609 resultados para wildlife damage management


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Aim Non-radiographic axial spondyloarthritis (nr-axSpA) is axial inflammatory arthritis where plain radiographic damage is not evident. An unknown proportion of these patients will progress to ankylosing spondylitis (AS). The increasing recognition of nr-axSpA has been greatly assisted by the widespread use of magnetic resonance imaging. The aim of this article was to construct a set of consensus statements based on a literature review to guide investigation and promote best management of nr-axSpA. Methods A literature review using Medline was conducted covering the major investigation modalities and treatment options available. A group of rheumatologists and a radiologist with expertise in investigation and management of SpA reviewed the literature and formulated a set of consensus statements. The Grade system encompassing the level of evidence and strength of recommendation was used. The opinion of a patient with nr-axSpA and a nurse experienced in the care of SpA patients was also sought and included. Results The literature review found few studies specifically addressing nr-axSpA, or if these patients were included, their results were often not separately reported. Fourteen consensus statements covering investigation and management of nr-axSpA were formulated. The level of agreement was high and ranged from 8.1 to 9.8. Treatment recommendations vary little with established AS, but this is primarily due to the lack of available evidence on the specific treatment of nr-axSpA. Conclusion The consensus statements aim to improve the diagnosis and management of nr-axSpA. We aim to raise awareness of this condition by the public and doctors and promote appropriate investigation and management.

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Internationally, marine biodiversity conservation objectives are having an increasing influence on the management of commercial fisheries. While this is largely being implemented through Marine Protected Areas (MPAs) other management measures, such as market based instruments (MBIs), have proved to be effective at managing target species catch in fisheries and reducing environmental impacts in industries such as mining and tourism. Market-based management measures aim to mitigate the impacts of activities by better aligning the incentives their participants face with the objectives of management, changing their behavior as a consequence. In this paper, we review the potential of MBIs as management tools to mitigate undesirable environmental impacts associated with commercial fishing. Where they exist, examples of previous applications are described and the factors that influence their applicability and effectiveness are discussed. Several fishing methods and impacts are considered and suggest that whilst no single approach is most appropriate in all circumstances either replacing or complementing existing management arrangements with MBIs has the potential to improve environmental performance. This has a number of implications. From the environmental perspective they should enable levels of undesirable impacts such as damage to sensitive habitat or the bycatch of protected species of turtles, marine mammals, and seabirds to be reduced. The increased flexibility MBIs allow industry when developing solutions also has the potential to reduce costs to both the industry and managers, improving the cost-effectiveness of regulation as a result. Further, in the increasingly relevant case of MPAs the need for publicly funded compensation, often paid to industry when vessels are excluded from grounds, may also be significantly reduced if improved environmental performance makes it possible for some industry members to continue operating.

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Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

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This paper examines empirically the relative influence of the degree of endangerment of wildlife species and their stated likeability on individuals' allocation of funds for their conservation. To do this, it utilises data obtained from the IUCN Red List, and likeability and fund allocation data obtained from two serial surveys of a sample of the Australian public who were requested to assess 24 Australian wildlife species from three animal classes: mammals, birds and reptiles. Between the first and second survey, respondents were provided with extra information about the focal species. This information resulted in the dominance of endangerment as the major influence on the allocation of funding of respondents for the conservation of the focal wildlife species. Our results throw doubts on the proposition in the literature that the likeability of species is the dominant influence on willingness to pay for conservation of wildlife species. Furthermore, because the public's allocation of fund for conserving wildlife species seems to be more sensitive to information about the conservation status of species than to factors influencing their likeability, greater attention to providing accurate information about the former than the latter seems justified. Keywords: Conservation of wildlife species; Contingent valuation; Endangerment of species; Likeability of species; Willingness to pay

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Developments in information technology will drive the change in records management; however, it should be the health information managers who drive the information management change. The role of health information management will be challenged to use information technology to broker a range of requests for information from a variety of users, including he alth consumers. The purposes of this paper are to conceptualise the role of health information management in the context of a technologically driven and managed health care environment, and to demonstrat e how this framework has been used to review and develop the undergraduate program in health information management at the Queensland University of Technology.