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Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate‐only model, an environment‐only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020–2039 and 2060–2079. The climate‐only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment‐only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020–2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060–2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry. [ABSTRACT FROM AUTHOR]

Cultivating business growth intentions in rural, regional, and remote women entrepreneurs is crucial, considering the unique challenges they face in rural areas. The growth intentions of rural, regional, and remote women entrepreneurs remain understudied. This study pioneers research on the interplay between entrepreneurial leadership competency, identity, and growth intentions of rural, regional, and remote Australian women. We surveyed rural, regional, and remote women entrepreneurs in Queensland, Australia, using structural equation modeling for analysis. Results revealed a positive relationship between entrepreneurial leader identity, business growth intentions, and entrepreneurial leadership competency. Moreover, entrepreneurial leadership competency positively correlated with growth intentions. The study indicated that entrepreneurial leadership competency partially mediates the link between identity and growth intentions. This research addresses a theoretical gap by introducing a new model showcasing the relationships between entrepreneurial leadership identity, entrepreneurial leadership competency, and venture growth intentions. From a practical standpoint, our findings strengthen the business case for improving tailor-made rural, regional, and remote entrepreneurial development programs. [ABSTRACT FROM AUTHOR]

Rehabilitation of disturbed sites is a complex process requiring constant monitoring and assessment, with current methods being somewhat obsolete, manual, and rather fraught with risk in terms of beneficial outcomes of the evaluation. This study challenges the status quo of manual assessments and build a new methodology to recognise a clear need for a quasi-automated and reliable remote sensing method to achieve rapid mine rehabilitation monitoring. The aim of this study was to innovate and develop an ensemble analytic methodology for the use of airborne LiDAR, in conjunction with deep learning, to rapidly evaluate the rehabilitation status of post-mined areas. Airborne LiDAR datasets, obtained via an Optech ORION m/c 200 sensor, were collected over bauxite mining operations on the western coast of Cape York Peninsula, Queensland, Australia. These datasets were processed into a 3 D point cloud using the Esri ArcGIS Pro platform. An ensemble analytical approach was developed, leading with a Convolutional Neural Network (CNN) algorithm, which was trained to recognise, then classify images of the reference site (natural ecosystems) and active rehabilitation areas. The result of this classification was then leveraged, training in turn a support vector machine (SVM) algorithm which assessed the entire LiDAR collection, resulting in a predictive surface of rehabilitation status. This surface, as the final analytical product, was assessed for validity using ground-truth plot data and an ordinary least squares regression model, as well as comparison to subject matter expert evaluation through a Delphi expert panel assessment. The results indicate that the predictive surface, as the final analytical product, had statistically significant correlation coefficient with multiple attributes (or predictor) that correlated with the rehabilitation status interpretation. These predictor variables were primarily structural in nature and included the canopy height, sub-canopy height, key species as a proportion of canopy, herbaceous ground cover percentage, litter ground cover percentage, and distance from haul road (p < 0.05). A Delphi expert collaboration comprised of ten environmental science subject matter experts and 600 observations, indicated a high precision (r = 0.89 at p < 0.05) of the prediction surface when compared with a subject expert panels assessment, as well as a high Total Deviation Index (TDI) of 16% (p < 0.05). This indicated positive agreement between the panel’s assessment and the predictive surface. This study suggests that airborne LiDAR and deep learning ensemble analytics can be used as a rapid means to estimate the rehabilitation status of disturbed sites. [ABSTRACT FROM AUTHOR]

Savanna fire is a major source of global greenhouse gas (GHG) emissions. In Australia, savanna fire contributes about 3% of annual GHG emissions reportable to the Kyoto Protocol. In order to reduce GHG emissions from savanna burning, the Australian government has developed and approved a Kyoto compliant savanna controlled burning methodology-the first legal instrument of this kind at a global level-under its Emission Reduction Fund. However, this approved methodology is currently only applicable to nine vegetation fuel types across northern parts of Australia in areas which receive on average over 600 mm rainfall annually, covering only 15.4% of the total land area in Australia. Savanna ecosystems extend across a large proportion of mainland Australia. This paper provides a critical review of ten key factors that need to be considered in developing a savanna burning methodology applicable to the other parts of Australia. It will also inform discussion in other countries intent on developing similar emissions reduction strategies. [ABSTRACT FROM AUTHOR]

Several studies have quantified the energy consumption associated with crop production in various countries. However, these studies have not compared the energy consumption from a broad range of farming practices currently in practice, such as zero tillage, conventional tillage and irrigated farming systems. This study examines direct on-farm energy use for high value grain crops grown under different farming practices in Australia. Grain farming processes are identified and "typical" farming operation data are collected from several sources, including published and unpublished literature, as well as expert interviews. The direct on-farm energy uses are assessed for 27 scenarios, including three high value grain crops--wheat, barley and sorghum--for three regions (Northern, Southern andWestern Australia) under three farming conditions with both dryland (both for conventional and zero-tillage) and irrigated conditions. It is found that energy requirement for farming operations is directly related to the intensity and frequency of farming operations, which in turn is related to tillage practices, soil types, irrigation systems, local climate, and crop types. Among the three studied regions, Western Australia requires less direct on-farm energy for each crop, mainly due to the easily workable sandy soils and adoption of zero tillage systems. In irrigated crops, irrigation energy remains a major contributor to the total on-farm energy demand, accounting for up to 85% of total energy use. [ABSTRACT FROM AUTHOR]

Abstract: Farm forestry is a very minor land use in the inland agricultural landscapes of Australia. The Australian Government intends to introduce a program to encourage landholders to trade the carbon sequestration value of plantations and this may change the relative profitability of plantations against other agricultural land uses. This research compares the returns from a timber and ‘carbon’ plantation, with those from grazing and a common crop rotation in the Kingaroy area of Queensland. Typical production patterns for all systems were developed from producer and expert knowledge and soil and vegetation sampling were used to estimate sequestration rates. The costs and benefits of all land use systems were converted into monetary terms and discounted to produce net present values. With a standard discount rate and average commodity prices based on recent history, cultivation is the most profitable option, followed by pasture and plantations. After the inclusion of carbon, plantations are the most profitable option, followed by pasture and cultivation. A number of qualifications of these findings are also discussed. [Copyright &y& Elsevier]

This study suggests 11 reasons why agriculture should be included in the Australian Government's Carbon Pollution Reduction Scheme (also known as the Australian Emissions Trading Scheme, AETS) and proposes some cost-effective methods of including agriculture in the AETS. If Australia incorporates agriculture into the AETS, there will be the added benefit of providing global leadership to other major polluting and agricultural commodity exporting countries in developing similar inclusive emissions trading schemes. [ABSTRACT FROM AUTHOR]

The authors review the decision-making since the Labour Government came into office (November 2007). The Australian Government's 'Carbon Pollution Reduction Scheme' White Paper (15 December 2008) proposes that an Australian Emissions Trading Scheme (AETS) be implemented in mid-2010. Acknowledging that the scheme is comprehensive, the paper finds that in many cases, Australia will take a softer approach to climate change through the AETS than the European Union ETS (EUETS). The paper assesses key issues in the White Paper such as emissions reduction targets, GHG coverage, sectoral coverage, inclusion of unlimited quantities of offsets from Kyoto international markets and exclusion of deforestation activities. [ABSTRACT FROM AUTHOR]

One of the assumptions underlying efforts to convert cropping land, especially marginal crop land, to plantations is that there will be a net reduction in greenhouse gas emissions, with a gas “sink” replacing a high energy system in which the breakdown of biomass is routinely accelerated to prepare for new crops. This research, based on case studies in Kingaroy in southeast Queensland, compares the amount of greenhouse gas (GHGs) emissions from a peanut/maize crop rotation, a pasture system for beef production and a spotted gum (Corymbia citriodora) timber plantation. Three production inputs, fuel, farm machinery and agrochemicals (fertilizer, pesticides and herbicides) are considered. The study extends beyond the farm gate to include packing and transportation and the time period is 30 years. The results suggest that replacing the crops with plantations would indeed reduce emissions but that a pasture system would have even lower net emissions. These findings cast some doubt on the case for farm forestry as a relatively effective means of ameliorating greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

Climate change is a multifaceted problem impacting social, economic and environmental values. Strategies to reduce climate change impacts require novel and integrated solutions that simultaneously benefit multiple parts of society and minimise potential conflict between economic, food production and environmental values. Here, we use a novel integrated analysis of the energy-water-food nexus, land use, and climate change to explore whether mounting environmental pressure can be reversed without negative consequences on food production and economic outcomes. Using Australia as a test case, our results show the significant potential of optimal use of land and water resources in achieving both increased crop production and reduced greenhouse gas (GHG) emissions while sustaining economic outcomes. Our trade-off analysis shows that, at a regional level, up to 50% reduction in GHG emissions from irrigated crop production is possible without compromising total gross margins; in addition, regional optimisation of resource use resulted in surplus water and land available for environmental planting. Our analysis also indicates that further emissions reduction without trade-offs can be achieved with a higher carbon price and/or where water markets ensure higher value water use. To our knowledge, this is the first future-looking modelling to integrate this range of crop production, environmental and economic issues. This type of integrated approach has potential to better inform government emissions reduction policy aimed at finding an equitable and sustainable balance across multiple policy areas. • Develops an integrated regional water-food-GHG nexus optimisation model. • Includes systematic evaluation of externalities such as carbon and water policies. • Optimal use of land and water can increase crop production whilst reducing carbon footprints. • At a price of $30/tCO2e, ∼50% emissions reduction is possible without reducing income. • Adoption of the approach would have implications for sustainability at a range of scales. [ABSTRACT FROM AUTHOR]

The apiary industry plays a crucial role in global food production. However, many studies worldwide have never considered seasonal variation when locating suitable areas for apiaries. This study assessed the land suitability for apiaries in southern Queensland, Australia with respect to spatial and temporal variations using GIS-based fuzzy AHP and fuzzy overlay techniques. Suitability maps were generated using eleven criteria: regional ecosystems, land cover, land use, slope, aspect, elevation, distance to water, distance to roads, rainfall, temperature, and solar radiation. In spring, as revealed by fuzzy AHP, the area is largely moderately suitable (67.78%) while according to fuzzy overlay the area is mostly marginally and moderately suitable (69.44%). Almost similar trend is observed in the remaining seasons for the fuzzy AHP. Fuzzy overlay on the other hand, exhibits a constant trend of not suitable, marginally suitable and moderately suitable with almost equal percentages of around 30% during summer, autumn and winter. Fuzzy AHP, with validity ratings from 60% to 70% from all seasons, outperforms fuzzy overlay with 80% for spring but less than 60% in the other seasons.The findings can aid sustainable apiary management by mapping suitable areas for apiary sites in four different seasons. • Compare Fuzzy AHP and fuzzy overlay in suitability analysis for apiary sites. • Suitability maps based on environmental, climatic, topographic, social criteria. • Regional ecosystem map to extract floral information and inclusion of floral resource information is most important in land suitability assessment. • Application of fuzzy membership functions to input criterion in GIS environment. • Limitations associated with fuzzy AHP but more appropriate than fuzzy overlay. [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]

Environmental impact assessment (EIA) has evolved as an environmental management and sustainability tool. Despite common principles shared by EIA globally, there are considerable variations in EIA processes across countries. In this paper, we reviewed and compared EIA processes of China, Queensland State of Australia and Nepal considering five key steps (selection of consultants, report preparation, public participation, report review and approval, and monitoring and evaluations) of EIA. Our review indicated that the EIA is well recognised in legal instruments in all state and countries under consideration and there are both similarities and differences in key steps of EIA. Monitoring of EIA recommendations and the integration of feedbacks from the past and current practices are important in improving EIA processes. This study also found that there are elements for possible improvement in existing EIA processes by each state and country introducing the best practices from others' EIA system. Some of the practices that Nepal can follow from the EIA processes of Queensland and China are licensing and accreditation of individuals and firms to conduct EIA, establishment of separate monitoring unit within regulating department, development of clear guidelines for approvals and monitoring, and the use of independent third-party auditing in EIA monitoring. The findings of this paper are useful in revising and improving EIA policies, practices and processes in the selected state, countries and elsewhere.

Reducing nitrous oxide (N 2 O) emissions from agriculture soils is crucial, as it accounts for 5.6-6.8% of global anthropogenic emissions. This study aims to understand the interaction among climate, soil nitrogen (N) and applied N on N 2 O emissions from the irrigated cotton farming system and its implications on farm economics. We conducted simulations for 116 years (1900-2015) and assessed the effect of different N-fertiliser application rates, initial soil nitrate (NO 3 ) N levels and rainfall conditions on N 2 O emissions, N 2 O emission factors (EFs) and financial returns (with and without N 2 O costs). Results showed the following. 1) The proportional impact of higher N fertiliser rates on soil N 2 O emissions was greater when initial soil N level was lower (5 mg NO 3 kg -1 ) than higher (35 mg NO 3 kg -1 ). However, the volume of impact was greater under higher initial soil N levels. 2) The relationship between N fertiliser rates and the EFs (range 0.03-7.2%) was not linear but bell-shaped. 3) Fertiliser N requirements increased with rainfall and decreased with initial soil N. Accordingly, the cotton returns for the driest rainfall condition (<10th percentile) were maximum at 300, 250 and 150 kg N ha -1 for initial soil N of 5, 20 and 35 mg NO 3 kg -1 . For the wettest rainfall condition (>90th percentile), these rates were 50 kg ha -1 higher across the initial soil N conditions. Any additional application of N-fertiliser above these rates was counterproductive. 4) Inclusion of N 2 O cost into farm economics reduced the annual returns by up to $39 ha -1 , but the optimal fertiliser application rates remain the same. 5) Optimising N fertiliser rates to soil N and rainfall conditions increased the annual returns by up to $303 ha -1 , with a further increase of $15 ha -1 from fertiliser use efficiency when the Australian Government incentives under the $2.55 billion dollar Emission Reduction Fund program was considered. These findings suggest that N-fertiliser application rates and N 2 O emission mitigation strategies need further refinements specific to prevailing soil and climate variabilities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Recently, partly due to the increasing carbon consciousness in the electorates and partly due to the imminent introduction of the Australian Government's Carbon Pollution Reduction Scheme (CPRS), estimating carbon footprints is becoming increasingly necessary in agriculture. By taking data from several sources, this study estimates the national greenhouse gas (GHG) emissions from a variety of farm inputs, for the 23 key vegetables crops grown in Australia. For the 121,122 ha of land occupied by vegetable farms, there are 1.1 MtCO(2)e GHG emissions or 9.2 tCO(2)e ha(-1). In total, 65% of total GHG emissions from the vegetable industry are due to electricity use for irrigation and post-harvest on-farm activities, 17% from soil N(2)O emissions due to N fertiliser use, 10% from agrochemicals, 7% through fossils fuels and 1% from on-farm machinery. The top four vegetables (by area), potatoes, lettuce, tomatoes and broccoli account for 29.1%, 7.9%, 5.9% and 7.2% of total GHG emissions from vegetables, respectively. However, the ratio of GHG emissions between the highest and lowest-emitting crops per hectare and per tonne, are different. Therefore, care must be exercised in carbon footprint labelling vegetable products to ensure that the labels reflect carbon emissions on a per tonnage basis.