Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques

Information on distribution and relative abundance of species is integral to sustainable management, especially if they are to be harvested for subsistence or commerce. In northern Australia, natural landscapes are vast, centers of population few, access is difficult, and Aboriginal resource centers and communities have limited funds and infrastructure. Consequently defining distribution and relative abundance by comprehensive ground survey is difficult and expensive. This highlights the need for simple, cheap, automated methodologies to predict the distribution of species in use, or having potential for use, in commercial enterprise. The technique applied here uses a Geographic Information System (GIS) to make predictions of probability of occurrence using an inductive modeling technique based on Bayes' theorem. The study area is in the Maningrida region, central Arnhem Land, in the Northern Territory, Australia. The species examined, Cycas arnhemica and Brachychiton diversifolius, are currently being 'wild harvested' in commercial trials, involving sale of decorative plants and use as carving wood, respectively. This study involved limited and relatively simple ground surveys requiring approximately 7 days of effort for each species. The overall model performance was evaluated using Cohen's kappa statistics. The predictive ability of the model for C. arnhemica was classified as moderate and for B. diversifolius as fair. The difference in model performance can be attributed to the pattern of distribution of these species. C. arnhemica tends to occur in a clumped distribution due to relatively short distance dispersal of its large seeds and vegetative growth from long-lived rhizomes, while B. diversifolius seeds are smaller and more widely dispersed across the landscape. The output from analysis predicts trends in species distribution that are consistent with independent on-site sampling for each species and therefore should prove useful in gauging the extent of resource availability. However, some caution needs to be applied as the models tend to over predict presence which is a function of distribution patterns and of other variables operating in the landscape such as fire histories which were not included in the model due to limited availability of data.     

Seasonal temperatures have more influence than nitrogen fertilizer rates on cucumber yield and nitrogen uptake in a double cropping system

Two-year greenhouse cucumber experiments were conducted to investigate seasonal effects on fruit yield, dry matter allocation, and N uptake in a double-cropping system with different fertilizer management. Seasonal effects were much greater than fertilizer effects, and winter-spring (WS) cucumber attained higher fruit yields and N uptake than autumn-winter (AW) cucumber due to lower cumulative air temperatures during fruit maturation in the AW season. Fertilizer N application and apparent N loss under recommended N management (Nmr) decreased by 40-78% and 33-48% without yield loss compared to conventional N management (Nmt) over four growing seasons. However, there were no seasonal differences in N recommendations, taking into consideration seasonal differences in crop N demand, critical nutrient supply in the root zone and N mineralization rate.     

Thoughts concerning the economic valuation of landscapes

The incorporation of economic thinking into the valuation of landscapes is still relatively new. It is an approach that yields valuable new insights and can help with prioritizing the use of scarce resources to improve and/or preserve landscapes. This paper explores and discusses the uses and limitations of economic valuation of landscapes from market failure, policy process, and theoretical and philosophical perspectives.     

The occurrence of heavy metals in irrigated and non-irrigated arable soils,NW Albania

The study analysed the content of heavy metals in surface soil and sediment samples from the Bregu i Matit Plain in NW Albania in relation to irrigation in order to evaluate the soil pollution and the potential risk to human health. Evaluation of soil pollution was performed using the enrichment factor and geo-accumulation index. Contents of cadmium, chromium and nickel of irrigated soils were significantly higher than those of non-irrigated soil, while contents of lead (in three of the irrigated locations), zinc and arsenic (in one of the irrigated locations) were significantly lower. Correlation analysis (CA) and principal component analysis (PCA) indicated that the primary source of the first three metals was irrigation, and the last three metals were originated from other anthropic sources, like the use of chemicals, etc. Enrichment factor (E _f) calculation showed that irrigated soils were most enriched in cadmium, chromium, copper and nickel. Index of geo-accumulation (I _geo) revealed that arable soils of Bregu i Matit are unpolluted to moderately polluted with cadmium, chromium, copper and zinc and moderately to strongly polluted with nickel and arsenic. The presence of heavy metals in the studied soils indicates a potential risk of transfer of these elements in the food chain. Therefore, further studies on the speciation of heavy metals in the studied soils in order to evaluate their mobility are needed.     

Lead traceability along soil-melliferous flora-bee family-apiary products chain

Indirect measures were considered to study the lead transfer along the soil-melliferous flora-bee family-apiary products food chain. The concentrations of total and bioavailable lead in the soil were first investigated. Next, the lead level in different organs of melliferous flora and subsequently in the bee family and apiary products was measured. The results indicate a decrease in contamination as follows: honeybees > drones > propolis > wax > bee larvae > honey > royal jelly. The statistical analysis highlights the "lead pollution bioindicator" role of honeybees, honey and propolis. The risk factor parameter allows the prediction of the most impacted month and the least impacted of the melliferous season.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

Workplace aerosol mass concentration measurement using optical particle counters

Direct-reading aerosol measurement usually uses the optical properties of airborne particles to detect and measure particle concentration. In the case of occupational hygiene, mass concentration measurement is often required. Two aerosol monitoring methods are based on the principle of light scattering: optical particle counting (OPC) and photometry. The former analyses the light scattered by a single particle, the latter by a cloud of particles. Both methods need calibration to transform the quantity of scattered light detected into particle concentration. Photometers are simpler to use and can be directly calibrated to measure mass concentration. However, their response varies not only with aerosol concentration but also with particle size distribution, which frequently contributes to biased measurement. Optical particle counters directly measure the particle number concentration and particle size that allows assessment of the particle mass provided the particles are spherical and of known density. An integrating algorithm is used to calculate the mass concentration of any conventional health-related aerosol fraction. The concentrations calculated thus have been compared with simultaneous measurements by conventional gravimetric sampling to check the possibility of field OPC calibration with real workplace aerosols with a view to further monitoring particle mass concentration. Aerosol concentrations were measured in the food industry using the OPC GRIMM? 1.108 and the CIP 10-Inhalable and CIP 10-Respirable (ARELCO?) aerosol samplers while meat sausages were being brushed and coated with calcium carbonate. Previously, the original OPC inlet had been adapted to sample inhalable aerosol. A mixed aerosol of calcium carbonate and fungi spores was present in the workplace. The OPC particle-size distribution and an estimated average particle density of both aerosol components were used to calculate the mass concentration. The inhalable and respirable aerosol fractions calculated from the OPC data are closely correlated with the results of the particle size-selective sampling using the CIP 10. Furthermore, the OPC data allow calculation of the thoracic fraction of workplace aerosol (not measured by sampling), which is interesting in the presence of allergenic particles like fungi spores. The results also show that the modified COP inlet adequately samples inhalable aerosol in the range of workplace particle-size distribution.