supplying additional grazeable feed in summer, since current forage species options for this time of year are limited. [Copyright &y& Elsevier]

Abstract: The prospect that decision support systems (DSS) can help farmers adjust their management to suit seasonal conditions by putting scientific knowledge and rational risk management algorithms at farmers’ fingertips continues to challenge the science and extension community. A number of reviews of agricultural DSS have called for a re-appraisal of the field and for the need to reflect on past mistakes and to learn from social and management theory. The objective of this paper was to investigate whether there is an emerging consensus, among stakeholders in DSS for Australian agriculture, about the lessons learned from past experience with DSS tools. This investigation was conducted in three parts. The first part was a distillation of suggestions for best practice from the relevant literature. The second part was a reflection on what the champions of five current DSS development and delivery efforts in Australia learned from their recent efforts. The third part tested the level of support for the combined findings from the first and second approaches by surveying 23 stakeholders in the research, development, delivery and funding of DSS. The key propositions relating to best practice that were supported by the survey, listed according to the strength of support, were: 1. It is essential to have a plan for delivery of the DSS beyond the initial funding period. 2. DSS need to be embedded in a support network consisting of farmers, consultants and researchers. 3. DSS development requires the commitment of a critical mass of appropriately skilled people. 4. A DSS should aim to educate farmers’ intuition rather than replace it with optimised recommendations. 5. A DSS should enable users to experiment with options that satisfy their needs rather than attempt to present ‘optimised’ solutions. 6. DSS tools stand on the quality and authority of their underlying science and require ongoing improvement, testing and validation. 7. DSS development should not commence unless it is backed by marketing information and a plan for delivery of the DSS beyond the initial funding period. While the DSS stakeholders supported the proposition that it is essential to have a plan for delivery of a DSS beyond the funding period, the majority resisted the notion of DSS development being market-driven and especially commercial delivery of DSS. We argue that since public funding of the delivery of DSS for farmers’ management of climate risk is highly unlikely, reaping the benefits of lessons learned from past efforts will require that DSS stakeholders change their perception of the commercial delivery model or find an alternative way to fund the delivery of DSS beyond the R&D phase. [Copyright &y& Elsevier]

Abstract: Evaluating the potential scale of adoption of a technological innovation or management practice at the farm business scale can help gauge the potential size of an industry for the purposes of prioritising resources for research and development. In this paper we address the question of quantifying the potential area of adoption of a perennial pasture, lucerne (Medicago sativa L.), in dryland mixed farming systems in Australia. Lucerne pastures play a significant role in dryland farming systems in the wheat-sheep zone of southern and western Australia. While there are benefits of integrating lucerne into cropping systems there will inevitably be additional costs, and the scale of adoption of lucerne will depend largely on the increase in farm profit resulting from the introduction of lucerne. Whole-farm economic models of representative farms in the Australian wheat-sheep belt were used to determine the key drivers for the scale of adoption of lucerne. For a particular farming system the optimal area of lucerne which maximises whole-farm profit is found to depend on production, price and cost conditions. Generally, no more than 30% of a farm was allocated to lucerne according to those conditions and location of the farm. For most scenarios examined the response of profit was flat around the optimal area. This implies that lucerne could be grown on areas greater than the optimum, in order to reduce groundwater recharge (and thereby reduce the risk of dryland salinity), without greatly reducing whole-farm profit. The optimal area of lucerne in all regions was limited by the area of suitable soil types and proportion of lucerne in the most profitable lucerne-crop sequences. At all price levels assumed in this study lucerne remained as part of the optimal enterprise mix for all farm types examined. Lucerne productivity was also a major determinant of the optimal area of lucerne. The sensitivity of profit to changes in winter and/or summer production varied between regions and for different livestock enterprises. The differences were driven by the timing of energy demands and supply of feed in individual farming systems. In all regions the optimal area and profitability of lucerne varied with livestock enterprise. The analyses showed that changing from wool production to meat production enabled greater economic benefit to be realised from lucerne. This was consistent across farm types and demonstrated the value of lucerne as a source of high quality feed for finishing prime lambs in summer. The results of this study demonstrate that lucerne is profitable in a range of environments on a significant proportion of the farm area, but that this area is small relative to that required to significantly influence in its own right the environmental issue of salinity. [Copyright &y& Elsevier]

Abstract: The Moore Catchment, which lies to the north of Perth in Western Australia, suffers from a number of problems related to water management. Farmers want to manage salinity and waterlogging problems through the use of drains, but this has possible negative off-farm impacts on both the environment and flood risk. Views on responsibilities for managing water within the catchment differ between farmers, local communities and government agencies. This paper reports the results from surveys of attitudes towards catchment management, for two community groups: residents of Perth and residents of rural towns in the catchment. These surveys elicited general attitudes towards the environment and agriculture, and views on responsibilities for managing the catchment. It also included a choice modelling section, where the attributes under consideration included the area of land under salt and trees, ecological risks to off-farm wetlands and risk of flooding, farm incomes and personal financial contributions to a management fund. Preliminary results indicate that residents of both rural towns and Perth are willing to pay to avoid damage to the natural environment, both on and off-farm, as well as the risk of flooding. Perhaps more surprisingly, whether farmers’ incomes were being negatively affected in a choice set has a very strong impact on the choice made. [Copyright &y& Elsevier]

Abstract: The provision of food causes environmental impacts that range from local through to global in scale. Organic farming, used in general here to mean farming practices with a greater emphasis on long-term sustainability, is one general approach to reduce these impacts. Whilst organic farming may be argued to be superior to conventional farming on the basis of local impacts, it is not often clear how organic farming performs relative to conventional farming in terms of wider, global impacts. In this paper we present a comparative assessment of on-farm and indirect energy consumption, land disturbance, water use, employment, and emissions of greenhouse gases, NO x , and SO2 of organic and conventional farming in Australia. A hybrid input-output-based life-cycle technique is employed in order to ensure a complete coverage of indirect requirements originating from all upstream production stages. Using data from a detailed survey of organic farms, the results show that direct energy use, energy related emissions, and greenhouse gas emissions are higher for the organic farming sample than for a comparable conventional farm sample. Direct water use and employment are significantly lower for the organic farms than for the conventional farms. However, the indirect contributions for all factors are much higher for the conventional farms, leading to their total impacts being substantially higher. This shows that indirect effects must be taken into account in the consideration of the environmental consequences of farming, in particular for energy use and greenhouse gas emissions, where the majority of impacts usually occur off-farm. Subject to yield uncertainties for organic versus conventional farming, from the sample here we can conclude that in addition to their local benefits, organic farming approaches can reduce the total water, energy and greenhouse gases involved in food production. [Copyright &y& Elsevier]

Abstract: What is causing the increasing densities of native shrubs, or so-called ‘woody weeds’, in some semi-arid pastoral lands and how might they be most effectively managed? This question has been on the rangeland policy agenda in Australia for more than one hundred years. This paper describes a fresh examination of this question using a systems approach. A key component of the approach involved ‘mapping the problem’. Using a systems-based approach, landholders developed four system diagrams broadly describing the ecology of woody weed re-occurrence, control options, property economics and management constraints with diagrams identifying how different factors related to, or influenced, each other. Agency personnel also constructed a system diagram describing institutional and regulatory constraints, and their interactions. Later, all these system diagrams formed the basis for an adaptive management model with capabilities for developing and quantitatively evaluating alternative management strategies relating to woody weeds. This model is called the Woody Weed Planner. The Woody Weed Planner contains mathematical relationships developed through field experimentation over the last 25–50 years covering the ecology of woody weeds, control options and control economics. These relationships enable the user to generate mathematical responses as a result of changing model parameters. A key component of the model is the ability to simulate the effects of alternative management responses given different rainfall scenarios. To enable this to occur, the Planner allows the user to replay historical rainfall patterns and ask the question “what impact will these have on woody weeds, stocking rates and economic performance on my property?” [Copyright &y& Elsevier]

The Australian sugar industry is seeking to increase profitability through better integration across a value chain fragmented among many owners. Within the cane harvesting and transport sectors, many existing inefficiencies are a result of excessive numbers of harvesting machines owned by harvester contractors and growers, and the fact that most harvesters operate within a short time window each day. In order to improve the complex system from a tactical and strategic planning perspective, leading to reduced costs of production, a modelling framework identifying the key drivers and links must first be developed. Upon developing the framework, techniques in operations research, financial modelling, and simulation can be applied to investigate opportunities to enhance the system in partnership with industry. This paper describes the development of such a framework through participation with two case-study mill areas within the Australian sugar industry, along with its application to improve the efficiency of the harvesting and transport system. Through reducing the number of harvesters in the region and implementing best practice principles for harvesting, one of the case study mills showed potential gains in profitability of up to AU$1 million per annum. Implementation took place in one of the case study regions during the 2003 harvest season for which the region is now pursuing further adoption in 2004. [Copyright &y& Elsevier]

Over the last 10 years, there has been a rapid expansion of rainfed cotton production in Australia. The majority of this area has used “skip row” configurations in which certain rows in the crop are not sown with the aim of providing a slowly available supply of soil moisture during periods of low rainfall. In the past, the OZCOT cotton crop simulation model has been used with long-term climate records to assess the impact of different management strategies for irrigated cotton production and to study the prospects for rainfed cotton production in the major cotton growing regions. In this paper, we present modifications made to OZCOT to better accommodate skip row. First, a simple procedure previously used to approximate light interception of row crops was assessed for its ability to enhance the capability of OZCOT to simulate skip row configurations and second, a modification to allow for the possibility that water in the skip is not as freely available as the water in the plant row was also explored. Including modifications to allow for differences in soil water extraction significantly improved predictions of crop yield for cotton in skip row configurations across a number of locations in the Eastern Australian cotton producing regions, but modifications to account for light interception in row configurations reduced the ability of the model to simulate skip row cotton yields. The modified model gave reasonable predictions of yield for solid planted and skip row crops. The performance was within the range of results published for solid planted crops over a range of nitrogen and irrigation treatments and planting dates. The model’s simulation of skip row yields when compared to solid planted crops grown under the same conditions, reflected the relationships seen in the measured data and those published in the industry literature. [Copyright &y& Elsevier]

Structural econometric models are often used in the analysis of economic issues that affect the agricultural industries because of their rigour in modelling the behavioural nature of the relationships between the major economic variables in the industries of interest. The value of such models for economic analyses depends on how accurately they represent an industry''s economic activity. In the Australian livestock industries, model applications have often been in a single industry context which does not adequately capture the supply and demand relationships that exist between the related industries. Model integration offers the opportunity to rectify this deficiency but it also has the potential to introduce additional error into the model''s estimation and simulation processes and reduce value of the model for economic analysis. This paper investigates that possibility in the context of the Australian grazing livestock sector. Using exogenous shock experiments, it was found that model integration did not adversely effect the predictions of the endogenous variables by the combined models. It is concluded that the additional modelling complexity of model integration is not detrimental to the modelling of industry activity and provides an improved and more realistic economic mechanism for evaluating issues such as new production technology adoption that have important effects on the Australian livestock industries. [Copyright &y& Elsevier]

FARMSCAPE (Farmers'', Advisers'', Researchers'', Monitoring, Simulation, Communication And Performance Evaluation) is a program of participatory research with the farming community of northeast Australia. It initially involved research to explore whether farmers and their advisers could gain benefit from tools such as soil characterisation and sampling, climate forecasts and, in particular, simulation modelling. Its current focus is facilitating the implementation of commercial delivery systems for these same tools in order to meet industry demand for their access. This paper presents the story of what was done over the past decade, it provides performance indicators of impact, it reflects on what was learnt over this period and it outlines where this research is likely to head in the future.Over the past 10 years, the FARMSCAPE team employed a Participatory Action Research approach to explore whether farmers could value simulation as a decision support tool for managing their farming system and if so, could it be delivered cost-effectively. Through farmer group engagement, on-farm trials, soil characterisation, monitoring of crops, soils and climate, and sessions to apply the APSIM systems simulator, FARMSCAPE represented a research program on decision support intervention. Initial scepticism by farmers and commercial consultants about the value of APSIM was addressed by testing its performance both against measured data from on-farm trials and against farmers'' experiences with past commercial crops. Once this credibility check was passed, simulation sessions usually evolved into participants interactively inquiring of the model the consequence of alternative management options. These ‘What if’ questions using APSIM were contextualised using local climate and soil data and the farmer''s actual or proposed management rules.The active participation of farmers and their advisers, and working in the context of their own farming operations, were the key ingredients in the design, implementation and interpretation of the FARMSCAPE approach to decision support. The attraction of the APSIM systems simulator to farmers contemplating change was that it allowed them to explore their own system in a manner equivalent to learning from experience. To achieve this, APSIM had to be credible and flexible. While direct engagement of farmers initially enabled only a limited number of beneficiaries, this approach generated a commercial market for timely and high quality interactions based on soil monitoring and simulation amongst a significant sector of the farming community. Current efforts are therefore focused on the training, support and accreditation of commercial agronomists in the application of the FARMSCAPE approach and tools.The FARMSCAPE approach to decision support has come to represent an approach to guiding science-based engagement with farm decision making which is being tested nationally and internationally. [Copyright &y& Elsevier]

The seasonal break is a rainfall event that has traditionally initiated sowing and enabled plant establishment in Mediterranean-type environments. Despite its importance to crop production, neither the pattern of the seasonal break, nor the impact of recent autumn rainfall decline in eastern Australia on the pattern has been quantified at a national scale. Adaptive strategies to remove reliance on the seasonal break for crop establishment can include combinations of novel genotypes and innovative crop management. This paper (i) shows how seasonal changes may be altering the pattern of sowing opportunities across southern Australia, and (ii) evaluates the potential for adaptive management to deal with these changes using a case-study in southern Australia involving early, deep-sown wheat cultivars with long coleoptiles to reduce the dependence on the seasonal break for successful crop establishment. In the first part of the study, the timing of the seasonal break across the southern Australian cropping regions was determined using the sum of a 7-day rolling mean rainfall to evaporation ratio > 1 to trigger a sowing opportunity between 1 March and 30 July using long-term (1971–2018) gridded (0.05° × 0.05°) historical climate data. The relationship between early-season climatic conditions and adaptive management options was then evaluated using a growth chamber experiment and a field experiment in a Mediterranean-type environment to evaluate the factors leading to successful establishment of earlier deeply sown wheat cultivars with long coleoptiles. The analysis revealed spatial and seasonal variability with the earliest median seasonal break (27-March) in New South Wales (NSW) and Victoria, and the latest (3-June) in Western Australia (WA). The largest shift in seasonal break was a 17-day advance in the Mallee and Sandplain of WA, and an 11-day delay in Central NSW during the period 1990–2018. Evaluation of the factors controlling establishment of a long coleoptile wheat cultivar suggested that soil temperatures in the early sowing windows were unlikely to reduce coleoptile length, but seeding depth, soil type and water availability will play an important role on emergence. In summary, the shifts in the climatic conditions at the break of the growing season have not been the same across the southern cropping region. Adaptations for this climatic shift such as long-coleoptile, deep-sowing strategies for wheat show significant promise but careful consideration of soil factors is required to ensure success and to improve on-farm decision making regarding its use. [Display omitted] • Understanding recent climate shifts that influence the seasonal break underpins better decisions on GxM responses on-farm. • The seasonal break varied spatially in southern Australia, but it has seen shifts of −11 to 17 days in recent decades. • Long coleoptile wheat cultivars are a promising option for adaptation to this shift. • Soil temperatures during early sowing periods will not inhibit long coleoptiles, but soil moisture and texture were critical. • Combining knowledge of climatic shifts with successful crop emergence factors is critical to develop adaptive GxM strategies. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. 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. Unlabelled Image • Risk mitigation benefits of mixed farming examined across 6 locations in Australia. • Long-term variability in returns from crop and livestock enterprises were modelled. • Down-side risk was lower from livestock than cropping enterprises. • Annual returns from crop and livestock enterprises were weakly or not correlated. • Mixed farms were more risk efficient than those specialising on a single enterprise. [ABSTRACT FROM AUTHOR]

At least 25% of lambs born in Australia die before marking. Research across southern Australia has demonstrated that reducing mob size at lambing by 100 ewes will, on average, increase the survival of single-born lambs by 0.8% and twin-born lambs by 2.2%. In this paper we assessed the economic value of lambing ewes in smaller mobs to improve lamb survival. The analysis considered scenarios for Merino and non-Merino flocks where producers subdivided lambing paddocks using temporary or permanent fencing, or where ewes were reallocated within existing paddocks based on ewe pregnancy status. Optimum mob sizes were most sensitive to the type of fencing used for subdivision, whether ewes were single- or twin-bearing, whether the effect of paddock size on potential stocking rate was included and the target return on investment. Breed, ewe stocking rate, scanning percentage and lamb price also impacted optimum mob size but had a smaller effect. The optimum mob size for twin-bearing Merino and non-Merino ewes was between 34% and 60% that of single-bearing ewes and this was similar for scenarios where paddocks were subdivided or ewes were reallocated within existing paddocks. Permanent subdivision of paddocks also presents an opportunity to increase stocking rate by capitalising on the benefits of improved pasture utilisation in smaller paddocks. The relationship between paddock size and pasture utilisation is not well quantified but it has an important effect on optimum mob and paddock size. The value of reallocating ewes within existing paddocks was greatest at a scanning percentage of 150% as this presents the greatest opportunity to alter mob sizes for single- and twin-bearing ewes. The economic return from adjusting the relative mob size of twin-bearing ewes from 100% to 50% that of single-bearing ewes was up to $0.27/Merino ewe/yr and $0.44/non-Merino ewe/yr with lamb at $6/kg carcass weight. Overall, these analyses demonstrate that reducing mob size at lambing can be a profitable strategy for improving lamb survival depending on the current size of lambing mobs. However, it is difficult to provide generic recommendations to producers for the optimum mob size of ewes and value of paddock subdivision because these are dependent on enterprise-specific factors. • The optimum mob size for ewes and value of paddock subdivision are enterprise-specific. • Optimum mob size was smaller for twin-bearing ewes compared with single-bearing ewes. • Optimum mob size was smaller where the costs of paddock subdivision were reduced. • The return on investment was greater when splitting up larger mobs. [ABSTRACT FROM AUTHOR]

This paper draws on a decadal dataset of 250 farms in south-western Australia. These farms, when categorised according to their type of farming system and business strategy, faced different trends in their terms of trade. Profitability measures of these farms for the period 2002/3 to 2011/12 were compared. Most farms, other than some highly crop dominant ones, applied a strategy of maintaining or increasing their cropping intensity and farm size over the decade. The strategy of a greater commitment to cropping was supported by cropping technologies and beneficial change in agronomic practices. Increased cropping was universally profitable among all types of farming systems, providing a statistically significant increase in operating surpluses. By contrast, irrespective of their underpinning farming system, farms which did not strategically increase their intensity of cropping generated statistically significant less returns to their business equity. By maintaining rather than increasing their cropping intensity these businesses failed to capture the operating surplus upside available from increased cropping. Overall, the results show that management of farming systems is not solely about tactics and flexibility. Strategic management can additionally influence the nature and profitability of farming systems. • Business strategies applied to different Australian farming systems are assessed. • The strategy of increased cropping is consistently significantly profitable. • Managing farming systems is not solely about tactics and flexibility. • A beneficial strategy can greatly add to farm business wealth and profit. [ABSTRACT FROM AUTHOR]

Digitalisation is widely regarded as having the potential to provide productivity and sustainability gains for the agricultural sector. However, there are likely to be broader implications arising from the digitalisation of agricultural innovation systems. Agricultural knowledge and advice networks are important components of agricultural innovation systems that have the potential to be digitally disrupted. In this paper, we review trends within agricultural knowledge and advice networks both internationally and in Australia, to anticipate and prepare for potential transformations in these networks. Through a combined structured and traditional review of relevant literature, we come to three key conclusions regarding the state-of-the-art. First, the connectivity of humans and technologies in agricultural knowledge and advice networks and value chains will likely continue to increase. Second, transparency of agricultural practices and informational interaction between farmers, advisors, agri-businesses, consumers and regulators will drive and be driven by growing connectivity. Finally, there are likely to be challenges balancing the priorities of various agricultural stakeholders as agricultural innovation systems digitalise. These findings have implications for the oversight of international agri-food sectors. • Research concerning the digitalisation of agricultural innovation systems is reviewed. • Dominant trends concerning agricultural advisory services are presented. • Connectivity, transparency and governance are found to be key themes. • Australian agricultural knowledge and advice networks provide further context for analysis. [ABSTRACT FROM AUTHOR]

Mixed crop-livestock farming systems provide food for over half of the global population. However, some important food exporting countries, like Australia, are predicted to be vulnerable to climate change and may require transformative adaptations if they are to continue their role in food exportation. This paper assesses the potential impacts of projected climate change by 2030 (0.4–1.6° increase in mean temperature) on Australian mixed crop-livestock systems and examines the consequences of shifts in land allocations to cropping and grazing, in these systems, as an adaptation option. Farm bio-economic simulation models were developed for these mixed enterprise systems in several regions of Australia. These models were based on biophysically coupled crop, pasture, and livestock simulation models that in turn drew on site-based downscaled climate projection datasets. The farm models calculated farm profitability and risk measures. A range of land use changes was investigated. At drier locations facing adverse climate change, results showed a transition towards a greater emphasis on livestock production could be beneficial when assessed against multiple criteria of farm profit, downside financial risk, and environmental damage. We highlight some industry and government actions and policies that could facilitate these preferred adaptation strategies at such locations. • Temperature increase of 0.4–1.6° affect mixed crop-livestock systems in Australia. • Transition towards a greater emphasis on livestock production is often desirable. • Financially optimal land allocations vary between historical and future climate. • Increase in the land devoted to pasture is a strategy to manage future climate risk. [ABSTRACT FROM AUTHOR]

• The value of extra pasture DM for livestock production can be estimated using several different methods. • The two-price market value method can be an efficient way to estimate the value of extra seasonal dry matter yield of pasture grown and used. • To demonstrate its application, the method is used to value the seasonal yield of 19 perennial ryegrass cultivars grown in temperate Australia. • The value of extra pasture estimated using the two-price market value method can be easily generalised across a range of farming systems. The challenges of estimating the value of growing and using extra pasture to the farm business often necessitates using complex systems modelling of individual farms. In this paper, a straightforward market value method is outlined, where technical substitutes for which there is a defined market price are used as proxies to estimate an equivalent value for extra pasture used in a farm system. The method can be useful for all grazed livestock production systems where substitutes for pasture are purchased and sold. The two-price approach presented advances on previous applications of using market values by accounting for differences in the value of extra pasture DM used on farm in different seasons. The value per extra kg DM harvested in seasons when pasture typically limits livestock production, for example during summer/autumn in temperate environments, and used on farm equates to the market price of the replacement cost as purchased supplementary feed. This is the maximum the extra pasture DM could be worth when used in the farm system. Conversely, the value per extra kg DM harvested in spring when extra pasture is likely to be in surplus of livestock requirements, equates to its market price if sold, as standing hay for example, termed the salvage value. This two-price approach was applied to value the previously published seasonal DM yield differences of 19 perennial ryegrass cultivars, compared to an industry standard cultivar, grown in three regions of Victoria, Australia. Results were then compared to the value of extra pasture DM previously estimated using system simulation analyses of three farms and applied to the same perennial ryegrass data set. The difference in the value of extra pasture DM estimated using the two methods ranged from $0.01/kg DM to $0.24/kg DM. Overall, the two-price method estimated an extra $24 to $200/ha.year benefit over the industry standard cultivar for the 19 cultivars across the three regions, similar to the extra $0 to ∼ $180/ha.year estimated by the previous system simulation analysis. The two-price market value method can be an efficient way to estimate the value of extra seasonal DM yield of pasture, with results easily generalised across a range of farming systems. [ABSTRACT FROM AUTHOR]

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. • The decision when to remove lucerne in leys requires a whole farm analysis. • Differences in removal dates at the farm level were small and yet significant. • Land in transition presents opportunities for increasing water and N use efficiency. • Summer termination of lucerne was overall more profitable, efficient and less risky. • Perennial legume pastures need to be seen as a whole-of-farm resource. [ABSTRACT FROM AUTHOR]