Volcanic stratigraphy, alteration zoning, and vein paragenesis of the Sascha-Pelligrini low-sulphidation epithermal system, Santa Cruz, Argentina

The Sascha-Pelligrini low-sulphidation epithermal system is located on the western edge of the Deseado Massif, Santa Cruz Province, Argentina. Outcrop sampling has returned values of up to 160g/t gold and 796g/t silver, with Mirasol Resources and Coeur D.Alene Mines currently exploring the property. Detailed mapping of the volcanic stratigraphy has defined three units that comprise the middle Jurassic Chon Aike Formation and two units that comprise the upper Jurassic La Matilde Formation. The Chon Aike Formation consists of rhyodacite ignimbrites and tuffs, with the La Matilde Formation including rhyolite ash and lithic tuffs. The volcanic sequence is intruded by a large flow-banded rhyolite dome, with small, spatially restricted granodiorite dykes and sills cropping out across the study area. ASTER multispectral mineral mapping, combined with PIMA (Portable Infrared Mineral Analyser) and XRD (X-ray diffraction) analysis defines an alteration pattern that zones from laumontite-montmorillonite, to illite-pyritechlorite, followed by a quartz-illite-smectite-pyrite-adularia vein selvage. Supergene kaolinite and steam-heated acid-sulphate kaolinite-alunite-opal alteration horizons crop out along the Sascha Vein trend and Pelligrini respectively. Paragenetically, epithermal veining varies from chalcedonic to saccharoidal with minor bladed textures, colloform/crustiform-banded with visible electrum and acanthite, crustiform-banded grey chalcedonic to jasperoidal with fine pyrite, and crystalline comb quartz. Geothermometry of mineralised veins constrains formation temperatures from 174.8 to 205.1¡ÆC and correlates with the stability field for the interstratified illite-smectite vein selvage. Vein morphology, mineralogy and associated alteration are controlled by host rock rheology, permeability, and depth of the palaeo-water table. Mineralisation within ginguro banded veins resulted from fluctuating fluid pH associated with selenide-rich magmatic pulses, pressure release boiling and wall-rock silicate buffering. The study of the Sascha-Pelligrini epithermal system will form the basis for a deposit-specific model helping to clarify the current understanding of epithermal deposits, and may serve as a template for exploration of similar epithermal deposits throughout Santa Cruz.

Genetic Diversity of Rice Tungro Spherical Virus in Tungro-Endemic Provinces of the Philippines and Indonesia

The two adjacent genes of coat protein 1 and 2 of rice tungro spherical virus (RTSV) were amplified from total RNA extracts of serologically indistinguishable field isolates from the Philippines and Indonesia, using reverse transcriptase polymerase chain reaction (RT-PCR). Digestion with HindIII and BstYI restriction endonucleases differentiated the amplified DNA products into eight distinct coat protein genotypes. These genotypes were then used as indicators of virus diversity in the field. Inter- and intra-site diversities were determined over three cropping seasons. At each of the sites surveyed, one or two main genotypes prevailed together with other related minor or mixed genotypes that did not replace the main genotype over the sampling time. The cluster of genotypes found at the Philippines sites was significantly different from the one at the Indonesia sites, suggesting geographic isolation for virus populations. Phylogenetic studies based on the nucleotide sequences of 38 selected isolates confirm the spatial distribution of RTSV virus populations but show that gene flow may occur between populations. Under the present conditions, rice varieties do not seem to exert selective pressure on the virus populations. Based on the selective constraints in the coat protein amino acid sequences and the virus genetic composition per site, a negative selection model followed by random-sampling events due to vector transmissions is proposed to explain the inter-site diversity observed

Networks cities and ecological habitats

As the world’s rural populations continue to migrate from farmland to sprawling cities, transport networks form an impenetrable maze within which monocultures of urban form erupt from the spaces in‐between. These urban monocultures are as problematic to human activity in cities as cropping monocultures are to ecosystems in regional landscapes. In China, the speed of urbanisation is exacerbating the production of mono‐functional private and public spaces. Edges are tightly controlled. Barriers and management practices at these boundaries are discouraging the formation of new synergistic relationships, critical in the long‐term stability of ecosystems that host urban habitats. Some urban planners, engineers, urban designers, architects and landscape architects have recognised these shortcomings in contemporary Chinese cities. The ideology of sustainability, while critically debated, is bringing together thinking people in these and other professions under the umbrella of an ecological ethic. This essay aims to apply landscape ecology theory, a conceptual framework used by many professionals involved in land development processes, to a concept being developed by BAU International called Networks Cities: a city with its various land uses arranged in nets of continuity, adjacency, and superposition. It will consider six lesser‐known concepts in relation to creating enhanced human activity along (un)structured edges between proposed nets and suggest new frontiers that might be challenged in an eco‐city. Ecological theory suggests that sustaining biodiversity in regions and landscapes depends on habitat distribution patterns. Flora and fauna biologists have long studied edge habitats and have been confounded by the paradox that maximising the breadth of edges is detrimental to specialist species but favourable to generalist species. Generalist species of plants and animals tolerate frequent change in the landscape, frequenting two or more habitats for their survival. Specialist species are less tolerant of change, having specific habitat requirements during their life cycle. Protecting species richness then may be at odds with increasing mixed habitats or mixed‐use zones that are dynamic places where diverse activities occur. Forman (1995) in his book Land Mosaics however argues that these two objectives of land use management are entirely compatible. He postulates that an edge may be comprised of many small patches, corridors or convoluting boundaries of large patches. Many ecocentrists now consider humans to be just another species inhabiting the ecological environments of our cities. Hence habitat distribution theory may be useful in planning and designing better human habitats in a rapidly urbanising context like China. In less‐constructed environments, boundaries and edges provide important opportunities for the movement of multi‐habitat species into, along and from adjacent land use areas. For instance, invasive plants may escape into a national park from domestic gardens while wildlife may forage on garden plants in adjoining residential areas. It is at these interfaces that human interactions too flow backward and forward between land types. Spray applications of substances by farmers on cropland may disturb neighbouring homeowners while suburban residents may help themselves to farm produce on neighbouring orchards. Edge environments are some of the most dynamic and contested spaces in the landscape. Since most of us require access to at least two or three habitats diurnally, weekly, monthly or seasonally, their proximity to each other becomes critical in our attempts to improve the sustainability of our cities.

Diversity management for innovation in social enterprises in the UK

This paper examines the linkages between diversity management (DM), innovation and high performance in social enterprises. These linkages are explicated beyond traditional framing of DM limited to workforce composition, to include discussions of innovation through networked diversity practices; reconciliation; and funding options. The paper draws upon a UK-based national survey and the case study data. Multiple data collection methods were used, including semi-structured interviews, questionnaires and workshops with participant observation. NVivo and SPSS software packages were utilized in order to analyse the qualitative and quantitative data, respectively. We used thematic coding and cropping techniques in analysing the case studies in the paper. A broad range of conflicting and supporting literature was enfolded into the conversations and discussion. The paper demonstrates that social enterprises exhibit unique characteristics in terms of size and location, as well as their double remit to add value both economically and socially. As a conclusion, we argue for social enterprises to consider options for DM in the interests of maximization of innovation and business performance. We contend that further research is needed to describe how social entrepreneurs draw upon their various ‘diversity resources’ in the process of innovation

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Comparison of three-dimensional profiles over time

In this paper, we describe an analysis for data collected on a three-dimensional spatial lattice with treatments applied at the horizontal lattice points. Spatial correlation is accounted for using a conditional autoregressive model. Observations are defined as neighbours only if they are at the same depth. This allows the corresponding variance components to vary by depth. We use the Markov chain Monte Carlo method with block updating, together with Krylov subspace methods, for efficient estimation of the model. The method is applicable to both regular and irregular horizontal lattices and hence to data collected at any set of horizontal sites for a set of depths or heights, for example, water column or soil profile data. The model for the three-dimensional data is applied to agricultural trial data for five separate days taken roughly six months apart in order to determine possible relationships over time. The purpose of the trial is to determine a form of cropping that leads to less moist soils in the root zone and beyond.We estimate moisture for each date, depth and treatment accounting for spatial correlation and determine relationships of these and other parameters over time.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Defining the role of phytoene synthase in carotenoid accumulation of high provitamin A bananas

Vitamin A deficiency (VAD) is a serious problem in developing countries, affecting approximately 127 million children of preschool age and 7.2 million pregnant women each year. However, this deficiency is readily treated and prevented through adequate nutrition. This can potentially be achieved through genetically engineered biofortification of staple food crops to enhance provitamin A (pVA) carotenoid content. Bananas are the fourth most important food crop with an annual production of 100 million tonnes and are widely consumed in areas affected by VAD. However, the fruit pVA content of most widely consumed banana cultivars is low (~ 0.2 to 0.5 ìg/g dry weight). This includes cultivars such as the East African highland banana (EAHB), the staple crop in countries such as Uganda, where annual banana consumption is approximately 250 kg per person. This fact, in addition to the agronomic properties of staple banana cultivars such as vegetative reproduction and continuous cropping, make bananas an ideal target for pVA enhancement through genetic engineering. Interestingly, there are banana varieties known with high fruit pVA content (up to 27.8 ìg/g dry weight), although they are not widely consumed due to factors such as cultural preference and availability. The genes involved in carotenoid accumulation during banana fruit ripening have not been well studied and an understanding of the molecular basis for the differential capacity of bananas to accumulate carotenoids may impact on the effective production of genetically engineered high pVA bananas. The production of phytoene by the enzyme phytoene synthase (PSY) has been shown to be an important rate limiting determinant of pVA accumulation in crop systems such as maize and rice. Manipulation of this gene in rice has been used successfully to produce Golden Rice, which exhibits higher seed endosperm pVA levels than wild type plants. Therefore, it was hypothesised that differences between high and low pVA accumulating bananas could be due either to differences in PSY enzyme activity or factors regulating the expression of the psy gene. Therefore, the aim of this thesis was to investigate the role of PSY in accumulation of pVA in banana fruit of representative high (Asupina) and low (Cavendish) pVA banana cultivars by comparing the nucleic acid and encoded amino acid sequences of the banana psy genes, in vivo enzyme activity of PSY in rice callus and expression of PSY through analysis of promoter activity and mRNA levels. Initially, partial sequences of the psy coding region from five banana cultivars were obtained using reverse transcriptase (RT)-PCR with degenerate primers designed to conserved amino acids in the coding region of available psy sequences from other plants. Based on phylogenetic analysis and comparison to maize psy sequences, it was found that in banana, psy occurs as a gene family of at least three members (psy1, psy2a and psy2b). Subsequent analysis of the complete coding regions of these genes from Asupina and Cavendish suggested that they were all capable of producing functional proteins due to high conservation in the catalytic domain. However, inability to obtain the complete mRNA sequences of Cavendish psy2a, and isolation of two non-functional Cavendish psy2a coding region variants, suggested that psy2a expression may be impaired in Cavendish. Sequence analysis indicated that these Cavendish psy2a coding region variants may have resulted from alternate splicing. Evidence of alternate splicing was also observed in one Asupina psy1 coding region variant, which was predicted to produce a functional PSY1 isoform. The complete mRNA sequence of the psy2b coding regions could not be isolated from either cultivar. Interestingly, psy1 was cloned predominantly from leaf while psy2 was obtained preferentially from fruit, suggesting some level of tissue-specific expression. The Asupina and Cavendish psy1 and psy2a coding regions were subsequently expressed in rice callus and the activity of the enzymes compared in vivo through visual observation and quantitative measurement of carotenoid accumulation. The maize B73 psy1 coding region was included as a positive control. After several weeks on selection, regenerating calli showed a range of colours from white to dark orange representing various levels of carotenoid accumulation. These results confirmed that the banana psy coding regions were all capable of producing functional enzymes. No statistically significant differences in levels of activity were observed between banana PSYs, suggesting that differences in PSY activity were not responsible for differences in the fruit pVA content of Asupina and Cavendish. The psy1 and psy2a promoter sequences were isolated from Asupina and Cavendish gDNA using a PCR-based genome walking strategy. Interestingly, three Cavendish psy2a promoter clones of different sizes, representing possible allelic variants, were identified while only single promoter sequences were obtained for the other Asupina and Cavendish psy genes. Bioinformatic analysis of these sequences identified motifs that were previously characterised in the Arabidopsis psy promoter. Notably, an ATCTA motif associated with basal expression in Arabidopsis was identified in all promoters with the exception of two of the Cavendish psy2a promoter clones (Cpsy2apr2 and Cpsy2apr3). G1 and G2 motifs, linked to light-regulated responses in Arabidopsis, appeared to be differentially distributed between psy1 and psy2a promoters. In the untranscribed regulatory regions, the G1 motifs were found only in psy1 promoters, while the G2 motifs were found only in psy2a. Interestingly, both ATCTA and G2 motifs were identified in the 5’ UTRs of Asupina and Cavendish psy1. Consistent with other monocot promoters, introns were present in the Asupina and Cavendish psy1 5’ UTRs, while none were observed in the psy2a 5’ UTRs. Promoters were cloned into expression constructs, driving the â-glucuronidase (GUS) reporter gene. Transient expression of the Asupina and Cavendish psy1 and psy2a promoters in both Cavendish embryogenic cells and Cavendish fruit demonstrated that all promoters were active, except Cpsy2apr2 and Cpsy2apr3. The functional Cavendish psy2a promoter (Cpsy2apr1) appeared to have activity similar to the Asupina psy2a promoter. The activities of the Asupina and Cavendish psy1 promoters were similar to each other, and comparable to those of the functional psy2a promoters. Semi-quantitative PCR analysis of Asupina and Cavendish psy1 and psy2a transcripts showed that psy2a levels were high in green fruit and decreased during ripening, reinforcing the hypothesis that fruit pVA levels were largely dependent on levels of psy2a expression. Additionally, semi-quantitative PCR using intron-spanning primers indicated that high levels of unprocessed psy2a and psy2b mRNA were present in the ripe fruit of Cavendish but not in Asupina. This raised the possibility that differences in intron processing may influence pVA accumulation in Asupina and Cavendish. In this study the role of PSY in banana pVA accumulation was analysed at a number of different levels. Both mRNA accumulation and promoter activity of psy genes studied were very similar between Asupina and Cavendish. However, in several experiments there was evidence of cryptic or alternate splicing that differed in Cavendish compared to Asupina, although these differences were not conclusively linked to the differences in fruit pVA accumulation between Asupina and Cavendish. Therefore, other carotenoid biosynthetic genes or regulatory mechanisms may be involved in determining pVA levels in these cultivars. This study has contributed to an increased understanding of the role of PSY in the production of pVA carotenoids in banana fruit, corroborating the importance of this enzyme in regulating carotenoid production. Ultimately, this work may serve to inform future research into pVA accumulation in important crop varieties such as the EAHB and the discovery of avenues to improve such crops through genetic modification.

Regulating coal seam gas in Queensland : lessons in an adaptive environmental management approach?

The current regulatory approach to coal seam gas projects in Queensland is based on the philosophy of adaptive environmental management. This method of “learning by doing” is implemented in Queensland primarily through the imposition of layered monitoring and reporting duties on the coal seam gas operator alongside obligations to compensate and “make good” harm caused. The purpose of this article is to provide a critical review of the Queensland regulatory approach to the approval and minimisation of adverse impacts from coal seam gas activities. Following an overview of the hallmarks of an effective adaptive management approach, this article begins by addressing the mosaic of approval processes and impact assessment regimes that may apply to coal seam gas projects. This includes recent Strategic Cropping Land reforms. This article then turns to consider the preconditions for land access in Queensland and the emerging issues for landholders relating to the negotiation of access and compensation agreements. This article then undertakes a critical review of the environmental duties imposed on coal seam gas operators relating to hydraulic fracturing, well head leaks, groundwater management and the disposal and beneficial use of produced water. Finally, conclusions are drawn regarding the overall effectiveness of the Queensland framework and the lessons that may be drawn from Queensland’s adaptive environmental management approach.

Soil carbon sequestration and associated economic costs for farming systems of the Indo-Gangetic Plain : a meta-analysis

Soil organic carbon sequestration rates over 20 years based on the Intergovernmental Panel for Climate Change (IPCC) methodology were combined with local economic data to determine the potential for soil C sequestration in wheat-based production systems on the Indo-Gangetic Plain (IGP). The C sequestration potential of rice–wheat systems of India on conversion to no-tillage is estimated to be 44.1 Mt C over 20 years. Implementing no-tillage practices in maize–wheat and cotton–wheat production systems would yield an additional 6.6 Mt C. This offset is equivalent to 9.6% of India's annual greenhouse gas emissions (519 Mt C) from all sectors (excluding land use change and forestry), or less than one percent per annum. The economic analysis was summarized as carbon supply curves expressing the total additional C accumulated over 20 year for a price per tonne of carbon sequestered ranging from zero to USD 200. At a carbon price of USD 25 Mg C−1, 3 Mt C (7% of the soil C sequestration potential) could be sequestered over 20 years through the implementation of no-till cropping practices in rice–wheat systems of the Indian States of the IGP, increasing to 7.3 Mt C (17% of the soil C sequestration potential) at USD 50 Mg C−1. Maximum levels of sequestration could be attained with carbon prices approaching USD 200 Mg C−1 for the States of Bihar and Punjab. At this carbon price, a total of 34.7 Mt C (79% of the estimated C sequestration potential) could be sequestered over 20 years across the rice–wheat region of India, with Uttar Pradesh contributing 13.9 Mt C.

Soil N2O and CO2 emissions from cotton in Australia under varying irrigation management

Irrigation is known to stimulate soil microbial carbon and nitrogen turnover and potentially the emissions of nitrous oxide (N2O) and carbon dioxide (CO2). We conducted a study to evaluate the effect of three different irrigation intensities on soil N2O and CO2 fluxes and to determine if irrigation management can be used to mitigate N2O emissions from irrigated cotton on black vertisols in South-Eastern Queensland, Australia. Fluxes were measured over the entire 2009/2010 cotton growing season with a fully automated chamber system that measured emissions on a sub-daily basis. Irrigation intensity had a significant effect on CO2 emission. More frequent irrigation stimulated soil respiration and seasonal CO2 fluxes ranged from 2.7 to 4.1 Mg-C ha−1 for the treatments with the lowest and highest irrigation frequency, respectively. N2O emission happened episodic with highest emissions when heavy rainfall or irrigation coincided with elevated soil mineral N levels and seasonal emissions ranged from 0.80 to 1.07 kg N2O-N ha−1 for the different treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the cotton cropping season, uncorrected for background emissions, ranged from 0.40 to 0.53 % of total N applied for the different treatments. There was no significant effect of the different irrigation treatments on soil N2O fluxes because highest emission happened in all treatments following heavy rainfall caused by a series of summer thunderstorms which overrode the effect of the irrigation treatment. However, higher irrigation intensity increased the cotton yield and therefore reduced the N2O intensity (N2O emission per lint yield) of this cropping system. Our data suggest that there is only limited scope to reduce absolute N2O emissions by different irrigation intensities in irrigated cotton systems with summer dominated rainfall. However, the significant impact of the irrigation treatments on the N2O intensity clearly shows that irrigation can easily be used to optimize the N2O intensity of such a system.

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.

Brave new green world : consequences of a carbon economy for the conservation of Australian biodiversity

Pricing greenhouse gas emissions is a burgeoning and possibly lucrative financial means for climate change mitigation. Emissions pricing is being used to fund emissions-abatement technologies and to modify land management to improve carbon sequestration and retention. Here we discuss the principal land-management options under existing and realistic future emissions-price legislation in Australia, and examine them with respect to their anticipated direct and indirect effects on biodiversity. The main ways in which emissions price-driven changes to land management can affect biodiversity are through policies and practices for (1) environmental plantings for carbon sequestration, (2) native regrowth, (3) fire management, (4) forestry, (5) agricultural practices (including cropping and grazing), and (6) feral animal control. While most land-management options available to reduce net greenhouse gas emissions offer clear advantages to increase the viability of native biodiversity, we describe several caveats regarding potentially negative outcomes, and outline components that need to be considered if biodiversity is also to benefit from the new carbon economy. Carbon plantings will only have real biodiversity value if they comprise appropriate native tree species and provide suitable habitats and resources for valued fauna. Such plantings also risk severely altering local hydrology and reducing water availability. Management of regrowth post-agricultural abandonment requires setting appropriate baselines and allowing for thinning in certain circumstances, and improvements to forestry rotation lengths would likely increase carbon-retention capacity and biodiversity value. Prescribed burning to reduce the frequency of high-intensity wildfires in northern Australia is being used as a tool to increase carbon retention. Fire management in southern Australia is not readily amenable for maximising carbon storage potential, but will become increasingly important for biodiversity conservation as the climate warms. Carbon price-based modifications to agriculture that would benefit biodiversity include reductions in tillage frequency and livestock densities, reductions in fertiliser use, and retention and regeneration of native shrubs; however, anticipated shifts to exotic perennial grass species such as buffel grass and kikuyu could have net negative implications for native biodiversity. Finally, it is unlikely that major reductions in greenhouse gas emissions arising from feral animal control are possible, even though reduced densities of feral herbivores will benefit Australian biodiversity greatly.

Urban agriculture : a growing field of research workshop at INTERACT 2013

Growing food presents diverse challenges and opportunities within the urban environment. As cities develop, population density rises, land prices rise, and the opportunity to use land for traditional farming and gardening diminishes. Counter to this trend there are a growing number of both community gardens, city farms, guerrilla gardening, rooftop and vertical gardens, pot plants, windowsill herbs, and other balcony or backyard gardens cropping up in different cities, all with a purpose to produce food. This workshop brings to-gether practitioners and researchers in the field of urban agriculture and Hu-man-Computer Interaction to explore and opportunities for technology design to support the different forms of growing practice and foster local food production in cities. This 1-day workshop will serve as an active forum for researchers and practi-tioners across various fields including, but not limited to, agriculture and gar-dening, education, urban planning, human-computer interaction, and communi-ty engagement. This workshop has three distinct points of focus: i) Individual and small-scale gardening and food production, and how to connect like minded people who are involved in these practices to share their knowledge ii) Com-munities involved in urban agriculture, either through community gardens, city farms, or grassroots movements, often dependant on volunteer participation, providing the challenge of managing limited resources iii) Environmental and sociocultural sustainability through urban agriculture. The participants will have an opportunity to present their own work. This will be followed by a visit to a nearby city farm, which will provide a local context for a group design exercise. Finally the workshop will conclude with panel dis-cussions to review opportunities for further research and collaborations beyond the conference. For more information, please visit the workshop website, at http://www.urbaninformatics.net/resources/interact2013cfp/

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.