7 resultados para Laghi vulcanici, Kawah Ijen, Saturation Index, diluizione, degassamento, sferule di zolfo.
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Seven discrete stages and substages of moulting in the ornate rock lobster, Panulirus ornatus, have been distinguished by microscopic examination of the cuticle and setae of the pleopods . The diagnostic features and the duration of each of the stages are described. Freezing did not visually alter the tissue features used to identify each moult stage. Pleopod morphology can reliably indicate whether a lobster has moulted within the previous 24 h or is within 72 h of the next ecdysis.
Resumo:
Forty-four study sites were established in remnant woodland in the Burdekin River catchment in tropical north-east Queensland, Australia, to assess recent (decadal) vegetation change. The aim of this study was further to evaluate whether wide-scale vegetation 'thickening' (proliferation of woody plants in formerly more open woodlands) had occurred during the last century, coinciding with significant changes in land management. Soil samples from several depth intervals were size separated into different soil organic carbon (SOC) fractions, which differed from one another by chemical composition and turnover times. Tropical (C4) grasses dominate in the Burdekin catchment, and thus δ13C analyses of SOC fractions with different turnover times can be used to assess whether the relative proportion of trees (C3) and grasses (C4) had changed over time. However, a method was required to permit standardized assessment of the δ13C data for the individual sites within the 13 Mha catchment, which varied in soil and vegetation characteristics. Thus, an index was developed using data from three detailed study sites and global literature to standardize individual isotopic data from different soil depths and SOC fractions to reflect only the changed proportion of trees (C3) to grasses (C3) over decadal timescales. When applied to the 44 individual sites distributed throughout the Burdekin catchment, 64% of the sites were shown to have experienced decadal vegetation thickening, while 29% had remained stable and the remaining 7% had thinned. Thus, the development of this index enabled regional scale assessment and comparison of decadal vegetation patterns without having to rely on prior knowledge of vegetation changes or aerial photography.
Resumo:
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.
Resumo:
Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.
Resumo:
Negative potassium (K) balances in all broadacre grain cropping systems in northern Australia are resulting in a decline in the plant-available reserves of K and necessitating a closer examination of strategies to detect and respond to developing K deficiency in clay soils. Grain growers on the Red Ferrosol soils have increasingly encountered K deficiency over the last 10 years due to lower available K reserves in these soils in their native condition. However, the problem is now increasingly evident on the medium-heavy clay soils (Black and Grey Vertosols) and is made more complicated by the widespread adoption of direct drill cropping systems and the resulting strong strati. cation of available K reserves in the top 0.05-0.1 m of the soil pro. le. This paper reports glasshouse studies examining the fate of applied K fertiliser in key cropping soils of the inland Burnett region of south-east Queensland, and uses the resultant understanding of K dynamics to interpret results of field trials assessing the effectiveness of K application strategies in terms of K availability to crop plants. At similar concentrations of exchangeable K (K-exch), soil solution K concentrations and activity of K in the soil solution (AR(K)) varied by 6-7-fold between soil types. When K-exch arising from different rates of fertiliser application was expressed as a percentage of the effective cation exchange capacity (i.e. K saturation), there was evidence of greater selective adsorption of K on the exchange complex of Red Ferrosols than Black and Grey Vertosols or Brown Dermosols. Both soil solution K and AR(K) were much less responsive to increasing K-exch in the Black Vertosols; this is indicative of these soils having a high K buffer capacity (KBC). These contrasting properties have implications for the rate of diffusive supply of K to plant roots and the likely impact of K application strategies (banding v. broadcast and incorporation) on plant K uptake. Field studies investigating K application strategies (banding v. broadcasting) and the interaction with the degree of soil disturbance/mixing of different soil types are discussed in relation to K dynamics derived from glasshouse studies. Greater propensity to accumulate luxury K in crop biomass was observed in a Brown Ferrosol with a KBC lower than that of a Black Vertosol, consistent with more efficient diffusive supply to plant roots in the Ferrosol. This luxury K uptake, when combined with crops exhibiting low proportional removal of K in the harvested product (i.e. low K harvest index coarse grains and winter cereals) and residue retention, can lead to rapid re-development of stratified K profiles. There was clear evidence that some incorporation of K fertiliser into soil was required to facilitate root access and crop uptake, although there was no evidence of a need to incorporate K fertiliser any deeper than achieved by conventional disc tillage (i.e. 0.1-0.15 m). Recovery of fertiliser K applied in deep (0.25-0.3 m) bands in combination with N and P to facilitate root proliferation was quite poor in Red Ferrosols and Grey or Black Vertosols with moderate effective cation exchange capacity (ECEC, 25-35 cmol(+)/kg), was reasonable but not enough to overcome K deficiency in a Brown Dermosol (ECEC 11 cmol(+)/kg), but was quite good on a Black Vertosol (ECEC 50-60 cmol(+)/kg). Collectively, results suggest that frequent small applications of K fertiliser, preferably with some soil mixing, is an effective fertiliser application strategy on lighter clay soils with low KBC and an effective diffusive supply mechanism. Alternately, concentrated K bands and enhanced root proliferation around them may be a more effective strategy in Vertosol soils with high KBC and limited diffusive supply. Further studies to assess this hypothesis are needed.
Resumo:
Varying the spatial distribution of applied nitrogen (N) fertilizer to match demand in crops has been shown to increase profits in Australia. Better matching the timing of N inputs to plant requirements has been shown to improve nitrogen use efficiency and crop yields and could reduce nitrous oxide emissions from broad acre grains. Farmers in the wheat production area of south eastern Australia are increasingly splitting N application with the second timing applied at stem elongation (Zadoks 30). Spectral indices have shown the ability to detect crop canopy N status but a robust method using a consistent calibration that functions across seasons has been lacking. One spectral index, the canopy chlorophyll content index (CCCI) designed to detect canopy N using three wavebands along the "red edge" of the spectrum was combined with the canopy nitrogen index (CNI), which was developed to normalize for crop biomass and correct for the N dilution effect of crop canopies. The CCCI-CNI index approach was applied to a 3-year study to develop a single calibration derived from a wheat crop sown in research plots near Horsham, Victoria, Australia. The index was able to predict canopy N (g m-2) from Zadoks 14-37 with an r2 of 0.97 and RMSE of 0.65 g N m-2 when dry weight biomass by area was also considered. We suggest that measures of N estimated from remote methods use N per unit area as the metric and that reference directly to canopy %N is not an appropriate method for estimating plant concentration without first accounting for the N dilution effect. This approach provides a link to crop development rather than creating a purely numerical relationship. The sole biophysical input, biomass, is challenging to quantify robustly via spectral methods. Combining remote sensing with crop modelling could provide a robust method for estimating biomass and therefore a method to estimate canopy N remotely. Future research will explore this and the use of active and passive sensor technologies for use in precision farming for targeted N management.
Resumo:
Rarely is it possible to obtain absolute numbers in free-ranging populations and although various direct and indirect methods are used to estimate abundance, few are validated against populations of known size. In this paper, we apply grounding, calibration and verification methods, used to validate mathematical models, to methods of estimating relative abundance. To illustrate how this might be done, we consider and evaluate the widely applied passive tracking index (PTI) methodology. Using published data, we examine the rationality of PTI methodology, how conceptually animal activity and abundance are related and how alternative methods are subject to similar biases or produce similar abundance estimates and trends. We then attune the method against populations representing a range of densities likely to be encountered in the field. Finally, we compare PTI trends against a prediction that adjacent populations of the same species will have similar abundance values and trends in activity. We show that while PTI abundance estimates are subject to environmental and behavioural stochasticity peculiar to each species, the PTI method and associated variance estimate showed high probability of detection, high precision of abundance values and, generally, low variability between surveys, and suggest that the PTI method applied using this procedure and for these species provides a sensitive and credible index of abundance. This same or similar validation approach can and should be applied to alternative relative abundance methods in order to demonstrate their credibility and justify their use.