Should Native Pastures Be Fertilised?

Considerable research has been conducted in recent years demonstrating the ongoing benefits of phosphorus (P) fertiliser in achieving and maintaining higher levels of production from native pastures (Graham 2006; Garden et al. 2003; Lodge et al. 2003; Michalk et al. 2003). However Garden et al. (2003), Hill et al. (2004) and Dorrough et al. (2008) all question the sustainability of this practice by highlighting changes in species composition of these pastures with regard to increasing the introduced annual grass and broadleaf weed components at the expense of the native grasses and forbs but in most cases, these trends have been based on short term replicated data or based on qualitative survey data incapable of establishing causal relationships. In the Monaro region of NSW, 70% of pastures are based on native species and are the cornerstone of livestock production. The Monaro Research, Development and Demonstration of Sustainable Grassland Management Project (MGP) was designed to determine if productivity could be increased without compromising the composition and bio-diversity values of these pastures

Social integration and system integration: Reconsidering the classical distinction

Accepted versio

Soil acidity and nutrient deficiency cause poor legume nodulation in the permanent pasture and mixed farming zones of south-eastern Australia

Pasture legumes must be adequately and effectively nodulated in order to reach nitrogen-fixation targets. Of 225 pasture paddocks sampled across the Central Tablelands, Central West, Monaro and Riverina regions of New South Wales, 93% had inadequate legume nodulation. Legume content was significantly higher in the mixed faming zone (>50%, Central West and Riverina) than the permanent pasture zone (26%, Central Tablelands; 28% Monaro). Available phosphorus (P) was below critical levels in 40% of paddocks sampled and sulfur (S) in 73% of paddocks; >35% of all paddocks had soil pHCa 5.55, nodulation was predicted to be near adequate (score 3.95, where adequate = 4). At pHCa <5.55, higher available S resulted in a higher nodulation score (2.42) than in paddocks where S was deficient (score 0–1.97). These results suggest that improving the capacity of legumes to supply nitrogen should focus on addressing soil acidity and plant nutrition, specifically P and S

Achieving data synergy: the socio-technical process of handling data

Good quality research depends on good quality data. In multidisciplinary projects with quantitative and qualitative data, it can be difficult to collect data and share it between partners with diverse backgrounds in a timely and useful way, limiting the ability of different disciplines to collaborate. This chapter will explore two examples of the impact of data collection and sharing on analysis in a recent Horizon 2020 project, RealValue. The main insight is that it is not only projects but also the processes within them such as data collection, sharing and analysis that are socio-technical. We shall examine two examples within the project—validating the models and triangulating the qualitative data—to examine data synergy across four dimensions: time (synchronising activities), people (managing and coordinating actors), technology (in this case focusing mainly on connectivity) and quality. Recommendations include developing a data protocol for the energy demand community built on these four dimensions

Simulating residential demand response: Improving socio-technical assumptions in activity-based models of energy demand

Demand response is receiving increasing interest as a new form of flexibility within lowcarbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, the socio-technical assumptions underpinning ‘bottom-up’ activity-based energy demand models are identified and a number of shortcomings are discussed. First, links between appliance usage and activities are not evidence-based. We propose new data collection approaches to address this gap. Second, aside from thermal comfort, service expectations, which can be an important source of flexibility, are underrepresented and their inclusion into demand models would improve their predicative power in this area. Finally, flexibility can be present over a range of time scales, from immediate responses, to longer term trends. Longitudinal time use data from participants in demand response schemes may be able to illuminate these. The recommendations of this paper seek to enhance the current state-of-the-art in activity-based models and to provide useful tools for the assessment of demand response