32 resultados para 010401 Applied Statistics

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


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Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .

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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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Management of the commercial harvest of kangaroos relies on quotas set annually as a proportion of regular estimates of population size. Surveys to generate these estimates are expensive and, in the larger states, logistically difficult; a cheaper alternative is desirable. Rainfall is a disappointingly poor predictor of kangaroo rate of increase in many areas, but harvest statistics (sex ratio, carcass weight, skin size and animals shot per unit time) potentially offer cost-effective indirect monitoring of population abundance (and therefore trend) and status (i.e. under-or overharvest). Furthermore, because harvest data are collected continuously and throughout the harvested areas, they offer the promise of more intensive and more representative coverage of harvest areas than aerial surveys do. To be useful, harvest statistics would need to have a close and known relationship with either population size or harvest rate. We assessed this using longterm (11-22 years) data for three kangaroo species (Macropus rufus, M. giganteus and M. fuliginosus) and common wallaroos (M. robustus) across South Australia, New South Wales and Queensland. Regional variation in kangaroo body size, population composition, shooter efficiency and selectivity required separate analyses in different regions. Two approaches were taken. First, monthly harvest statistics were modelled as a function of a number of explanatory variables, including kangaroo density, harvest rate and rainfall. Second, density and harvest rate were modelled as a function of harvest statistics. Both approaches incorporated a correlated error structure. Many but not all regions had relationships with sufficient precision to be useful for indirect monitoring. However, there was no single relationship that could be applied across an entire state or across species. Combined with rainfall-driven population models and applied at a regional level, these relationships could be used to reduce the frequency of aerial surveys without compromising decisions about harvest management.

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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We examined the effect of surface-applied treatments on the above-ground decay resistance of the tenon of mortice-and-tenon timber joints designed to simulate joinery that is exposed to the weather. Joints made from untreated radiata pine, Douglas-fir, brush box, spotted gum and copper-chrome-arsenic (CCA) treated radiata pine were exposed to the weather for 9 y on above-ground racks at five sites throughout eastern Australia. Results indicate (1) a poorly maintained external paint film generally accelerated decay, (2) a brush coat of water-repellent preservative inside the joints often extended serviceability (in some cases by a factor of up to seven times that of untreated joints) and (3) the level of protection provided by a coat of primer applied inside the joint varied and in most cases was not as effective as the water-repellent preservative treatment.

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In recent years, there have been significant developments in climate science relevant to agriculture and natural resource management. Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. Consideration of climate change further increases the need for improved management strategies. While climate risk extension activities have kept pace with advances in climate science, a national review of the Vocational Education and Training system in Australia in relation to "weather and climate" showed that these topics were "poorly represented" at the management level in the Australian Qualifications Framework, and needed increased emphasis. Consequently, a new Unit of Competency concerning management of climatic risk was developed and accredited to address this deficiency. The objective of the unit was to build knowledge and skills for better management of climate variability via the elements of surveying climatic and enterprise data; analysing climatic risks and opportunities; and developing climatic risk management strategies. This paper describes establishment of a new unit for vocational education that is designed to harness recent developments in applied climate science for better management of Australia's highly variable climate. The main benefits of the new unit of competency, "Developing climatic risk management strategies,"were seen as improving decisions in climate and agriculture, and reducing climate risk exposure to enhance sustainable agriculture. The educational unit is now within the scope of agricultural colleges, universities, and registered training organisations as an accredited unit.

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Quantifying the local crop response to irrigation is important for establishing adequate irrigation management strategies. This study evaluated the effect of irrigation applied with subsurface drip irrigation on field corn (Zea mays L.) evapotranspiration (ETc), yield, water use efficiencies (WUE = yield/ETc, and IWUE = yield/irrigation), and dry matter production in the semiarid climate of west central Nebraska. Eight treatments were imposed with irrigation amounts ranging from 53 to 356 mm in 2005 and from 22 to 226 mm in 2006. A soil water balance approach (based on FAO-56) was used to estimate daily soil water and ETc. Treatments resulted in seasonal ETc of 580-663 mm and 466-656 mm in 2005 and 2006, respectively. Yields among treatments differed by as much as 22% in 2005 and 52% in 2006. In both seasons, irrigation significantly affected yields, which increased with irrigation up to a point where irrigation became excessive. Distinct relationships were obtained each season. Yields increased linearly with seasonal ETc (R 2 = 0.89) and ETc/ETp (R 2 = 0.87) (ETp = ETc with no water stress). The yield response factor (ky), which indicates the relative reduction in yield to relative reduction in ETc, averaged 1.58 over the two seasons. WUE increased non-linearly with seasonal ETc and with yield. WUE was more sensitive to irrigation during the drier 2006 season, compared with 2005. Both seasons, IWUE decreased sharply with irrigation. Irrigation significantly affected dry matter production and partitioning into the different plant components (grain, cob, and stover). On average, the grain accounted for the majority of the above-ground plant dry mass (≈59%), followed by the stover (≈33%) and the cob (≈8%). The dry mass of the plant and that of each plant component tended to increase with seasonal ETc. The good relationships obtained in the study between crop performance indicators and seasonal ETc demonstrate that accurate estimates of ETc on a daily and seasonal basis can be valuable for making tactical in-season irrigation management decisions and for strategic irrigation planning and management.

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Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals under the influence of humankind. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. International Society for Applied Ethology (ISAE) Special Issue 2004.

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Welcome to the latest collection of papers selected from the International Society for Applied Ethology's (ISAE's) annual congress. The ISAE is a multi-faceted scientific society that supports applied research on animals that are managed by humans. Every year, we aim to invite congress participants who have submitted papers, plenary talks, run workshops, or presented the memorial lecture on theoretical, review or discussion papers of topical interest to contribute to the Special Issue. These papers are peer-reviewed before being published here in Applied Animal Behaviour Science. This year, we have a variety of papers to bring to your attention. The David Wood-Gush Memorial lecture, the keynote address of the congress, was given by Shigeru Watanabe on animal cognition and welfare. His paper highlights how animal's sensory capabilities relate to their welfare. On the topic of human–animal bonds, Stine Christiansen and Björn Forkman explore how animal welfare is assessed in a veterinary context, and how those assessments might be improved by ethologists. Yoshie Kakuma and co-authors report on the discussions from a workshop on the welfare of working and companion dogs in five different countries. Based on their plenary lectures, Michael Cockram discusses the factors that affect farmed animals during road transport and how these might contribute in making decisions to restrict journey times, while Clive Phillips and co-author Danica Peck examine how personality influences the behaviour and interactions between zoo-housed tigers and their keepers. We hope you enjoy these papers. Our sincere thanks go to both the authors and referees, without whom these special issues would not be possible. A selection of papers from the 39th International Congress of the International Society for Applied Ethology (ISAE), Tokyo, Japan, August 2005.

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Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

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Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

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The fate of nitrogen (N) applied in biosolids was investigated in a forage production system on an alluvial clay loam soil in south-eastern Queensland, Australia. Biosolids were applied in October 2002 at rates of 6, 12, 36, and 54dryt/ha for aerobically digested biosolids (AE) and 8, 16, 48, and 72dryt/ha for anaerobically digested biosolids (AN). Rates were based on multiples of the Nitrogen Limited Biosolids Application rate (0.5, 1, 3, and 4.5NLBAR) for each type of biosolid. The experiment included an unfertilised control and a fertilised control that received multiple applications of synthetic fertiliser. Forage sorghum was planted 1 week after biosolids application and harvested 4 times between December 2002 and May 2003. Dry matter production was significantly greater from the biosolids-treated plots (21-27t/ha) than from the unfertilised (16t/ha) and fertilised (18t/ha) controls. The harvested plant material removed an extra 148-488kg N from the biosolids-treated plots. Partial N budgets were calculated for the 1NLBAR and 4.5NLBAR treatments for each biosolids type at the end of the crop season. Crop removal only accounted for 25-33% of the applied N in the 1NLBAR treatments and as low as 8-15% with 4.5NLBAR. Residual biosolids N was predominantly in the form of organic N (38-51% of applied biosolids N), although there was also a significant proportion (10-23%) as NO3-N, predominantly in the top 0.90m of the soil profile. From 12 to 29% of applied N was unaccounted for, and presumed to be lost as gaseous nitrogen and/or ammonia, as a consequence of volatilisation or denitrification, respectively. In-season mineralisation of organic N in biosolids was 43-59% of the applied organic N, which was much greater than the 15% (AN)-25% (AE) expected, based on current NLBAR calculation methods. Excessive biosolids application produced little additional biomass but led to high soil mineral N concentrations that were vulnerable to multiple loss pathways. Queensland Guidelines need to account for higher rates of mineralisation and losses via denitrification and volatilisation and should therefore encourage lower application rates to achieve optimal plant growth and minimise the potential for detrimental impacts on the environment.

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Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

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This paper reports on a purposive survey study which aimed to identify needs for the development, delivery and evaluation of applied climate education for targeted groups, to improve knowledge and skills to better manage under variable climatic conditions. The survey sample consisted of 80 producers and other industry stakeholders in Australia (including representatives from consulting, agricultural extension and agricultural education sectors), with a 58% response rate to the survey. The survey included an assessment of (i) knowledge levels of the Southern Oscillation Index and sea surface temperatures, and (ii) skill and ability in interpreting weather and climate parameters. Results showed that despite many of the respondents having more than 20 years experience in their industry, the only formal climate education or training undertaken by most was a 1-day workshop. Over 80% of the applied climate skills listed in the survey were regarded by respondents as essential or important, but only 42% of educators, 30% of consultants and 28% of producers rated themselves as competent in applying such skills. Essential skills were deemed as those that would enable respondents or their clients to be better prepared for the next extended wet or dry meteorological event, and improved capability in identifying and capitalising on key decision points from climate information and a seasonal climate outlook. The complex issue of forecast accuracy is a confounding obstacle for many in the application of climate information and forecasts in management. Addressing this problem by describing forecast 'limitations and skill' can help to overcome this problem. The survey also highlighted specific climatic tactical and strategic information collated from grazing, cropping and agribusiness enterprises, and showed the value of such information from a users perspective.

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Negative potassium (K) balances in all broadacre grain cropping systems in northern Australia are resulting in a decline in the plant-available reserves of K and necessitating a closer examination of strategies to detect and respond to developing K deficiency in clay soils. Grain growers on the Red Ferrosol soils have increasingly encountered K deficiency over the last 10 years due to lower available K reserves in these soils in their native condition. However, the problem is now increasingly evident on the medium-heavy clay soils (Black and Grey Vertosols) and is made more complicated by the widespread adoption of direct drill cropping systems and the resulting strong strati. cation of available K reserves in the top 0.05-0.1 m of the soil pro. le. This paper reports glasshouse studies examining the fate of applied K fertiliser in key cropping soils of the inland Burnett region of south-east Queensland, and uses the resultant understanding of K dynamics to interpret results of field trials assessing the effectiveness of K application strategies in terms of K availability to crop plants. At similar concentrations of exchangeable K (K-exch), soil solution K concentrations and activity of K in the soil solution (AR(K)) varied by 6-7-fold between soil types. When K-exch arising from different rates of fertiliser application was expressed as a percentage of the effective cation exchange capacity (i.e. K saturation), there was evidence of greater selective adsorption of K on the exchange complex of Red Ferrosols than Black and Grey Vertosols or Brown Dermosols. Both soil solution K and AR(K) were much less responsive to increasing K-exch in the Black Vertosols; this is indicative of these soils having a high K buffer capacity (KBC). These contrasting properties have implications for the rate of diffusive supply of K to plant roots and the likely impact of K application strategies (banding v. broadcast and incorporation) on plant K uptake. Field studies investigating K application strategies (banding v. broadcasting) and the interaction with the degree of soil disturbance/mixing of different soil types are discussed in relation to K dynamics derived from glasshouse studies. Greater propensity to accumulate luxury K in crop biomass was observed in a Brown Ferrosol with a KBC lower than that of a Black Vertosol, consistent with more efficient diffusive supply to plant roots in the Ferrosol. This luxury K uptake, when combined with crops exhibiting low proportional removal of K in the harvested product (i.e. low K harvest index coarse grains and winter cereals) and residue retention, can lead to rapid re-development of stratified K profiles. There was clear evidence that some incorporation of K fertiliser into soil was required to facilitate root access and crop uptake, although there was no evidence of a need to incorporate K fertiliser any deeper than achieved by conventional disc tillage (i.e. 0.1-0.15 m). Recovery of fertiliser K applied in deep (0.25-0.3 m) bands in combination with N and P to facilitate root proliferation was quite poor in Red Ferrosols and Grey or Black Vertosols with moderate effective cation exchange capacity (ECEC, 25-35 cmol(+)/kg), was reasonable but not enough to overcome K deficiency in a Brown Dermosol (ECEC 11 cmol(+)/kg), but was quite good on a Black Vertosol (ECEC 50-60 cmol(+)/kg). Collectively, results suggest that frequent small applications of K fertiliser, preferably with some soil mixing, is an effective fertiliser application strategy on lighter clay soils with low KBC and an effective diffusive supply mechanism. Alternately, concentrated K bands and enhanced root proliferation around them may be a more effective strategy in Vertosol soils with high KBC and limited diffusive supply. Further studies to assess this hypothesis are needed.