Characterizing a tropical deforestation wave: a dynamic spatial analysis of a deforestation hotspot in the Colombian Amazon

Tropical deforestation is the major contemporary threat to global biodiversity, because a diminishing extent of tropical forests supports the majority of the Earth's biodiversity. Forest clearing is often spatially concentrated in regions where human land use pressures, either planned or unplanned, increase the likelihood of deforestation. However, it is not a random process, but often moves in waves originating from settled areas. We investigate the spatial dynamics of land cover change in a tropical deforestation hotspot in the Colombian Amazon. We apply a forest cover zoning approach which permitted: calculation of colonization speed; comparative spatial analysis of patterns of deforestation and regeneration; analysis of spatial patterns of mature and recently regenerated forests; and the identification of local-level hotspots experiencing the fastest deforestation or regeneration. The colonization frontline moved at an average of 0.84 km yr(-1) from 1989 to 2002, resulting in the clearing of 3400 ha yr(-1) of forests beyond the 90% forest cover line. The dynamics of forest clearing varied across the colonization front according to the amount of forest in the landscape, but was spatially concentrated in well-defined 'local hotspots' of deforestation and forest regeneration. Behind the deforestation front, the transformed landscape mosaic is composed of cropping and grazing lands interspersed with mature forest fragments and patches of recently regenerated forests. We discuss the implications of the patterns of forest loss and fragmentation for biodiversity conservation within a framework of dynamic conservation planning.

In vitro antibacterial activity of Australian native herb extracts against food-related bacteria

The antibacterial activities of water, ethanol and hexane extracts of five Australian herbs (Backhousia citriodora, Anetholea anisata, Eucalyptus staigerana, Eu. olida and Prostanthera incisa) against seven food-related bacteria (Enterococcus faecalis, Escherichia coli, Listeria monocytogenes, Pseudomonas aeruginosa, Salmonella Enteritidis, Sal. Typhimurium and Staphylococcus aureus) were determined by the microtitre broth microdilution assay. The water extracts of all the herbs displayed no or low antimicrobial activity against all of the bacteria tested with the exception of S. aureus. Relatively high levels of activity (minimum inhibitory concentrations of 125-15.6 mu g ml(-1)) against this pathogen were present in water extracts from all herbs except P. incisa. The ethanol and hexane extracts of all herbs displayed some activity against a number of the bacteria tested, with no one particular herb displaying an obviously higher level or range of activity. Staphylococcus aureus proved to be the most sensitive of the bacteria tested against the solvent extracts with all extracts displaying activity ranging from 125 to 7.8 mu g ml(-1), while E. coli and L. monocytogenes, on the other hand, proved the least sensitive with only five of 15 herb/extract combinations displaying any activity against these pathogens. The extracts of the Australian native herbs examined in this study have potential for application in foods to increase shelf-life or promote safety. (c) 2005 Elsevier Ltd. All rights reserved.

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.