Environmental and economic evaluation of N fertilizer rates in a maize crop in Italy : a spatial and temporal analysis using crop models

Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

Agronomic and economic evaluation of irrigation strategies on cotton lint yield in Australia

Cotton is one of the most important irrigated crops in subtropical Australia. In recent years, cotton production has been severely affected by the worst drought in recorded history, with the 2007–08 growing season recording the lowest average cotton yield in 30 years. The use of a crop simulation model to simulate the long-term temporal distribution of cotton yields under different levels of irrigation and the marginal value for each unit of water applied is important in determining the economic feasibility of current irrigation practices. The objectives of this study were to: (i) evaluate the CROPGRO-Cotton simulation model for studying crop growth under deficit irrigation scenarios across ten locations in New South Wales (NSW) and Queensland (Qld); (ii) evaluate agronomic and economic responses to water inputs across the ten locations; and (iii) determine the economically optimal irrigation level. The CROPGRO-Cotton simulation model was evaluated using 2 years of experimental data collected at Kingsthorpe, Qld. The model was further evaluated using data from nine locations between northern NSW and southern Qld. Long-term simulations were based on the prevalent furrowirrigation practice of refilling the soil profile when the plant -available soil water content is<50%. The model closely estimated lint yield for all locations evaluated. Our results showed that the amounts of water needed to maximise profit and maximise yield are different, which has economic and environmental implications. Irrigation needed to maximise profits varied with both agronomic and economic factors, which can be quite variable with season and location. Therefore, better tools and information that consider the agronomic and economic implications of irrigation decisions need to be developed and made available to growers.

Adapting wheat sowing dates to projected climate change in the Australian subtropics: analysis of crop water use and yield

Projected increases in atmospheric carbon dioxide concentration ([CO2]) and air temperature associated with future climate change are expected to affect crop development, crop yield, and, consequently, global food supplies. They are also likely to change agricultural production practices, especially those related to agricultural water management and sowing date. The magnitude of these changes and their implications to local production systems are mostly unknown. The objectives of this study were to: (i) simulate the effect of projected climate change on spring wheat (Triticum aestivum L. cv. Lang) yield and water use for the subtropical environment of the Darling Downs, Queensland, Australia; and (ii) investigate the impact of changing sowing date, as an adaptation strategy to future climate change scenarios, on wheat yield and water use. The multimodel climate projections from the IPCC Coupled Model Intercomparison Project (CMIP3) for the period 2030–2070 were used in this study. Climate scenarios included combinations of four changes in air temperature (08C, 18C, 28C, and 38C), three [CO2] levels (380 ppm, 500 ppm, and 600 ppm), and three changes in rainfall (–30%, 0%, and +20%), which were superimposed on observed station data. Crop management scenarios included a combination of six sowing dates (1 May, 10 May, 20 May, 1 June, 10 June, and 20 June) and three irrigation regimes (no irrigation (NI), deficit irrigation (DI), and full irrigation (FI)). Simulations were performed with the model DSSAT4.5, using 50 years of daily weather data.Wefound that: (1) grain yield and water-use efficiency (yield/evapotranspiration) increased linearly with [CO2]; (2) increases in [CO2] had minimal impact on evapotranspiration; (3) yield increased with increasing temperature for the irrigated scenarios (DI and FI), but decreased for the NI scenario; (4) yield increased with earlier sowing dates; and (5) changes in rainfall had a small impact on yield for DI and FI, but a high impact for the NI scenario.

Nitrous oxide emissions from irrigated wheat in Australia : impact of irrigation management

Background and Aims: Irrigation management affects soil water dynamics as well as the soil microbial carbon and nitrogen turnover and potentially the biosphere-atmosphere exchange of greenhouse gasses (GHG). We present a study on the effect of three irrigation treatments on the emissions of nitrous oxide (N2O) from irrigated wheat on black vertisols in South-Eastern Queensland, Australia. Methods: Soil N2O fluxes from wheat were monitored over one season with a fully automated system that measured emissions on a sub-daily basis. Measurements were taken from 3 subplots for each treatment within a randomized split-plot design. Results: Highest N2O emissions occurred after rainfall or irrigation and the amount of irrigation water applied was found to influence the magnitude of these “emission pulses”. Daily N2O emissions varied from -0.74 to 20.46 g N2O-N ha-1 day-1 resulting in seasonal losses ranging from 0.43 to 0.75 kg N2O N ha-1 season -1 for the different irrigation treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the wheat cropping season, uncorrected for background emissions, ranged from 0.2 to 0.4% of total N applied for the different treatments. Highest seasonal N2O emissions were observed in the treatment with the highest irrigation intensity; however, the N2O intensity (N2O emission per crop yield) was highest in the treatment with the lowest irrigation intensity. Conclusions: Our data suggest that timing and amount of irrigation can effectively be used to reduce N2O losses from irrigated agricultural systems; however, in order to develop sustainable mitigation strategies the N2O intensity of a cropping system is an important concept that needs to be taken into account.

Effects of rice husk biochar and sugar-mill by-products on methane consumption from two different soils

Methane (CH4) is an important greenhouse gas with a global warming potential (GWP) 25 times greater than carbon dioxide (CO2) that can be produced or consumed in soils depending on environmental conditions and other factors. Biochar application to soils has been shown to reduce CH4 emissions and to increase CH4 consumption. However, the effects of rice husk biochar (RB) have not been thoroughly investigated. Two 60-day laboratory incubation experiments were conducted to investigate the effects of amending two soil types with RB, raw mill mud (MM) and composted mill mud (CM) on soil CH4 consumption and emissions. Soil cores incubated in 1 L glass jars and gas samples were analysed for CH4 using gas chromatography. Average CH4 consumption rates varied from -0.06 to -0.68 g CH4-C( )/ha/d in sandy loam soil and -0.59 to -1.00 g CH4-C/ha/d in clay soil. Application of RB resulted in CH4 uptake of -0.52 to -0.55 g CH4-C/ha/d in sandy loam and -0.76 to -0.91 g CH4-C/ha/d in clay soil. Addition of MM showed low CH4 emissions or consumption at 60% water-filled pore space (WFPS) in both soils. However, at high water contents (>75% WFPS) the application of MM produced high rates of CH4 emissions which were significantly suppressed when RB was added. Cumulative emissions of the MM treatment produced 108.9 g CH4-C/ha at 75% WFPS and 11 459.3 g CH4-C/ha at 90% WFPS in sandy loam soil over a period of 60 days. RB can increase CH4 uptake under low soil water content (SWC) and decrease CH4 emissions under anaerobic conditions. CM expressed more potential to reduce CH4 emissions than those of MM.

Discussion paper and working paper series : Motivations, expectations and experiences of Australian rural and regional planners

Despite playing an extremely important role in shaping communities, the role and contribution of planners is not widely understood or acknowledged. At the same time, there is a shortage of planners in Australia, especially in non-urban areas. Thus, though an online survey of 185 rural and regional planners, this research explores their motivations, expectations and experiences. Most enjoyed and felt confident in their role, explaining that they valued the relaxed family orientated rural lifestyle and the varied nature of the planning work. Although they sometimes felt isolated, the non-urban location provided quicker progression to senior roles, the ability to engage directly with the community and to see the consequences of their decisions. Only half felt their education had prepared them well for their role, citing gaps in terms of computerised modelling, team leadership and conflict resolution skills. Their feedback centred on providing a more practical course, focussing more on regional planning, and encouraging urban and rural experience placements. As the first study to quantifiably explore rural and regional Australian planners perceptions of their role and challenges, the findings illustrate current experiences, key planning challenges, perceived educational gaps and future priorities.

Predicting the retention of first-time donors using an extended Theory of Planned Behavior

BACKGROUND: Donor retention is vital to blood collection agencies. Past research has highlighted the importance of early career behavior for long-term donor retention, yet research investigating the determinants of early donor behavior is scarce. Using an extended Theory of Planned Behavior (TPB), this study sought to identify the predictors of first-time blood donors' early career retention. STUDY DESIGN AND METHODS: First-time donors (n = 256) completed three surveys on blood donation. The standard TPB predictors and self-identity as a donor were assessed 3 weeks (Time 1) and at 4 months (Time 2) after an initial donation. Path analyses examined the utility of the extended TPB to predict redonation at 4 and 8 months after initial donation. RESULTS: The extended TPB provided a good fit to the data. Post-Time 1 and 2 behavior was consistently predicted by intention to redonate. Further, intention was predicted by attitudes, perceived control, and self-identity (Times 1 and 2). Donors' intentions to redonate at Time 1 were the strongest predictor of intention to donate at Time 2, while donors' behavior at Time 1 strengthened self-identity as a blood donor at Time 2. CONCLUSION: An extended TPB framework proved efficacious in revealing the determinants of first-time donor retention in an initial 8-month period. The results suggest that collection agencies should intervene to bolster donors' attitudes, perceived control, and identity as a donor during this crucial post–first donation period.

A flexible Bayesian model for describing temporal variability of N2O emissions from an Australian pasture

Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

Influence of nitrogen fertiliser application and timing on greenhouse gas emissions from a lychee (Litchi chinensis) orchard in humid subtropical Australia

Nitrous oxide emissions from intensive, fertilised agricultural systems have been identified as significant contributors to both Australia's and the global greenhouse gas (GHG) budget. This is expected to increase as rates of agriculture intensification and land use change accelerate to support population growth and food production. Limited data exists on N2O trace gas fluxes from subtropical or tropical tree cropping soils critical for the development of effective mitigation strategies.This study aimed to quantify GHG emissions over two consecutive years (March 2007 to March 2009) from a 30 year (lychee) orchard in the humid subtropical region of Australia. GHG fluxes were measured using a combination of high temporal resolution automated sampling and manually sampled chambers. No fertiliser was added to the plots during the 2007 measurement season. A split application of nitrogen fertiliser (urea) was added at the rate of 265kgNha-1 during the autumn and spring of 2008. Emissions of N2O were influenced by rainfall events and seasonal temperatures during 2007 and the fertilisation events in 2008. Annual N2O emissions from the lychee canopy increased from 1.7kgN2O-Nha-1yr-1 for 2007, to 7.6kgN2O-Nha-1yr-1 following fertiliser application in 2008. This represented an emission factor of 1.56%, corrected for background emissions. The timing of the split application was found to be critical to N2O emissions, with over twice as much lost following an application in spring (2.44%) compared to autumn (EF: 1.10%). This research suggests that avoiding fertiliser application during the hot and moist spring/summer period can reduce N2O losses without compromising yields.

The interface of acute and aged care : the role of the nurse in a provincial area

Objective This study was to investigate issues that arose from pre-admission to post-discharge, for people in Toowoomba, Queensland over the age of 65 admitted to an acute facility. This paper concentrates on a significant concern that emerged from the large amount of data collected during this project, that is,the role of the nurse in the continuum of health care involving elderly people. Method The study involved a multi-site, multi-agency and multi-method (qualitative and quantitative) approach. Data was collected from regional service providers, the Department of Health and Aged Care (DHAC), the Australian Bureau of Statistics (ABS), Home and Community Care (HACC), the Aged Care Assessment Team (ACAT), elderly people who had been discharged from regional hospitals and their carers, residents of regional aged care facilities, area health professionals and elderly regional hospital inpatients. Results The data indicated that nurses in this provincial area currently play a limited role in preadmission planning, being mostly concerned with elective surgery, especially joint replacements. While nurses deliver the majority of care during hospitalisation, they do not appear to be cognizant of the needs of the elderly regarding post-acute discharge. Conclusion The recent introduction of the model of nurse case management in the acute sector appears to be a positive development that will streamline and optimise the health care of the elderly across the continuum in the Toowoomba area. The paper recommends some strategies, such as discharge liaison nurses based in Emergency Departments and the expansion of the nurse case management role, which would optimise care for the elderly person at the interface of care.

The threat of CHikungunya in Oceanea

The Oceania region, which includes Australia, New Zealand, Papua New Guinea and the islands of the tropical Pacific Ocean, has historically been free from chikungunya. However, the 2011 outbreak in New Caledonia and the ongoing outbreak in Papua New Guinea have highlighted the risk to other communities in Oceania where there are competent mosquito vectors and permissive social factors and environmental conditions. In this article we discuss the threat to this region that is posed by the recent evolution of the E1:A226V mutant strains of chikungunya virus (CHIKV).

The essential parameters of a resource-based carrying capacity assessment model : an Australian case study

Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Narratives of healing: a case study of a young Liberian refugee settled in Australia

The Tree of Life group program is a narrative-based expressive arts intervention, designed to target the psychological difficulties faced by young people from refugee backgrounds. This study utilised a case study methodology to investigate the experience of a single adolescent from a Liberian background resettled in Australia, who participated in a manualised version of the Tree of Life program. The case study aimed to identify the underlying therapeutic processes that enabled the participant to adopt a preferred self-narrative. The participant was observed to demonstrate positive gains as a result of program participation. Five therapeutic factors were identified as particularly salient to the program’s success: the exploration of alternative stories of self; the fostering of group cohesion; the provision of corrective emotional experiences; the experience of outsider witnesses; and the instillation of hope. These factors were discussed in relation to working with young people from refugee backgrounds. Recommendations for future implementation of the Tree of Life program are provided.

Reframing Conceptions of Contemporary Literacy Capabilities in Pre-Service Primary Teacher Education

This chapter describes the challenges of integrating new technologies with literacy education in pre-service primary teacher education in Australia. The authors describe the policy context and regulatory mechanisms controlling pre-service education, including a national set of professional standards for graduate teachers, a new national curriculum for school students, the introduction of high stakes national assessment for school students, and the looming threat of decontextualized back-to-the-basics professional entry tests for aspiring teachers. The chapter includes three case studies of the authors’ pedagogical practices that attempt to reframe conceptions of the literacy capabilities of pre-service teachers to reflect the complex and sophisticated requirements of teachers in contemporary schooling. The authors conclude the chapter with a discussion of the implications of these case studies as they illustrate the ways that pre-service teachers can be scaffolded and supported to develop creative capacity and critical awareness of the kinds of literacies required in the digital age despite restrictive regimes.