Regions Of Eastern Australia Research Articles

Tolerance of wheat cultivars to root‐lesion nematode (Pratylenchus thornei) assessed by normalised difference vegetation index is predictive of grain yield

Tolerant wheat cultivars yield well when sown in fields infested with the root‐lesion nematode Pratylenchus thornei, which is present in 67% of fields in the subtropical grain region of eastern Australia. Wheat breeding programmes require accurate phenotyping to select germplasm with superior tolerance to P. thornei. This study investigated normalised difference vegetation index (NDVI) as a phenotypic tool to predict the tolerance of wheat cultivars on low and high P. thornei population densities. Three, 2‐year field experiments used a resistant and a susceptible wheat cultivar in the first year to develop low and high P. thornei populations. In the second year, 36 wheat cultivars were sown on these plots. A NTech Greenseeker was used to determine the NDVI of each plot at regular times during the season and grain yield was measured at crop maturity. There was an inverse relationship between P. thornei population densities and the NDVI for intolerant wheat cultivars. Regression analysis showed a highly predictive response between the yield tolerance index and NDVI with R2 ranging from 0.85 (n = 36) to 0.93 (n = 36) for the three experiments. The area under the disease progress curve with respect to NDVI was highly predictive of yield tolerance (R2 = 0.92; n = 36) when there were high populations (9,091 P. thornei/kg), but not when populations were low (578 P. thornei/kg). Tolerant cultivars can be identified by NDVI when sown on soil containing high populations (>2,500 P. thornei/kg) by measurement at approximately 1,000 degree days after sowing. Greenseeker is a valuable tool for wheat breeders to select germplasm with tolerance of P. thornei.

Illawarra Born cross-generational health study: feasibility of a multi-generational birth cohort study

BackgroundThere is a strong interest in the concept of developmental origins of health and disease and their influence on various factors “from cradle to grave”. Despite the increasing appreciation of this lifelong legacy across the human life course, many gaps remain in the scientific understanding of mechanisms influencing these formative phases. Cross-generational susceptibility to health problems is emerging as a focus of research in the context of birth cohort studies.The primary aim of the Illawarra Born study is to make scientific discoveries associated with improving health and wellbeing across the lifespan, with a particular focus on preventable chronic diseases, especially mental health. This birth cohort study will follow and collect data from three cohorts representing different stages across the lifespan: infants, adults (parents) and older adults (grandparents). The multi-generational, cross-sectional and longitudinal design of this birth cohort study supports a focus on the contributions of genetics, environment and lifestyle on health and wellbeing. The feasibility of conducting a multi-generational longitudinal birth cohort project was conducted through a small pilot study.Methods/designThe purpose of this paper is to report on the feasibility and acceptability of the research protocol for a collaborative cross-generation health study in the community and test recruitment and outcome measures for the main study. This feasibility study included pregnant women who were intending to give birth in the Illawarra-Shoalhaven region in Eastern Australia. The area includes a large, regional referral hospital, with capacity to treat specialist and complex cases. Pregnant women were asked to participate in five data collection waves beginning at 22 weeks gestation and ending with a 6-month post-partum appointment. Recruitment was then extended, via the pregnant women, to also include fathers and maternal grandmothers.DiscussionThis feasibility study focused on the perinatal period and collected data across three multi-disciplinary domains including mental health, diet, exposures to toxins and the role of these in maternal and infant outcomes. Forty-one families participated in extensive data collection from 22 weeks gestation to 6-months post-partum. Factors impacting on viability and feasibility including recruitment solutions provide the basis for a large-scale study.

Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region

Accurate predictions of drought events to plan and manage the adverse effects of drought on agriculture and the environment requires tools that precisely predict standardized drought metrics. Improving on the World Meteorological Organization approved Standardized Precipitation Index (SPI), the multi-scalar Standardized Precipitation and Evapotranspiration Index (SPEI), a variant of the SPI, is a relatively recent drought index, which takes into account the impacts of temperature change on overall dryness, along with precipitation and evapotranspiration effects. In this paper, an extreme learning machine (ELM) model was applied to predict SPEI in a drought-prone region in eastern Australia, and the quality of the model's performance was compared to that of a multiple linear regression (MLR), an artificial neural network (ANN), and a least support vector regression (LSSVR) model. The SPEI data were derived from climatic variables recorded at six weather stations between January 1915 and December 2012. Model performance was evaluated by means of the normalized root mean square error (NRMSE), normalized mean absolute error (NMAE), coefficients of determination (r2), and the Nash-Sutcliffe efficiency coefficient (NASH) in the testing period. Results showed that the ELM and ANN models outperformed the MLR and LSSVR models, and all four models revealed a greater predictive accuracy for the 12-month compared to the 3-month SPEI predictions. For the 12-month SPEI predictions, optimal models had r2 that ranged from 0.668 for the LSSVR model (Station 6) to 0.894 for the ANN model (Station 4). The good agreement between observed and predicted SPEI at different locations within the study region indicated the potential of the developed models to contribute to a more thorough understanding of potential future drought-risks in eastern Australia, and their applicability to drought assessments over multiple timescales. The models and findings have useful implications for water resources assessment in drought-prone regions.

Stochastic Modeling of Groundwater Extractions over a Data-Sparse Region of Australia.

Setting limit on groundwater extractions is important to ensure sustainable groundwater management. Lack of extraction data can affect interpretations of historical pressure changes, predictions of future impacts, accuracy of groundwater model calibration, and identification of sustainable management options. Yet, many groundwater extractions are unmetered. Therefore, there is a need for models that estimate extraction rates and quantify model outputs uncertainties arising due to a lack of data. This paper develops such a model within the Generalized Linear Modeling (GLM) framework, using a case study of stock and domestic (SD) extractions in the Surat Cumulative Management Area, a predominantly cattle farming region in eastern Australia. Various types of extraction observations were used, ranging from metering to analytically-derived estimates. GLMs were developed and applied to estimate the property-level extraction amounts, where observation types were weighted by perceived relative accuracy, and well usage status. The primary variables found to affect property-level extraction rates were: yearly average temperature and rainfall, pasture, property area, and number of active wells; while variables most affecting well usage were well water electrical conductivity, spatial coordinates, and well age. Results were compared with analytical estimates of property-level extraction, illustrating uncertainties and potential biases across 20 hydrogeological units. Spatial patterns of mean extraction rates (and standard deviations) are presented. It is concluded that GLMs are well suited to the problem of extraction rate estimation and uncertainty analysis, and are ideal when model verification is supported by measurement of a random sample of properties.

Climate affects fish-kill events in subtropical estuaries of eastern Australia

Fish kills following austral summer flood events (November–March) occur episodically in estuarine channels in Australia. We examined the climatic conditions associated with the historic record of such events in a subtropical region in eastern Australia to determine the effect of antecedent weather conditions on the probability of post-flood fish-kill events. Records, including regional county council logs, newspapers and New South Wales Fisheries annual reports, were analysed for reports of floods and fish kills following these events. Daily rainfall patterns preceding floods with fish-kill events tended to be drier than rainfall patterns preceding floods when a fish kill did not occur. Based on these observations, it is proposed that estuarine hypoxia resulting in a fish kill is increased by prolonged dry periods followed by rapid and intensive rainfall preceding the flood peak. This is most likely due to (i) accumulation of organic material on the floodplain due to vegetation stress and reduced decomposition processes in drier conditions; (ii) upstream migration of the salt wedge, allowing some estuarine fish species to maintain an optimum environment, followed by flooding with (iii) rapid consumption of dissolved oxygen during decomposition of accumulated organic material sourced from senescent vegetation; and (iv) fish becoming trapped upstream in discharging hypoxic floodwater during the flood recession phase.

Elevated temperature reduces survival of peak populations of root-lesion nematodes (Pratylenchus thornei) after wheat growth in a vertisol

Elevated temperature was investigated to understand why there is a faster decline in Pratylenchus thornei population abundances in the topsoil than in deeper layers of vertisols after wheat matures in the subtropical grain region of eastern Australia. Soil containing a large population abundance of P. thornei (after wheat growth) was incubated in a replicated experiment for various periods up to 16 weeks at eight temperatures ranging from 10 to 45 °C in 5 °C intervals, with three moisture treatments, namely (a) field capacity maintained during incubation, (b) field capacity allowed to dry during incubation and (c) air-dried before incubation. After incubation, live nematodes were extracted from the soil samples by the Whitehead tray method for 2 and 7 days and P. thornei was counted in four life-stage categories. Temperatures ≥ 35 °C resulted in rapid death of P. thornei independent of any effects due to soil desiccation. At lower temperatures, survival over a 16-week period was better in soil maintained at field capacity than in soil allowed to dry. Death of P. thornei in soil that was air-dried before incubation was rapid during incubation at all temperatures tested. Elevated temperature of itself plus faster soil desiccation with increasing temperature are the likely causes of the faster decline in P. thornei population abundances in the topsoil than in the subsoil. These effects can contribute to soil profile distributions of P. thornei recorded in some fields in this subtropical grain region after clean fallow periods where greater population abundances of P. thornei occur in the subsoil layers than in the topsoil.

Effects of Sorghum Malting on Colour, Major Classes of Phenolics and Individual Anthocyanins.

Sorghum (Sorghum bicolor) grain contains many health-promoting phytochemicals, including a broad range of phenolic compounds. Malting of cereal grains is known to increase the bioavailability of macro- and micronutrients. However, the detailed effects of malting on sorghum grain anthocyanins, a major class of phenolics that influence the taste and colour of sorghum-based foods, requires further investigation. Eight commercial sorghum hybrids harvested from three regions in eastern Australia were malted and analysed for colour, tannin content, total phenolic content (TPC), flavan-4-ols, total flavonoids, total anthocyanins and 3-deoxyanthocyanins. Grains of all the sorghums were found to be tannin-free. Malting decreased the TPC of all samples. For TPC, the grand means among all the sorghum cultivars for raw and malted grain were 2.77 and 2.48 mg gallic acid equivalents (GAE)/g, respectively. For flavan-4-ols, the grand means for raw and malted sorghum grains were 2.98 and 2.23 abs/mL/g, respectively. Remarkably, total anthocyanin levels more than doubled upon malting whereas total flavonoid levels decreased by 12%. The average abundance of 3-deoxyanthocyanins in raw sorghum grains increased for about 8-fold upon malting. Our results will be valuable for sorghum breeders in the selection of lines for specific end uses and for food scientists developing sorghum-based products.

Predicting the slow decline of root lesion nematodes (Pratylenchus thornei) during host-free fallows to improve farm management decisions

Abstract Pratylenchus thornei is a major pathogen of cereal and legume crops around the world, especially in the northern grains region of eastern Australia. The dominance of host species within the rotation has seen soil pathogen population densities increase. Long weed-free fallows combined with sorghum production (non host crop) to reduce population densities has been successful. However, little is known about the rate of population decline during the fallow or how long this non–host period should continue in order to reduce the population below an accepted damage threshold. The rate of decline from a range of initial starting populations (high, medium, low and very low) were monitored over a 30 month weed free fallow. Fallows were initiated in November (late Spring) for three consecutive years. Nematode population densities and soil moisture were measured at eight depths down the soil profile to 1.5 m and used to describe the rate of population decline over time in each soil layer. Dynamic populations of P. thornei existed within the upper layers (

Fusarium species associated with stalk rot and head blight of grain sorghum in Queensland and New South Wales, Australia

Historical records report Fusarium moniliforme sensu lato as the pathogen responsible for Fusarium diseases of sorghum; however, recent phylogenetic analysis has separated this complex into more than 25 species. During this study, surveys were undertaken in three major sorghum‐producing regions in eastern Australia to assess the diversity and frequency of Fusarium species associated with stalk rot‐ and head blight‐infected plants. A total of 523 isolates were collected from northern New South Wales, southern Queensland and central Queensland. Nine Fusarium species were isolated from diseased plants. Pathogenicity tests confirmed F. andiyazi and F. thapsinum were the dominant stalk rot pathogens, whilst F. thapsinum and species within the F. incarnatum–F. equiseti species complex were most frequently associated with head blight.

Broad-scale suppression of cotton bollworm, Helicoverpa armigera (Lepidoptera: Noctuidae), associated with Bt cotton crops in Northern New South Wales, Australia.

The cotton bollworm, Helicoverpa armigera, is a major pest of many agricultural crops in several countries, including Australia. Transgenic cotton, expressing a single Bt toxin, was first used in the 1990s to control H. armigera and other lepidopteran pests. Landscape scale or greater pest suppression has been reported in some countries using this technology. However, a long-term, broad-scale pheromone trapping program for H. armigera in a mixed cropping region in eastern Australia caught more moths during the deployment of single Bt toxin cotton (Ingard®) (1996-2004) than in previous years. This response can be attributed, at least in part, to (1) a precautionary cap (30% of total cotton grown, by area) being applied to Ingard® to restrict the development of Bt resistance in the pest, and (2) during the Ingard® era, cotton production greatly increased (as did that of another host plant, sorghum) and H. armigera (in particular the 3rd and older generations) responded in concert with this increase in host plant availability. However, with the replacement of Ingard® with Bollgard II® cotton (containing two different Bt toxins) in 2005, and recovery of the cotton industry from prevailing drought, H. armigera failed to track increased host-plant supply and moth numbers decreased. Greater toxicity of the two gene product, introduction of no cap on Bt cotton proportion, and an increase in natural enemy abundance are suggested as the most likely mechanisms responsible for the suppression observed.

Survival of root-lesion nematodes (Pratylenchus thornei) after wheat growth in a vertisol is influenced by rate of progressive soil desiccation

The root-lesion nematode (Pratylenchus thornei) is a major pathogen of wheat in the subtropical grain region of eastern Australia. Experiments were conducted to learn whether soil desiccation can account for the rapid fall in peak P. thornei population densities noted in the field after wheat matures. The decline in population densities of P. thornei after growth of wheat was measured on progressive desiccation of soil with roots by fast and slow drying methods. The vertisolic soil of initial moisture content 45% w/w (or matric potential of pF 3.3) was dried in 5% decrements to an air-dried gravimetric moisture content of 15% (pF 5.6) taking 10.7 h for fast drying and 91.5 h for slow drying. After drying, live nematodes were extracted with Whitehead trays for 2 and 7 days and counted in four life stages (adults and juvenile stages J2, J3 and J4). Fast drying resulted in a sigmoidal decline in total P. thornei with only 5% of the population alive in soil at 15% moisture content, but slow drying had no significant effect on the population density. The percentage of nematodes extracted at 2 days compared with the total extracted over 7 days in undried soil (∼89% of total) declined quadratically on desiccation to be 48% (fast drying) and 78% (slow drying) at 15% moisture content. With fast drying, the proportion of adults and J2 decreased whereas the proportion of J4 increased as the soil dried. With slow drying, the proportion of J2 and J3 stages decreased while the proportion of J4 increased. Thus the J4 or pre-adult was the life stage most tolerant of soil desiccation. Time is required for P. thornei to go into a state of anhydrobiosis as a soil dries and this information can be used to model P. thornei survival in the field based on environmental parameters.

Monthly rainfall forecasting using neural networks for sugarcane regions in Eastern Australia

Sugarcane is an important agricultural crop grown on the east coast of Australia. The timing and amount of rainfall is critical in determining both the yield of sugar and scheduling of harvesting operations. Rainfall forecasts issued through the Australian Bureau of Meteorology are based on general circulation models (GCMs) and have a poor skill levels. They are also limited in utility to end-users such as farmers as they cover very broad geographical areas and are only issued as probabilities above or below median. This paper presents an alternative approach for forecasting monthly rainfall with up to 12 month lead-time based on machine learning, in particular neural networks. Monthly rainfall forecasts have been developed for the eight locations in Eastern Australia at 3 and 12 month lead-time. The accuracy of the forecasts has been assessed relative to a skill scale with 0% representing climatology (the long term average) and 100% representing a perfect forecast (observation). On this scale, neural network forecasts are typically in the range 39.9–68% for all months using a single month optimization. This compares very favorably with forecasts using GCM from the Bureau that have skill levels only in the range −20% to 20%.

Pigeon pea refuge crops are likely to provide patchy delivery of Helicoverpa (Lepidoptera: Noctuidae) within Bt cotton production regions in eastern Australia

AbstractRefuge crops, in particular pigeon pea and conventional (non‐Bt) cotton, are mandatory components within the Bt resistance management strategy for Helicoverpa pests in Bt cotton production systems in eastern Australia. These refuge crops are expected to produce large numbers of Bt‐susceptible moths, some of which will mate with the relatively few resistant moths emerging from Bt cotton, thus reducing the likelihood of Bt resistance developing. The spatial and temporal variability in Helicoverpa production in pigeon pea refuge crops within the St George Irrigation Area in southern Queensland was measured in this study, and the likely dispersal of moths produced in such refuges to Bt cotton crops throughout the local landscape was modelled. The attractiveness of pigeon pea for Helicoverpa oviposition and the resultant abundance of eggs on plants and pupae in the soil were highly variable between refuge crops within and between seasons. A simulation model was developed to explore the effects of random and wind‐biased assumptions on moth movements within the landscape. The model was initialised using data on the abundance of either live pupae or remains of pupal cases in the soil as surrogates for moth production within refuges. The results of the model suggested that delivery of moths from refuges to Bt cotton crops throughout the St George landscape would be patchy, with some areas thus more likely to be exposed to the threat of Bt resistance development than others. A reduction in refuge area requirements, such as recently proposed as a change to the Bt resistance management guidelines, appears likely to exacerbate such risk.

Nitrous oxide emissions from grain production systems across a wide range of environmental conditions in eastern Australia

Nitrous oxide (N2O) emissions from Australian grain cropping systems are highly variable due to the large variations in soil and climate conditions and management practices under which crops are grown. Agricultural soils contribute 55% of national N2O emissions, and therefore mitigation of these emissions is important. In the present study, we explored N2O emissions, yield and emissions intensity in a range of management practices in grain crops across eastern Australia with the Agricultural Production Systems sIMulator (APSIM). The model was initially evaluated against experiments conducted at six field sites across major grain-growing regions in eastern Australia. Measured yields for all crops used in the experiments (wheat, barley, sorghum, maize, cotton, canola and chickpea) and seasonal N2O emissions were satisfactorily predicted with R2=0.93 and R2=0.91 respectively. As expected, N2O emissions and emissions intensity increased with increasing nitrogen (N) fertiliser input, whereas crop yields increased until a yield plateau was reached at a site- and crop-specific N rate. The mitigation potential of splitting N fertiliser application depended on the climate conditions and was found to be relevant only in the southern grain-growing region, where most rainfall occurs during the cropping season. Growing grain legumes in rotation with cereal crops has great potential to reduce mineral N fertiliser requirements and so N2O emissions. In general, N management strategies that maximise yields and increase N use efficiency showed the greatest promise for N2O mitigation.

Benchmarking nitrous oxide emissions in deciduous tree cropping systems

Nitrous oxide (N2O) emissions contribute 6% of the global warming effect and are derived from the activity of soil-based microorganisms involved in nitrification and denitrification processes. There is a paucity of greenhouse gas emissions data for Australia’s horticulture industry. In this study we investigated N2O flux from two deciduous fruit tree crops, apples and cherries, in two predominant growing regions in eastern Australia, the Huon Valley in southern Tasmania (Lucaston – apples and Lower Longley – cherries), and high altitude northern New South Wales (Orange – apples and Young – cherries). Estimated from manual chamber measurements over a 12-month period, average daily emissions were very low ranging from 0.78gN2O-Nha–1day–1 in the apple orchard at Lucaston to 1.86gN2O-Nha–1day–1 in the cherry orchard in Lower Longley. Daily emissions were up to 50% higher in summer (maximum 5.27gN2O-Nha–1day–1 at Lower Longley) than winter (maximum 2.47gN2O-Nha–1day–1 at Young) across the four trial orchards. N2O emissions were ~40% greater in the inter-row than the tree line for each orchard. Daily flux rates were used as a loss estimate for annual emissions, which ranged from 298gN2O-Nha–1year–1 at Lucaston to 736gN2O-Nha–1year–1 at Lower Longley. Emissions were poorly correlated with soil temperature, volumetric water content, water filled porosity, gravimetric water content and matric potential – with inconsistent patterns between sites, within the tree line and inter-row and between seasons. Stepwise linear regression models for the Lucaston site accounted for less than 10% of the variance in N2O emissions, for which soil temperature was the strongest predictor. N2O emissions in deciduous tree crops were among the lowest recorded for Australian agriculture, most likely due to low rates of N fertiliser, cool temperate growing conditions and highly efficient drip irrigation systems. We recommend that optimising nutrient use efficiency with improved drainage and a reduction in soil compaction in the inter-row will facilitate further mitigation of N2O emissions.

Modelling population densities of root-lesion nematode (Pratylenchus thornei) from soil profile temperatures to choose an optimum sowing date for wheat in a subtropical region

The root-lesion nematode Pratylenchus thornei is widely distributed in many wheat growing countries and is particularly damaging to wheat in subtropical environments. This study aimed to investigate by simulation the effects of soil profile temperatures after different sowing dates on reproduction of P. thornei in susceptible and moderately resistant wheat cultivars in the subtropical grain region of eastern Australia. A quadratic regression model relating P. thornei population densities to thermal time was produced from experimental data for susceptible, intolerant wheat cv. Gatcher and moderately resistant, tolerant wheat cv. GS50a, and applied to soil profile temperatures after four sowing dates from 25 April to 24 July. Simulated final population densities of P. thornei throughout the soil profile to 60cm depth were least at 18 weeks after 25 May sowing. For Gatcher and GS50a, respectively, there were 5.7 and 3.5 times as many nematodes after 24 July sowing as after 25 May sowing, 2.0 and 1.6 after 24 June, and 1.4 and 1.3 after 25 April sowings. GS50a had 78% (May) to 86% (July) fewer nematodes in the soil profile than Gatcher. These simulations indicated that an optimum sowing date can be chosen to limit P. thornei reproduction in both susceptible and moderately resistant wheat cultivars. Gatcher had a 61% increase in measured grain yield and GS50a had an 8% increase from sowing in late May rather than in the third week of June. Sowing wheat at an optimum time in subtropical grain regions to ensure roots grow in cool soil can be a useful component of integrated management by reducing the rate of P. thornei reproduction and increasing grain yield.

Environmental impacts and resource use of Australian beef and lamb exported to the USA determined using life cycle assessment

Australia is one of the two largest exporting nations for beef and lamb in the world and the USA is a major export market for both products. To inform the Australian red meat industry regarding the environmental performance of exported food products, this study conducted the first multi-impact analysis of Australian red meat export supply chains including all stages through to warehousing in the USA. A large, integrated dataset based on case study farms and regional survey was used to model beef and lamb from major representative production regions in eastern Australia. Per kilogram of retail-ready red meat, fresh water consumption ranged from 441.7 to 597.6 L across the production systems, stress-weighted water use from 108.5 to 169.4 L H2O-e, fossil energy from 28.1 to 46.6 MJ, crop land occupation from 2.5 to 29.9 m2 and human edible protein conversion efficiency ranged from 7.9 to 0.3, with major differences observed between grass finished and grain finished production. GHG emissions excluding land use and direct land use change ranged from 16.1 to 27.2 kg CO2-e per kilogram, and removals and emissions from land use and direct land use change ranged from −2.4 to 8.7 kg CO2-e per kilogram of retail retail ready meat.Process based life cycle assessment shows that environmental impacts and resource use were highest in the farm and feedlot phase. Transportation contributed ≤5% of greenhouse gas emissions, water and land, confirming that food miles is not a suitable indicator of environmental impacts for red meat transported by ocean shipping. The contribution of international transportation to total energy demand was higher, ranging from 14 to 23%. These beef and lamb supply chains were found to rely on small volumes of water from stressed water catchments, and occupied only small amounts of crop land suited to other food production systems. Production of high quality protein foods for human consumption used only small amounts of protein from human edible grain.

Determinants of business engagement with regional sport events

Research question: Small-scale sports events provide commercial opportunities for regional communities, and yet research suggests that local commercial organisations are sometimes reticent to engage with sport event organisations to leverage benefits. This paper examines variation in business engagement with sport events and identifies determinants to sport event leverage that are previously unrecognised in the academic literature.Research methods: Using a multiple case study approach in three regions of eastern Australia, this research examines reactions to a sport event within each respective host business community. The multiple cases allow comparison of results across regions, using a mixed method strategy of personal interviews, observation and document analysis.Results and findings: The main findings reveal six key determinants of organisational engagement with regional sport events being: event cooperation, tourism dependency, business size, promotional strategy, strategic direction and skills and knowledge. These key determinants are explored to create a framework for future research in this area, and further contribute to the field of sport leverage research, with particular importance to sport events.Implications: The barriers to the development of strategies to maximise event leverage are identified and discussed, and in so doing implications for improving business relationships with sport events are explored. These implications are relevant to managing impacts upon businesses, visitors, and event and regional destinations.

A life cycle assessment approach to quantifying greenhouse gas emissions from land-use change for beef production in eastern Australia

In life cycle assessment studies, greenhouse gas (GHG) emissions from direct land-use change have been estimated to make a significant contribution to the global warming potential of agricultural products. However, these estimates have a high uncertainty due to the complexity of data requirements and difficulty in attribution of land-use change. This paper presents estimates of GHG emissions from direct land-use change from native woodland to grazing land for two beef production regions in eastern Australia, which were the subject of a multi-impact life cycle assessment study for premium beef production. Spatially- and temporally consistent datasets were derived for areas of forest cover and biomass carbon stocks using published remotely sensed tree-cover data and regionally applicable allometric equations consistent with Australia’s national GHG inventory report. Standard life cycle assessment methodology was used to estimate GHG emissions and removals from direct land-use change attributed to beef production. For the northern-central New South Wales region of Australia estimates ranged from a net emission of 0.03 t CO2-e ha–1 year–1 to net removal of 0.12 t CO2-e ha–1 year–1 using low and high scenarios, respectively, for sequestration in regrowing forests. For the same period (1990–2010), the study region in southern-central Queensland was estimated to have net emissions from land-use change in the range of 0.45–0.25 t CO2-e ha–1 year–1. The difference between regions reflects continuation of higher rates of deforestation in Queensland until strict regulation in 2006 whereas native vegetation protection laws were introduced earlier in New South Wales. On the basis of liveweight produced at the farm-gate, emissions from direct land-use change for 1990–2010 were comparable in magnitude to those from other on-farm sources, which were dominated by enteric methane. However, calculation of land-use change impacts for the Queensland region for a period starting 2006, gave a range from net emissions of 0.11 t CO2-e ha–1 year–1 to net removals of 0.07 t CO2-e ha–1 year–1. This study demonstrated a method for deriving spatially- and temporally consistent datasets to improve estimates for direct land-use change impacts in life cycle assessment. It identified areas of uncertainty, including rates of sequestration in woody regrowth and impacts of land-use change on soil carbon stocks in grazed woodlands, but also showed the potential for direct land-use change to represent a net sink for GHG.

Changes in Allometric Attributes and Biomass of Forests and Woodlands across an Altitudinal and Rainfall Gradient: What Are the Implications of Increasing Seasonality due to Anthropogenic Climate Change?

Canonical correspondence analysis and linear regressions were used to relate height, diameter, and dispersion measurements of 36,380 stems from 197 species recorded in 2,341 plots against both climatic and landscape variables. Above ground biomass increased in wetter and cooler locations that ameliorate the seasonal rainfall deficits. Taller and greater diameter trees with lower wood densities occur at higher altitudes. Differences between locations are based on a change in the composition of species rather than a change in the allometric properties within a species. The results support the hydraulic limitation and species packing hypotheses. These interrelationships may be affected by the interactions of fire frequency and drought which are a common feature of much of the study area. Under current climate change scenarios it is likely that there will be a reduction in above ground biomass, the number of stems per hectare, average height, average diameter, and basal area due to increasing seasonality of rainfall, temperatures, and the intensity and frequency of fires. The largest of trees are likely to be removed early due to their inability to cope with increased drought stress. The results suggest a marked reduction in carbon storage will occur across the study region in eastern Australia.