6 resultados para Distance Matrix

em eResearch Archive - Queensland Department of Agriculture


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Mellitochory, seed dispersal by bees, has been implicated in long-distance dispersal of the tropical rain forest tree, Corymbia torelliana (Myrtaceae). We examined natural and introduced populations of C. torelliana for 4 years to determine the species of bees that disperse seeds, and the extent and distance of seed dispersal. The mechanism of seed dispersal by bees was also investigated, including fruit traits that promote dispersal, foraging behaviour of bees at fruits, and the fate of seeds. The fruit structure of C. torelliana, with seed presented in a resin reward, is a unique trait that promotes seed dispersal by bees and often results in long-distance dispersal. We discovered that a guild of four species of stingless bees, Trigona carbonaria, T. clypearis, T. sapiens, and T. hockingsi, dispersed seeds of C. torelliana in its natural range. More than half of the nests found within 250 m of fruiting trees had evidence of seed transport. Seeds were transported minimum distances of 20-220 m by bees. Approximately 88% of seeds were dispersed by gravity but almost all fruits retained one or two seeds embedded in resin for bee dispersal. Bee foraging for resin peaked immediately after fruit opening and corresponded to a peak of seed dispersal at the hive. There were strong correlations between numbers of seeds brought in and taken out of each hive by bees (r = 0.753-0.992, P < 0.05), and germination rates were 95 ± 5%. These results showed that bee-transported seeds were effectively dispersed outside of the hive soon after release from fruits. Seed dispersal by bees is a non-standard dispersal mechanism for C. torelliana, as most seeds are dispersed by gravity before bees can enter fruits. However, many C. torelliana seeds are dispersed by bees, since seeds are retained in almost all fruits, and all of these are dispersed by bees.

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Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

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Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

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The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

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Ammonia (NH3) can accumulate in high density cattle accommodation during live export shipments and could potentially threaten the animals' health and welfare. The effects of 4 NH3 concentrations, control (<8), 15, 30, and 45 ppm, on the physiology and behavior of steers were recorded. The animals were held for 12 d under a micro-climate and stocking density similar to shipboard conditions experienced on voyages from Australia to the Middle East during the northern hemispheric summer. In bronchoalveolar lavage samples, ammonia increased (P < 0.05) macrophage activity in proportion to NH3 concentration and it increased (P < 0.05) neutrophil percentage at 30 and 45 ppm, indicating active pulmonary inflammation. It also increased (P < 0.05) lacrimation, nasal secretions and coughing, particularly at 45 ppm, indicating that the NH3 was irritating the mucous membranes of the eyes, nasal cavity and respiratory tract. Ammonia had no effect (P > 0.05) on hematological parameters or body weight. Twenty-eight days after exposure to NH3, the steers' pulmonary macrophage activity and neutrophil levels had returned to normal. It was concluded that ammonia concentrations of 30 and 45 ppm induced temporary inflammatory responses which indicate an adverse effect on the welfare of steers.

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Banana bunchy top virus (BBTV; family Nanoviridae, genus Babuvirus) is a multi-component single-stranded DNA virus, which infects banana plants in many regions of the world, often resulting in large-scale crop losses. Weanalyzed 171 banana leaf samples from fourteen countries and recovered, cloned, and sequenced 855 complete BBTV components including ninety-four full genomes. Importantly, full genomes were determined from eight countries, where previously no full genomes were available (Samoa, Burundi, Republic of Congo, Democratic Republic of Congo, Egypt, Indonesia, the Philippines, and the USA [HI]). Accounting for recombination and genome component reassortment, we examined the geographic structuring of global BBTV populations to reveal that BBTV likely originated in Southeast Asia, that the current global hotspots of BBTV diversity are Southeast Asia/Far East and India, and that BBTV populations circulating elsewhere in the world have all potentially originated from infrequent introductions. Most importantly, we find that rather than the current global BBTV distribution being due to increases in human-mediated movements of bananas over the past few decades, it is more consistent with a pattern of infrequent introductions of the virus to different parts of the world over the past 1,000 years.