3 resultados para Ecosystem engineering
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Results from the humid tropics of Australia demonstrate that diverse plantations can achieve greater productivity than monocultures. We found that increases in both the observed species number and the effective species richness were significantly related to increased levels of productivity as measured by stand basal area or mean individual tree basal area. Four of five plantation species were more productive in mixtures with other species than in monocultures, offering on average, a 55% increase in mean tree basal area. A general linear model suggests that species richness had a significant effect on mean individual tree basal area when environmental variables were included in the model. As monoculture plantations are currently the preferred reforestation method throughout the tropics these results suggest that significant productivity and ecological gains could be made if multi-species plantations are more broadly pursued.
Resumo:
There are many potential bioremediation approaches that may be suitable for prawn farms in Queensland. Although most share generally accepted bioremediation principles, advocacy for different methods tends to vary widely. This diversity of approach is particularly driven by the availability and knowledge of functional species at different localities around the world. In Australia, little is known about the abilities of many native species in this regard, and translocation and biosecurity issues prevent the use of exotic species that have shown potential in other countries. Species selected must be tolerant of eutrophic conditions and ecological shifts, because prawn pond nutrient levels and pathways can vary with different assemblages of autotrophic and heterotrophic organisms. Generally, they would be included in a constructed ecosystem because of their functional contributions to nutrient cycling and uptake, and to create nutrient sinks in forms of harvestable biomass. Wide salinity, temperature and water quality tolerances are also valuable attributes for selected species due to the sometimes-pronounced effects of environmental extremes, and to provide over-wintering options and adequate safety margins in avoiding mass mortalities. To practically achieve these bioremediation polycultures on a large scale, and in concert with the operations of a prawn farm, methods involving seed production, stock management, and a range of other farm engineering and product handling systems need to be reliably achievable and economically viable. Research funding provided by the Queensland Government through the Aquaculture Industry Development Initiative (AIDI) 2002-04 has enabled a number of technical studies into biological systems to treat prawn farm effluent for recirculation and improved environmental sustainability. AIDI bioremediation research in southern Queensland was based at the Bribie Island Aquaculture Research Centre (BIARC), and was conducted in conjunction with AIDI genetics and selection research, and a Natural Heritage Trust (NHT) funded program (Coast and Clean Seas Project No.717757). This report compilation provides a summary of some of the work conducted within these programs.
Resumo:
This study examines the application of digital ecosystems concepts to a biological ecosystem simulation problem. The problem involves the use of a digital ecosystem agent to optimize the accuracy of a second digital ecosystem agent, the biological ecosystem simulation. The study also incorporates social ecosystems, with a technological solution design subsystem communicating with a science subsystem and simulation software developer subsystem to determine key characteristics of the biological ecosystem simulation. The findings show similarities between the issues involved in digital ecosystem collaboration and those occurring when digital ecosystems interact with biological ecosystems. The results also suggest that even precise semantic descriptions and comprehensive ontologies may be insufficient to describe agents in enough detail for use within digital ecosystems, and a number of solutions to this problem are proposed.