Replacing prelinguistic behaviors with functional communication

This study evaluated the effectiveness of a teacher-implemented intervention package designed to replace prelinguistic behaviors with functional communication. Four young children with autism participated in a multiple-probe design across three communicative functions. Initially, three existing communication functions were selected for each child. Next, the existing prelinguistic behaviors that the children used to achieve these functions were identified. Replacement forms that were considered more recognizable and symbolic were defined to achieve these same functions. After a baseline phase, teachers received inservice training, consultation, and feedback on how to encourage, acknowledge, and respond to the replacement forms. During intervention, the replacement forms increased and prelinguistic behaviors decreased in most cases. The results suggested that the teacher-implemented intervention was effective in replacing prelinguistic behaviors with alternative forms of functional communication.

Sequestration of carbon by soil

Soil carbon is a major component of the terrestrial carbon cycle. The soils of the world contain more carbon than the combined total amounts occurring in vegetation and the atmosphere. Consequently, soils are a major reservoir of carbon and an important sink. Because of the relatively long period of time that carbon spends within the soil and is thereby withheld from the atmosphere, it is often referred to as being sequestered. Increasing the capacity of soils to sequester C provides a partial, medium-term countermeasure to help ameliorate the increasing CO2 levels in the atmosphere arising from fossil fuel burning and land clearing. Such action will also help to alleviate the environmental impacts arising from increasing levels of atmospheric CO2. The C sequestration potential of any soil depends on its capacity to store resistant plant components in the medium term and to protect and accumulate the humic substances (HS) formed from the transformations or organic materials in the soil environment. The sequestration potential of a soil depends on the vegetation it supports, its mineralogical composition, the depth of the solum, soil drainage, the availability of water and air, and the temperature of the soil environment. The sequestration potential also depends on the chemical characteristics of the soil organic matter and its ability to resist microbial decomposition. When accurate information for these features is incorporated in model systems, the potentials of different soils to sequester C can be reliably predicted. It is encouraging to know that improved soil and crop management systems now allow field yields to be maintained and soil C reserves to be increased, even for soils with depleted levels of soil C. Estimates of the soil C sequestration potential are discussed. Inevitably HS are the major components of the additionally sequestered C. It will be important to know more about the compositions and associations of these substances in the soil if we are able to predict reasonably accurately the ability of any soil type to sequester C in different cropping and soil management systems.

Isolation of Gemmata-like and Isosphaera-like planctomycete bacteria from soil and freshwater

New cultured strains of the planctomycete division (order Planctomycetales) of the domain Bacteria related to species in the genera Gemmata and Isosphaera were isolated from soil, freshwater, and a laboratory ampicillin solution. Phylogenetic analysis of the 16S rRNA gene from eight representative isolates showed that all the isolates were members of the planctomycete division. Six isolates clustered with Gemmata obscuriglobus and related strains, while two isolates clustered with Isosphaera pallida. A double-membrane-bounded nucleoid was observed in Gemmata-related isolates but not in Isosphaera-related isolates, consistent with the ultrastructures of existing species of each genus. Two isolates from this study represent the first planctomycetes successfully cultivated from soil.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.