4 resultados para Job Demands-Resources model

em eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry


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Diel activity patterns of tropical fish assemblages in turbid, mangrove-dominated estuaries remain largely undocumented, leading to uncertainty about ecological processes in these systems. To capture active fishes by day and night, gill nets were set perpendicular to mangrove shorelines, in six northeastern Australian estuaries during 13 bimonthly trips. Fish were sampled with eight large mesh (102-151 mm) nets, set for 6 hrs (1500-2100), and checked hourly (1146 day, 635 dusk, 872 night checks). Four smaller mesh (19-51 mm) nets were also set for 1 hr before and after sunset (77 day, 78 night checks). Of 157 total species, 22 were netted exclusively before sunset and 47 exclusively after sunset. All of the top 26 species were present both day and night, but of these, 46% were primarily nocturnal (diel index > 0.65). An average of 77.2 fish hr−1 were netted by day vs 171.4 by night. Within the 400 km coastal region, assemblages differed between two northern wave-dominated (WD) estuaries and four southern tide-dominated ('I'D) estuaries. In all six estuaries Lates calcarifer (Bloch, 1790) dominated night assemblages. In 'I'D estuaries, night assemblages were also dominated by Thryssa hamiltoni Gray, 1835 and Eleutheronema tetradactylum (Shaw, 1804); while in WD estuaries Herklotsichthys castelnaui (Ogilby, 1897), Leiognathus equulus (Forsskål, 1775), and Megalops cyprinoids (Broussonet, 1782) were dominant at night. Nocturnal species included planktivores and carnivores, while daytime assemblages were dominated by detritivores (Mugillidae). Higher night catch rates are attributed to increased activity by mobile fishes moving from mangrove to adjacent habitats to forage, especially immediately post-sunset. Although day-night diets and forage resources have yet to be compared in mangrove systems, previously unrecognized trophic relationships involving variation in diel activity among important fishery species (Centropomidae, polynemidae, Carangidae) and their prey may be key ecological processes in these tropical mangrove estuaries. A proposed hypothesis explaining diel variation in mangrove fish assemblages of tropical estuaries is presented through a conceptual model.

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A simulation model that combines biological, search and economic components is applied to the eradication of a Miconia calvescens infestation at El Arish in tropical Queensland, Australia. Information on the year M. calvescens was introduced to the site, the number of plants controlled and the timing of control, is used to show that currently there could be M. calvescens plants remaining undetected at the site, including some mature plants. Modelling results indicate that the eradication programme has had a significant impact on the population of M. calvescens, as shown by simulated results for uncontrolled and controlled populations. The model was also used to investigate the effect of changing search effort on the cost of and time to eradication. Control costs were found to be negligible over all levels of search effort tested. Importantly, results suggest eradication may be achieved within several decades, if resources are increased slightly from their current levels and if there is a long-term commitment to funding the eradication programme.

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Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.

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We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.