Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

MOE and MOR assessment technologies for improving graded recovery of exotic pines in Australia.

This project was designed to provide the structural softwood processing industry with the basis for improved green and dry grading to allow maximise MGP grade yields, consistent product performance and reduced processing costs. To achieve this, advanced statistical techniques were used in conjunction with state-of-the-art property measurement systems. Specifically, the project aimed to make two significant steps forward for the Australian structural softwood industry: • assessment of technologies, both existing and novel, that may lead to selection of a consistent, reliable and accurate device for the log yard and green mill. The purpose is to more accurately identify and reject material that will not make a minimum grade of MGP10 downstream; • improved correlation of grading MOE and MOR parameters in the dry mill using new analytical methods and a combination of devices. The three populations tested were stiffness-limited radiata pine, strength-limited radiata pine and Caribbean pine. Resonance tests were conducted on logs prior to sawmilling, and on boards. Raw data from existing in-line systems were captured for the green and dry boards. The dataset was analysed using classical and advanced statistical tools to provide correlations between data sets and to develop efficient strength and stiffness prediction equations. Stiffness and strength prediction algorithms were developed from raw and combined parameters. Parameters were analysed for comparison of prediction capabilities using in-line parameters, off-line parameters and a combination of in-line and off-line parameters. The results show that acoustic resonance techniques have potential for log assessment, to sort for low stiffness and/or low strength, depending on the resource. From the log measurements, a strong correlation was found between the average static MOE of the dried boards within a log and the predicted value. These results have application in segregating logs into structural and non-structural uses. Some commercial technologies are already available for this application such as Hitman LG640. For green boards it was found that in-line and laboratory acoustic devices can provide a good prediction of dry static MOE and moderate prediction for MOR.There is high potential for segregating boards at this stage of processing. Grading after the log breakdown can improve significantly the effectiveness of the mill. Subsequently, reductions in non-structural volumes can be achieved. Depending on the resource it can be expected that a 5 to 8 % reduction in non structural boards won’t be dried with an associated saving of $70 to 85/m3. For dry boards, vibration and a standard Metriguard CLT/HCLT provided a similar level of prediction on stiffness limited resource. However, Metriguard provides a better strength prediction in strength limited resources (due to this equipment’s ability to measure local characteristics). The combination of grading equipment specifically for stiffness related predictors (Metriguard or vibration) with defect detection systems (optical or X-ray scanner) provides a higher level of prediction, especially for MOR. Several commercial technologies are already available for acoustic grading on board such those from Microtec, Luxscan, Falcon engineering or Dynalyse AB for example. Differing combinations of equipment, and their strategic location within the processing chain, can dramatically improve the efficiency of the mill, the level of which will vary depending of the resource. For example, an initial acoustic sorting on green boards combined with an optical scanner associated with an acoustic system for grading dry board can result in a large reduction of the proportion of low value low non-structural produced. The application of classical MLR on several predictors proved to be effective, in particular for MOR predictions. However, the usage of a modern statistics approach(chemometrics tools) such as PLS proved to be more efficient for improving the level of prediction. Compared to existing technologies, the results of the project indicate a good improvement potential for grading in the green mill, ahead of kiln drying and subsequent cost-adding processes. The next stage is the development and refinement of systems for this purpose.

Making More from Sheep Phase II : MMfS State Coordination – Queensland

Making More from Sheep (MMfS) is a majority market extension program funded by Meat & Livestock Australia (MLA) and Australian Wool Innovation (AWI). Phase II of MMfS commenced in Queensland with a business planning process in October 2010 and delivery from November 2010 until November 2013. Mr Tony Hamilton of the Department of Agriculture, Fisheries and Forestry (DAFF) was initially the State Coordinator with responsibility for planning, project implementation, monitoring and evaluation. He was replaced by Ms Nicole Sallur from DAFF towards the end of the project. Delivery involving partner organisations provided best practice management information and tools to sheep producers with target Key Performance Indicators (KPI’s) exceeded across all three tiers of engagement category. 31 events were delivered to 551 participants. Satisfaction and value scores averaged across all events measured 8.7 and 8.2 respectively. Operational recommendations have been included in the report.

AG15 (Sustainable Agricultural State-level Investment Program) natural resource management extension in irrigated cotton and grain

Natural Resource Management project developing reources and supporting best practice management for irrigated cotton and grain growers in Queensland.

Effect of physiological and experiential state of Bactrocera tryoni flies on intra-tree foraging behavior for food (bacteria) and host fruit

Using caged guava trees in Queensland, Australia, provided with food and oviposition sites, the foraging behaviour of females of the tephritid Bactrocera tryoni was investigated in relation to hunger for protein, the presence or absence of bacteria as a source of protein, the degree of prior experience with host fruit and quality of host fruit for oviposition. One aim was to evaluate whether it is immature or mature B. tryoni females that are responsible for initially inoculating host fruit surfaces with "fruit-fly-type" bacteria, the odour of which is known to attract B. tryoni females. Three-week-old immature females provided with sucrose but deprived of protein from eclosion had a much greater propensity than 3-week-old protein-fed mature females to visit vials containing fruit-fly-type bacteria, irrespective of whether vials were associated with adjacent host fruit or not. In the absence of associated bacteria in vials, immature females had a much lower propensity than mature females to visit host fruit. In the presence of bacteria in vials, however, propensity of immature and mature females to visit fruit was about equal. Mature (but not immature) females were more inclined to visit fruit that ranked higher for oviposition (nectarines) than fruit that ranked lower (sweet oranges). Mature females that attempted oviposition during a single 3-min exposure period to a nectarine prior to release were much more likely to find a nectarine than were mature females naive to fruit or immature females with or without prior contact with fruit. Exposure to a nectarine before release did not affect the propensity of either mature or immature females to alight on an odourless visual model of a nectarine, however. As judged by numbers of leaves visited, protein-deprived immature females were more active than protein-fed mature females, irrespective of the sorts of resources on a tree. It was concluded that: the 1st B. tryoni females to arrive on the fruit of a host tree and therefore inoculate the fruit with fruit-fly-type bacteria were unlikely to be sexually immature, but to be mature as a result of having earlier acquired protein elsewhere; the odour of colonies of fruit-fly-type bacteria when associated with host fruit attracted protein-hungry but not protein-fed females; and the odour of the fruit itself attracted mature females (especially experienced ones) but not immature females.

Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change

The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.