10 resultados para Classified site

em eResearch Archive - Queensland Department of Agriculture


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Six species of line-caught coral reef fish (Plectropomus spp., Lethrinus miniatus, Lethrinus laticaudis, Lutjanus sebae, Lutjanus malabaricus and Lutjanus erythropterus) were tagged by members of the Australian National Sportsfishing Association (ANSA) in Queensland between 1986 and 2003. Of the 14,757 fish tagged, 1607 were recaptured and we analysed these data to describe movement and determine factors likely to impact release survival. All species were classified as residents since over 80% of recaptures for each species occurred within 1 km of the release site. Few individuals (range 0.8-5%) were recaptured more than 20 km from their release point. L. sebae had a higher recapture rate (19.9%) than the other species studied (range 2.1-11.7%). Venting swimbladder gases, regardless of whether or not fish appeared to be suffering from barotrauma, significantly enhanced (P < 0.05) the survival of L. sebae and L. malabaricus but had no significant effect (P > 0.05) on L. erythropterus. The condition of fish on release, subjectively assessed by anglers, was only a significant effect on recapture rate for L. sebae where fish in "fair" condition had less than half the recapture rate of those assessed as in "excellent" or "good" condition. The recapture rate of L. sebae and L. laticaudis was significantly (P < 0.05) affected by depth with recapture rate declining in depths exceeding 30 m. Overall, the results showed that depth of capture, release condition and treatment for barotrauma influenced recapture rate for some species but these effects were not consistent across all species studied. Recommendations were made to the ANSA tagging clubs to record additional information such as injury, hooking location and hook type to enable a more comprehensive future assessment of the factors influencing release survival.

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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.

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Most plant disease resistance (R) genes encode proteins with a nucleotide binding site and leucine-rich repeat structure (NBS-LRR). In this study, degenerate primers were used to amplify genomic NBS-type sequences from wild banana (Musa acuminata ssp. malaccensis) plants resistant to the fungal pathogen Fusarium oxysporum formae specialis (f. sp.) cubense (FOC) race 4. Five different classes of NBS-type sequences were identified and designated as resistance gene candidates (RGCs). The deduced amino acid sequences of the RGCs revealed the presence of motifs characteristic of the majority of known plant NBS-LRR resistance genes. Structural and phylogenetic analyses grouped the banana RGCs within the non-TIR (homology to Toll/interleukin-1 receptors) subclass of NBS sequences. Southern hybridization showed that each banana RGC is present in low copy number. The expression of the RGCs was assessed by RT-PCR in leaf and root tissues of plants resistant or susceptible to FOC race 4. RGC1, 3 and 5 showed a constitutive expression profile in both resistant and susceptible plants whereas no expression was detected for RGC4. Interestingly, RGC2 expression was found to be associated only to FOC race 4 resistant lines. This finding could assist in the identification of a FOC race 4 resistance gene.

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Hazard site surveillance is a system for post-border detection of new pest incursions, targeting sites that are considered potentially at high risk of such introductions. Globalisation, increased volumes of containerised freight and competition for space at domestic ports means that goods are increasingly being first opened at premises some distance from the port of entry, thus dispersing risk away from the main inspection point. Hazard site surveillance acts as a backstop to border control to ensure that new incursions are detected sufficiently early to allow the full range of management options, including eradication and containment, to be considered. This is particularly important for some of the more cryptic forest pests whose presence in a forest often is not discovered until populations are already high and the pest is well established. General requirements for a hazard site surveillance program are discussed using a program developed in Brisbane, Australia, in 2006 as a case study. Some early results from the Brisbane program are presented. In total 67 species and 5757 individuals of wood-boring beetles have been trapped and identified during the program to date. Scolytines are the most abundant taxa, making up 83% of the catch. No new exotics have been trapped but 19 of the species and 60% of all specimens caught are exotics that are already established in Australia.

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Chytridiomycosis is an emerging infectious disease of amphibians caused by the fungal pathogen Batrachochytrium dendrobatidis, and its role in causing population declines and species extinctions worldwide has created an urgent need for methods to detect it. Several reports indicate that in anurans chytridiomycosis can cause the depigmentation of tadpole tnouthparts, but the accuracy of using depigmentation to determine disease status remains uncertain. Our objective was to determine for the Mountain Yellow-legged Frog (Rana muscosa) whether visual inspections of the extent of tadpole mouthpart depigmentation could be used to accurately categorize individual tadpoles or R. muscosa populations as B. dendrobatidis-positive or negative. This was accomplished by assessing the degree of mouthpart depigmentation in tadpoles of known disease status (based on PCR assays). The depigmentation of R. muscosa tadpole mouthparts was associated with the presence of B. dendrobatidis, and this association was particularly strong for upper jaw sheaths. Using a rule that classifies tadpoles with upper jaw sheaths that are 100% pigmented as uninfected and those with jaw sheaths that are <100% pigmented as infected resulted in the infection status of 86% of the tadpoles being correctly classified. By applying this rule to jaw sheath pigmentation scores averaged across all tadpoles inspected per site, we were able to correctly categorize the infection status of 92% of the study populations. Similar research on additional anurans is critically needed to determine how broadly applicable our results for R. muscosa are to other species.

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This report evaluates the wood and veneer properties of plantation-grown spotted gum (Corymbia citriodora subsp. variegata, or CCV) and Dunn's white gum (Eucalyptus dunnii), grown at different stockings, in thinning trials near Ellangowan in north-east New South Wales (mean annual rainfall 1050 mm) and Kingaroy in south-east Queensland (mean annual rainfall 873 mm). Thinning trials were established at age seven years. Both species showed a significant increase in stem diameter growth of the dominant trees in response to thinning. At age 10 years, trees from the unthinned (950–1270 stems ha-1) and 300 stems ha-1 treatments were selected for veneering. Five dominant trees were felled from each combination of species x sites x thinning treatment. Diameter at breast height over bark of the selected trees ranged from 20 cm to 27 cm at Ellangowan, and 19 cm to 26 cm at Kingaroy. From each tree, 1.5 m long billets were removed at two positions: a butt billet from 0.3–1.8 m above ground and a top billet from approximately 5.5–7.0 m. Log end splitting was assessed 24 hours after harvesting and again after steaming, approximately four days after harvesting. Disks from just above both billets were collected for assessment of wood properties. Billets were peeled on a spindleless veneer lathe to produce a full veneer ribbon with a target green thickness of 2.8 to 3.0 mm. The 1.55 m wide (tangential dimension) veneer sheets were dried and graded according to AS/NZ Standard 2269:2008, which describes four veneer grades. Veneer samples taken along the length of the veneer ribbon, at regular intervals of 1.55 m, were tested for stiffness, shrinkage and density. Veneer length measurements were used to calculate the radial distance of each sample from the central axis of the billet. Overall veneer gross recoveries ranged from 50% to 70%. They were significantly lower at the Kingaroy site, for both species. The veneer recoveries achieved were 2–3 times higher than typical green off saw recoveries from small plantation hardwood logs of similar diameter. Most of the veneer recovered was classified as D-grade. CCV trees from the Ellangowan site yielded up to 38% of the better C-grade and higher grade veneers. The main limiting factors that prevented veneer from meeting higher grades were the presence of kino defects and encased knots. Splits in E. dunnii veneer also contributed to reduced grade quality. Log end splits were higher for E. dunnii than for CCV, and logs from Ellangowan exhibited more severe splitting. Split index was generally higher for top than for butt billets. Split index was strongly correlated with the average veneer grade from corresponding billets. The Ellangowan site, where rainfall was higher and trees grew faster, yielded significantly denser and stiffer veneers than did the drier sites near Kingaroy, where tree growth was slower. The difference was more pronounced for E. dunnii than for CCV. Differences in measured wood properties between thinned and unthinned treatments were generally small and not significant. On average, 10% of billet volume was lost during the peeling rounding-up process. Much of the wood laid down following thinning was removed during rounding-up, meaning the effect of thinning on veneer properties could not be effectively assessed. CCV was confirmed as having high veneer density and very good veneer stiffness, exceeding 15 GPa, making it very suitable for structural products. E. dunnii also demonstrated good potential as a useful structural plywood resource, achieving stiffness above 10 GPa. Veneer stiffness and density in CCV increased from pith to bark at both sites, while for E. dunnii there was a radial increase in these properties at the Ellangowan site only. At the drier Kingaroy site, veneer stiffness and density declined from mid-radius to the log periphery. This may be associated with prolonged drought from 2005 to 2009, corresponding to the later years of tree growth at the Kingaroy site. CCV appeared to be less sensitive to drought conditions. Standing tree acoustic velocity, determined by the Fakopp time-of-flight method, provided a reliable prediction of average veneer stiffness for both species (R2=0.78 for CCV and R2=0.90 for E. dunnii) suggesting that the Fakopp method may be a useful indicator of tree and stand quality, in terms of veneer stiffness in standing trees.

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It is at the population level that an invasion either fails or succeeds. Lantana camara L. (Verbenaceae) is a weed of great significance in Queensland Australia and globally but its whole life-history ecology is poorly known. Here we used 3 years of field data across four land use types (farm, hoop pine plantation and two open eucalyptus forests, including one with a triennial fire regime) to parameterise the weed’s vital rates and develop size-structured matrix models. Lantana camara in its re-colonization phase, as observed in the recently cleared hoop pine plantation, was projected to increase more rapidly (annual growth rate, λ = 3.80) than at the other three sites (λ 1.88–2.71). Elasticity analyses indicated that growth contributed more (64.6 %) to λ than fecundity (18.5 %) or survival (15.5 %), while across size groups, the contribution was of the order: juvenile (19–27 %) ≥ seed (17–28 %) ≥ seedling (16–25 %) > small adult (4–26 %) ≥ medium adult (7–20 %) > large adult (0–20 %). From a control perspective it is difficult to determine a single weak point in the life cycle of lantana that might be exploited to reduce growth below a sustaining rate. The triennial fire regime applied did not alter the population elasticity structure nor resulted in local control of the weed. However, simulations showed that, except for the farm population, periodic burning could work within 4–10 years for control of the weed, but fire frequency should increase to at least once every 2 years. For the farm, site-specific control may be achieved by 15 years if the biennial fire frequency is tempered with increased burning intensity.

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Mixed species plantations using native trees are increasingly being considered for sustainable timber production. Successful application of mixed species forestry systems requires knowledge of the potential spatial interaction between species in order to minimise the chance of dominance and suppression and to maximise wood production. Here, we examined species performances across 52 experimental plots of tree mixtures established on cleared rainforest land to analyse relationships between the growth of component species and climate and soil conditions. We derived site index (SI) equations for ten priority species to evaluate performance and site preferences. Variation in SI of focus species demonstrated that there are strong species-specific responses to climate and soil variables. The best predictor of tree growth for rainforest species Elaeocarpus grandis and Flindersia brayleyana was soil type, as trees grew significantly better on well-draining than on poorly drained soil profiles. Both E. grandis and Eucalyptus pellita showed strong growth response to variation in mean rain days per month. Our study generates understanding of the relative performance of species in mixed species plantations in the Wet Tropics of Australia and improves our ability to predict species growth compatibilities at potential planting sites within the region. Given appropriate species selections and plantation design, mixed plantations of high-value native timber species are capable of sustaining relatively high productivity at a range of sites up to age 10 years, and may offer a feasible approach for large-scale reforestation.

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Key message Log-end splitting is one of the single most important defects in veneer logs. We show that log-end splitting in the temperate plantation species Eucalyptus nitens varies across sites and within-tree log position and increases with time in storage. Context Log-end splitting is one of the single most important defects in veneer logs because it can substantially reduce the recovery of veneer sheets. Eucalyptus nitens can develop log-end splits, but factors affecting log-end splitting in this species are not well understood. Aims The present study aims to describe the effect of log storage and steaming on the development of log-end splitting in logs from different plantations and log positions within the tree. Methods The study was conducted on upper and lower logs from each of 41 trees from three 20–22-year-old Tasmanian E. nitens plantations. Log-end splitting was assessed immediately after felling, after transport and storage in a log-yard, and just before peeling. A pre-peeling steam treatment was applied to half the logs. Results Site had a significant effect on splitting, and upper logs split more than lower logs with storage. Splitting increased with tree diameter breast height (DBH), but this relationship varied with site. The most rapidly growing site had more splitting even after accounting for DBH. No significant effect of steaming was detected. Conclusion Log-end splitting varied across sites and within-tree log position and increased with time in storage.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.