Neighborhood diversity, economic health and the role of the arts

Policymakers pursue a range of strategies aimed at diversifying neighborhoods despite research indicating the complicated and potentially damaging results of these efforts. One increasingly common approach is to incorporate the arts into planning efforts in the hope of enhancing diversity and catalyzing positive neighborhood change. Using data from the Cultural Data Project, we determine where newly established New York City art organizations locate in terms of neighborhood racial, income and industry diversity. We then analyze how diverse contexts interact with an arts presence to impact neighborhood economic health over time. We find that neighborhoods with high levels of racial diversity and low levels of income and industry diversity benefit most from an arts presence. However, the arts are attracted predominately to neighborhoods with moderate levels of racial diversity and high levels of income and industry diversity. This complicates the use of the arts as a tool in urban revitalization policy.

Effective Use in Livestock Feeds of Mouldy and Weather-damaged Grain Containing Mycotoxins-Case Histories and Economic Assessments Pertaining to Pig and Poultry Industries of Queensland

Mould growth in field crops or stored grain reduces starch and lipid content, with consequent increases in fibre, and an overall reduction in digestible energy; palatability is often adversely affected. If these factors are allowed for, and mycotoxin concentrations are low, there are sound economic reasons for using this cheaper grain. Mycotoxins are common in stock feed but their effects on animal productivity are usually slight because either the concentration is too low or the animal is tolerant to the toxin. In Australia, aflatoxins occur in peanut by-products and in maize and sorghum if the grain is moist when stored. Zearalenone is found in maize and in sorghum and wheat in wetter regions. Nivalenol and deoxynivalenol are found in maize and wheat but at concentrations that rarely affect pigs, with chickens and cattle being even more tolerant. Other mycotoxins including cyclopiazonic acid, T-2 toxin, cytochalasins and tenuazonic acid are produced by Australian fungi in culture but are not found to be significant grain contaminants. Extremely mouldy sorghum containing Alternaria and Fusarium mycotoxins decreased feed conversion in pigs and chickens by up to 14%. However, E moniliforme- and Diplodia maydis-infected maize produced only slight reductions in feed intake by pigs and Ustilago- infected barley produced no ill effects. Use of these grains would substantially increase profits if the grain can be purchased cheaply.

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Development of a stable isotope index to assess decadal-scale vegetation change and application to woodlands of the Burdekin catchment, Australia

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.

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.

Economic analyses of options for weedy Sporobolus grass management

Weedy Sporobolus grasses have low palatability for livestock, with infestations reducing land condition and pastoral productivity. Control and containment options are available, but the cost of weed control is high relative to the extra return from livestock, thus, limiting private investment. This paper outlines a process for analysing the economic consequences of alternative management options for weedy Sporobolus grasses. This process is applicable to other weeds and other pastoral degradation or development issues. Using a case study property, three scenarios were developed. Each scenario compared two alternative management options and was analysed using discounted cash flow analysis. Two of the scenarios were based on infested properties and one scenario was based on a currently uninfested property but highly likely to become infested without active containment measures preventing weed seed transport and seedling establishment. The analysis highlighted why particular weedy Sporobolus grass management options may not be financially feasible for the landholder with the infestation. However, at the regional scale, the management options may be highly worthwhile due to a reduction in weed seed movement and new weed invasions. Therefore, to encourage investment by landholders in weedy Sporobolus grass management the investment of public money on behalf of landholders with non-infested properties should be considered.

An effective, economic way of monitoring menstrual cycle hormones in at risk female athletes

PURPOSE: Female athletes, in response to intensive training, competition stress and a lean, athletic physique, are at increased risk of altered hypothalamic-pituitary ovarian (HPO) axis function associated with menstrual cycle disturbance and reduced secretion of the ovarian hormones estrogen and progesterone. Because there is evidence suggesting possible detrimental effects on skeletal health associated with deficiencies in these hormones, a suitable means to asses ovarian hormone concentrations in at risk athletes is needed. The aim of this study was to evaluate a simple, economical means to monitor the ovarian hormone production in athletes, in the setting of intensive training. METHODS: Subjects comprised 14 adolescent rowers, 12 lightweight rowers, and two groups of 10 matched control subjects. Ovarian function was monitored during the competition season by estimation of urinary excretion of estrone glucuronide (E1G) and pregnanediol glucuronide (PdG), enabling the menstrual cycles to be classified as ovulatory or anovulatory. RESULTS: Results indicated 35% and 75% of schoolgirl and lightweight rowers had anovulatory menstrual cycles, respectively. These findings were highlighted by significantly lower excretion of E1G and PdG during phases of intensive training in both the lightweight and schoolgirl rowers, compared with the control subjects. CONCLUSION: It was concluded that the urinary E1G and PdG assays were an effective means to assess the influence of intense training on ovarian hormone concentrations in at risk athletes. It is recommended that this technique be applied more widely as a means of early detection of athletes with low estrogen and progesterone levels, in an attempt to avoid detrimental influences on skeletal health.

A survey of management and economic impact of weeds in dryland cotton cropping systems of subtropical Australia

In dryland cotton cropping systems, the main weeds and effectiveness of management practices were identified, and the economic impact of weeds was estimated using information collected in a postal and a field survey of Southern Queensland and northern New South Wales. Forty-eight completed questionnaires were returned, and 32 paddocks were monitored in early and late summer for weed species and density. The main problem weeds were bladder ketmia (Hibiscus trionum), common sowthistle (Sonchus oleraceus), barnyard grasses (Echinochloa spp.), liverseed grass (Urochloa panicoides) and black bindweed (Fallopia convolvulus), but the relative importance of these differed with crops, fallows and crop rotations. The weed flora was diverse with 54 genera identified in the field survey. Control of weed growth in rotational crops and fallows depended largely on herbicides, particularly glyphosate in fallow and atrazine in sorghum, although effective control was not consistently achieved. Weed control in dryland cotton involved numerous combinations of selective herbicides, several non-selective herbicides, inter-row cultivation and some manual chipping. Despite this, residual weeds were found at 38-59% of initial densities in about 3-quarters of the survey paddocks. The on-farm financial costs of weeds ranged from $148 to 224/ha.year depending on the rotation, resulting in an estimated annual economic cost of $19.6 million. The approach of managing weed populations across the whole cropping system needs wider adoption to reduce the weed pressure in dryland cotton and the economic impact of weeds in the long term. Strategies that optimise herbicide performance and minimise return of weed seed to the soil are needed. Data from the surveys provide direction for research to improve weed management in this cropping system. The economic framework provides a valuable measure of evaluating likely future returns from technologies or weed management improvements.

Fundamental Principles and Rights At Work: Value, Viability, Incidence and Importance as Elements For Economic Progress and Social Justice

Working Paper prepared for the ILO by Maria Luz Vega Ruiz and Daniel Martinez, focusing on the rights at work in Latin America and the Caribbean.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

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.