Lippia (Phyla canescens) and its response to fire

Lippia (Phyla canescens), a significant invasive weed, is a recognized threat to floodplain woodlands in Australia, particularly in the Murray-Darling Basin. Current control methods include the use of herbicides, which can be costly and environmentally harmful, particularly in riparian areas. 'Environmentally friendly' control mechanisms are yet to be found, with the potential for biological control still being researched. This research explores the use of fire as a potential control method to help slow the expansion and growth of lippia. Lippia response to fire and the effect of fire in lippia-invaded landscapes has not previously been investigated. Half of the St. Ruth Reserve south of Dalby in Southern Queensland was subject to a control burn in November 2013 by the Western Downs Regional Council in an attempt to reduce lippia abundance in this remnant riparian woodland. This research investigates the response of lippia to the burn. The study will compare the cover abundance of lippia and major functional plant groups between burnt and unburnt (control) sites within the reserve; it will also investigate the impact of fire on lippia germination rates in soil samples from burnt and unburnt sites. Additional studies testing lippia seed viability, using tetrazolium staining, will also be conducted after a range of fire mimicking treatments have been applied to seeds and compared to controls from an unburnt area. This research will contribute to evidence-based decision-making for improved management of lippia-invaded remnant ecosystems

Groundwater thresholds for drought resilience in floodplain woodlands: a case study from the northern Murray-Darling Basin

In ephemeral river systems, canopy condition in dominant riparian and floodplain tree species may depend on access to shallow groundwater resources, particularly during drought. However, unsustainable groundwater extraction and chronic groundwater decline, evident in many agricultural landscapes worldwide, effectively decouples tree roots from deep soil moisture resources, increasing the susceptibility of trees to changes in precipitation. In such regions, drought may trigger loss of canopy condition and have long term consequences for the function and survival of trees and the composition, structure and function of ecosystems they dominate. However, critical groundwater depth thresholds have been difficult to identify. This study used a novel approach including boosted regression trees, quantile regression and threshold analysis to explore the relationship between groundwater depth and tree condition for two dominant tree species, Eucalyptus camaldulensis (river red gum) and E. populnea (poplar box); both species occur on the Upper Condamine floodplain, a region experiencing groundwater depth declines of 25+m in the northern Murray-­‐Darling Basin, southern Queensland. Distinct non-­‐linear responses were apparent, with minimum groundwater depth thresholds identified at 12.1m for E. camaldulensis and 12.6m for E.populnea, beyond which canopy condition declined significantly. This approach represents a repeatable method of quantifying ecological response thresholds along groundwater depth gradients. Its application may enable safe operating limits for groundwater resource management to be identified, supporting improved decision making to support resilient floodplain ecosystems. This will be particularly important in regions where groundwater decline driven by increasing water demand and drying climates is predicted

Can digital discussion support tools provide cost-effective options for agricultural extension services?

Agricultural extension that delivers timely, targeted, and cost-effective support to farmers will help ensure the sustainability and adaptive capacity of agriculture, enhancing both food security and environmental security. Leveraging advances in agriclimate science and adult education, innovative digital technologies offer significant new opportunities to engage with farmers and to support decision making. In this study, animated video clips (machinimas), developed using the Second LifeTM virtual world gaming platform, model conversations around climate risk and critical on-farm decisions in the Australian sugarcane farming industry. Early evaluation indicates that this is an engaging format that promotes discussion by leveraging farmers’ natural modes of information gathering and social learning. Comparison with conventional extension practices indicates that these discussion support tools may be a cost-effective addition to existing approaches. The format’s flexibility means machinimas are readily updated with new information and customized to meet the needs of different farmer groups. Rapid growth in digital access globally and the scalability of such approaches promise greater equity of access to high-value information, critical to better risk management decision making, at minimal cost, for millions of farmers

Groundwater depth thresholds for tree condition

A range of ecological processes supported by groundwater are at risk where socio-economic and climate drivers increase net groundwater demand. Previous research has indicated close links between groundwater and riparian/floodplain tree condition. However, little is known about the nature of the relationship or whether critical groundwater-tree condition thresholds exist. Threshold responses may indicate the existence of groundwater depths associated with rapid ecological change. This study provides evidence of threshold responses between groundwater depth and tree condition in the Condamine catchment in eastern Australia, where groundwater decline due to over-extraction is well documented. It collates tree condition data (118 sites) from recent studies of two dominant Australian floodplain species, Eucalyptus camaldulensis Denh. (river red gum) and E. populnea F. Muell. (poplar box). Boosted regression trees and quantile regression were used to investigate the nature of the relationship and threshold values. A distinct non-linear response of tree condition to groundwater depth was identified, with thresholds identified at 12.5–17.2 m for E. camaldulensis and 15.6–22.0 m for E. populnea. Threshold responses may be explained in terms of physiological limitations to rooting depth in these and similar floodplain/riparian species, with groundwater decline effectively decoupling tree roots from accessible moisture resources leaving trees more vulnerable to hydraulic stress and/or failure particularly under drought conditions. The existence of thresholds suggest that groundwater decline may trigger rapid ecological changes in riparian and floodplain tree species, which may have important implications not only for their future persistence but also the various ecological functions they support

Identifying groundwater thresholds for drought resilience in floodplain tree species in the northern Murray-Darling Basin

Previous research identifies links between groundwater depth and canopy condition in dominant riparian and floodplain tree species associated with ephemeral river systems, particularly during drought. Chronic groundwater decline, evident in many agricultural landscapes worldwide, effectively decouples tree roots from deep soil moisture resources, increasing the susceptibility of trees to changes in precipitation. Drought may trigger loss of canopy condition and, where severe or prolonged, have long term consequences for the function and survival of trees and the composition, structure and function of ecosystems they dominate. However, critical groundwater depth thresholds, which may reflect ecological 'tipping points' in such systems, have been difficult to identify. This study used boosted regression trees, quantile regression and Threshold Indicator Taxa Analysis to investigate the relationship between groundwater depth and tree condition for two dominant tree species, Eucalyptus camaldulensis (river red gum) and E. populnea (poplar box). Both occur on the Upper Condamine floodplain, a region experiencing significant groundwater decline due to unsustainable groundwater extraction in the northern Murray-Darling Basin, southern Queensland. Distinct non-linear responses were found, with groundwater depth thresholds identified at 12.1–22.6m for E. camaldulensis and 12.6–22.6m for E. populnea, beyond which canopy condition declined abruptly. This approach represents a repeatable method of quantifying ecological response thresholds along groundwater depth gradients, application of which may assist in identifying safe operating limits for groundwater resource management to support resilient floodplain ecosystems. It will be particularly important in regions where increasing water demand and drying climates may drive further groundwater decline

Applying risk-based principles of dispersive mine spoil behaviour to facilitate development of cost-effective best management practices

Dispersive spoil material on mine sites represents a significant operational, environmental and economic challenge to mining operations. Better understanding of the chemical and physical characteristic of spoil material and its behaviour under different climatic and management regimes is needed to inform site-specific management decisions. This industry-funded project has developed, parameterised and tested a prototype Bayesian network (BN) model which integrates a range of biophysical (climate, spoil characteristics, vegetation cover) and management (landform, spoil amendment, runoff management) variables. Where available, quantitative data were used to parameterise the model; however, in many instances, existing data were too few and it was necessary to use qualitative information (expert judgement). The process of developing the model identified serious data deficiencies which should inform future data collection strategies. An ongoing iterative process, with targeted data collection and feedback from industry decision makers and discipline experts, will support improvements in the model, which has significant potential to inform adaptive evidence-based best practice dispersive mine spoil management

Predicting water allocation trade prices using a hybrid Artificial Neural Network-Bayesian modelling approach

This paper proposes an integrated (hybrid) Artificial Neural Network-Bayesian (ANN-B) modelling approach to improve the accuracy of predicting seasonal water allocation prices in Australia’s Murry Irrigation Area, which is part of one of the world’s largest interconnected water markets. Three models (basic, intermediate and full), accommodating different levels of data availability, were considered. Data were analyzed using both ANN and hybrid ANN-B approaches. Using the ANN-B modelling approach, which can simulate complex and non-linear processes, water allocation prices were predicted with a high degree of accuracy (RBASIC = 0.93, RINTER. = 0.96 and RFULL = 0.99); this was a higher level of accuracy than realized using ANN. This approach can potentially be integrated with online data systems to predict water allocation prices, enable better water allocation trade decisions, and improve the productivity and profitability of irrigated agriculture

Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program

The Northern Australia Climate Program (NACP) is a fully integrated research, development and extension (RDandE) program operating across extensive pastoral regions of northern Australia. The NACP aims to improve existing climate models and forecast tools, develop new products to meet user needs and build the capacity of rangeland producers to manage the challenges posed by droughts (or failed wet seasons) and climate variability. Climate information gaps identified through earlier surveys of graziers and communities in rural and remote Australia informed the design of the research component of the NACP, which aims to address the low and variable accuracy of seasonal climate forecasts in many regions, the need for proof of value of forecasts and relevance of existing forecast systems and technologies, and perceived lack of effective support from climate experts for the use of climate resources and technologies in agricultural decision making. The development and extension components of the program aim to improve climate literacy and the use of climate information. Building on the research program, they deliver a climate service that provides local extension and technical support, with a focus on building trust in climate information through locally sourced, industry connected NACP trained and supported extension advisers called Climate Mates. Two-way information flow between decision makers and researchers, facilitated by the Climate Mates, ensures that forecasts and decision- A nd discussion-support tools developed through the program are regionally relevant and targeted to the needs of end users. Monitoring and evaluation of the program indicates that this approach is contributing to positive outcomes in terms of awareness and knowledge of climate forecasting and products, and their adoption and use in decision making (i.e. practice change). In the longer term, the Climate Mates have potential for enduring impact beyond the program, leaving a knowledgeable and trusted climate resource across regional northern Australia

Putting virtual worlds to work to support improved climate risk decision-making on real world farms

Climate variability represents a significant risk to farming enterprises. Effective communication and extension of climate information may improve climate risk decision making and adaptive management responses to climate variability on farms. However, extension services are under strain worldwide due to cost and time constraints. Innovative applications of emerging digital technologies are likely to play an increasingly important role in this space. Evaluation of stakeholder responses to new web-based virtual world ‘discussion-support’ tools (short scripted video clips or machinima filmed in Second Life) indicate that they may provide a potentially revolutionary way to present and cost-effectively disseminate consistent and highly targeted information about climate, climate risk and climate risk adaptation to large numbers of farmers. Leveraging the social and observational learning aspects of farming, these tools also incorporate and apply recent advances in the use of digital technologies in education. With contextualised settings and relevant and engaging storylines, the tools model discussions between farmers about climate information, risk and on-farm practices. Follow up discussion among real life farming groups and farming families, stimulated by the tools, will potentially assist farmers to make better on-farm decisions to manage climate risk which, in turn, will support sustainable food and fibre production systems and reduce environmental harm. Prototype machinimas were developed for and trialled in the Australian sugar cane farming industry (Fig. 1). This industry is located in coastal regions of north-eastern Australia (Queensland and northern New South Wales) which experience high levels of climatic variability ranging from drought to intense rainfall events associated with tropical lows and cyclones. Improved access to targeted climate information, better understanding of climate risk and adaptation through adoption of recommended farm management best practice have been a key focus of sugar industry extension programs, In the sugar industry, as in other agricultural sectors, farmer participation in conventional face-to-face workshops, though effective in influencing adoption rates, is limited and likely to become more so as resources supporting extension services diminish. At the same time, online dissemination of technical information, though far-reaching, is often ineffective. Even the development of high-level decision support tools has seen only limited uptake among farmers. It is generally recognised within extension circles that the key to farmer engagement is through participatory processes and relevant discussion. The discussion support machinimas developed in this project deal with specific scenarios within the sugar cane farming calendar: specifically, irrigation; fertiliser application; harvesting; and planning. Evaluation of the machinimas was conducted, firstly, through a series of climate workshops where the tools were used to generate discussion of climate risk associated with each of these situations. These workshops were followed up with a phenomenographic study in which selected participants were interviewed about their response to the machinimas and transcripts were then analysed thematically. This study was designed to investigate the value of these tools in stimulating discussion about climate risk and adaptation within a farmer group and, subsequently, farming families. Secondly, the machinimas and an on-line survey questionnaire were posted to the website of the sugar cane farming peak body, CANEGROWERS Australia, whose membership numbers approximately 4,000 cane farmers. This survey was designed to investigate both farmer responses to the tools and the effectiveness of the tools, when disseminated electronically, in stimulating discussion and potentially influencing on farm decision making. Results suggest that these virtual world tools positively engage farmers and, while not replacing face-to-face extension, provide cost-effective support for climate risk decision making on Australian sugar cane farms. Future development of the machinimas will enable rapid updates of relevant seasonal climate information to farmer groups to ensure access to the best available information as a basis for discussion and decision making. Increasing capacity to deliver such tools online, given expanding access to the internet and uptake of mobile technologies, also suggests potential to digitally engage large numbers of farmers globally. The virtual world platform in which the machinimas are made allows ready contextualisation of climate risk information for a target audience through customised representations of landscapes, farming systems, characters (avatars) and scripted dialogues that reflect the real life experiences of farmers, wherever they are. Discussion is a key element of social learning. By modelling conversations and stimulating further discussion, these tools may assist in providing cost-effective targeted support for learning and on-farm decision making, thereby enhancing the adaptive capacity of farmers and the development of more sustainable food production systems