939 resultados para Acinonyx jubatus, algae, algal bloom, Bayesian network, BN, Botswana, cheetah, conservation, cheetah relocation, DOOBN, dynamic network, free-ranging cheetah population, integrated network, IBNDC, integrated Bayesian network development cycle


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Florida Bay is a unique subtropical estuary that while historically oligotrophic, has been subjected to both natural and anthropogenic stressors, including hurricanes, coastal eutrophication and other impacts. These stressors have resulted in degradation of water quality in the past several decades, most evidenced by reoccurring blooms of the picocyanobacterium Synechococcus spp. Major nutrient inputs consist of freshwater flows to the eastern region from runoff and regulated canal releases, inputs from the Everglades to the central region via Taylor Slough, exchanges with the Gulf of Mexico, which include intermittent Shark River inputs to the western region, stormwater and wastewater from the Florida Keys, and atmospheric deposition. These nutrient inputs have resulted in a transition from strong phosphorus (P) limitation of phytoplankton in the eastern bay to nitrogen (N) limitation in the western bay. Large blooms of Synechococcus were most pronounced in the central bay region, in the area of transition between P and N limitation, in the mid-1990s. Although non-toxic, these blooms, which have continued intermittently through the early 2000s, resulted in significant sea-grass and benthic organism mortalities. A new suite of stressors in 2005, including the passages of Hurricanes Katrina, Rita, and Wilma, additional canal releases, and the initiation of road construction to widen the main roadway leading to the Keys, were correlated with a large Synechococcus bloom in the previously clear, strongly P- limited, northeastern region of the bay. Sustained for 3 years, this bloom was accompanied by a shift from P limitation to N limitation during its course. Nutrient bioassay experiments suggest that this bloom persisted due to the ability of Synechococcus to access organic N and P sources, microbial and geochemical cycling of organic and inorganic nutrients in the water column and between the water column and sediments (both suspended particles and benthos), and decreased grazing by benthic fauna due to their die-off.

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Harmful algal blooms can adversely affect fish communities, though their impacts are highly context-dependent and typically differ between fish species. Various approaches, comprising univariate and multivariate analyses and multimetric Fish Community Indices (FCI), were employed to characterise the perceived impacts of a Karlodinium veneficum bloom on the fish communities and ecological condition of the Swan Canning Estuary, Western Australia. The combined evidence suggests that a large proportion of the more mobile fish species in the offshore waters of the bloom-affected area relocated to other regions during the bloom. This was indicated by marked declines in mean species richness, catch rates and FCI scores in the bloom region but concomitant increases in these characteristics in more distal regions, and by pronounced and atypical shifts in the pattern of inter-regional similarities in fish community composition during the bloom. The lack of any significant changes among the nearshore fish communities revealed that bloom impacts were less severe there than in deeper, offshore waters. Nearshore habitats, which generally are in better ecological condition than adjacent offshore waters in this system, may provide refuges for fish during algal blooms and other perturbations, mirroring similar observations of fish avoidance responses to such stressors in estuaries worldwide.

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Harmful algal blooms can adversely affect fish communities, though their impacts are highly context-dependent and typically differ between fish species. Various approaches, comprising univariate and multivariate analyses and multimetric Fish Community Indices (FCI), were employed to characterise the perceived impacts of a Karlodinium veneficum bloom on the fish communities and ecological condition of the Swan Canning Estuary, Western Australia. The combined evidence suggests that a large proportion of the more mobile fish species in the offshore waters of the bloom-affected area relocated to other regions during the bloom. This was indicated by marked declines in mean species richness, catch rates and FCI scores in the bloom region but concomitant increases in these characteristics in more distal regions, and by pronounced and atypical shifts in the pattern of inter-regional similarities in fish community composition during the bloom. The lack of any significant changes among the nearshore fish communities revealed that bloom impacts were less severe there than in deeper, offshore waters. Nearshore habitats, which generally are in better ecological condition than adjacent offshore waters in this system, may provide refuges for fish during algal blooms and other perturbations, mirroring similar observations of fish avoidance responses to such stressors in estuaries worldwide.

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Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.

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Regional safety program managers face a daunting challenge in the attempt to reduce deaths, injuries, and economic losses that result from motor vehicle crashes. This difficult mission is complicated by the combination of a large perceived need, small budget, and uncertainty about how effective each proposed countermeasure would be if implemented. A manager can turn to the research record for insight, but the measured effect of a single countermeasure often varies widely from study to study and across jurisdictions. The challenge of converting widespread and conflicting research results into a regionally meaningful conclusion can be addressed by incorporating "subjective" information into a Bayesian analysis framework. Engineering evaluations of crashes provide the subjective input on countermeasure effectiveness in the proposed Bayesian analysis framework. Empirical Bayes approaches are widely used in before-and-after studies and "hot-spot" identification; however, in these cases, the prior information was typically obtained from the data (empirically), not subjective sources. The power and advantages of Bayesian methods for assessing countermeasure effectiveness are presented. Also, an engineering evaluation approach developed at the Georgia Institute of Technology is described. Results are presented from an experiment conducted to assess the repeatability and objectivity of subjective engineering evaluations. In particular, the focus is on the importance, methodology, and feasibility of the subjective engineering evaluation for assessing countermeasures.

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This study aims to explain the entrepreneurial processes as developments of entrepreneurial networks. As a theoretical framework, this study adopts the theory of experimentally organized economy and competence blocs. As suggested by this theory, entrepreneurs select profitable innovations and commercialise them. Through logistic regressions on the subjective and objective dependent variables, we find that nascent firms’ various activities to network customers, innovators, investors, and employees are positively associated with the business emergence. This study identifies the roles of entrepreneurs and the other actors in the entrepreneurial processes.

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This research focuses on the design and implementation of a tool to speed-up the development and deployment of heterogeneous wireless sensor networks. The THAWS (Tyndall Heterogeneous Automated Wireless Sensors) tool can be used to quickly create and configure application-specific sensor networks. THAWS presents the user with a choice of options, in order to characterise the desired functionality of the network. With this information, THAWS generates the necessary code from pre-written templates and well-tested, optimized software modules. This is then automatically compiled to form binary files for each node in the network. Wireless programming of the network completes the task of targeting the wireless network towards a specific sensing application. THAWS is an adaptable tool that works with both homogeneous and heterogeneous networks built from wireless sensor nodes that have been developed in the Tyndall National Institute.