4 resultados para 322-C0011B

em eResearch Archive - Queensland Department of Agriculture


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Bellyache bush (Jatropha gossypiifolia L.) is an invasive weed that poses economic and environmental problems in northern Australia. Competition between pasture and bellyache bush was examined in North Queensland using combinations of five pasture treatments (uncut (control); cut as low, medium, and high pasture; and no pasture) and four bellyache bush densities (0, 2, 6 and 12plantsm(-2)) in a buffel grass (Cenchrus ciliaris L.) dominated pasture. The pasture treatments were applied approximately once per year but no treatments were applied directly to the bellyache bush plants. Measurements of bellyache bush flowering, seed formation, and mortality were undertaken over a 9-year period, along with monitoring the pasture basal cover and plant species diversity. Maximum flowering rates of bellyache bush occurred after 9 years (97%) in plots containing no pasture, with the lowest rates of 9% in uncut control plots. Earliest flowering (322 days after planting) and seed formation (411 days) also occurred in plots with no pasture compared with all other pasture treatments (range 1314-1393 days for seed formation to occur). No seeds were produced in uncut plots. At the end of 9 years, mortality rates of bellyache bush plants initially planted averaged 73% for treatments with some pasture compared with 55% under the no-pasture treatment. The percentage of herbaceous plant basal cover in uncut plots was increased 5-fold after 9 years, much greater than the average 2% increase recorded across the low, medium, and high pasture treatments. The number of herbaceous species in uncut plots remained largely unchanged, whereas there was an average reduction of 46% in the cut pasture treatments. Buffel grass remained the species with the greatest basal cover across all cut pasture treatments, followed by sabi grass (Urochloa mosambicensis (Hack.) Dandy) and then red Natal grass (Melinis repens (Willd.) Ziska). These results suggest that grazing strategies that maintain a healthy and competitive pasture layer may contribute to reducing the rate of spread of bellyache bush and complement traditional control techniques such as the use of herbicides.

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This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected. (C) 2013 Elsevier B.V. All rights reserved.

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It is common to model the dynamics of fisheries using natural and fishing mortality rates estimated independently using two separate analyses. Fishing mortality is routinely estimated from widely available logbook data, whereas natural mortality estimations have often required more specific, less frequently available, data. However, in the case of the fishery for brown tiger prawn (Penaeus esculentus) in Moreton Bay, both fishing and natural mortality rates have been estimated from logbook data. The present work extended the fishing mortality model to incorporate an eco-physiological response of tiger prawn to temperature, and allowed recruitment timing to vary from year to year. These ecological characteristics of the dynamics of this fishery were ignored in the separate model that estimated natural mortality. Therefore, we propose to estimate both natural and fishing mortality rates within a single model using a consistent set of hypotheses. This approach was applied to Moreton Bay brown tiger prawn data collected between 1990 and 2010. Natural mortality was estimated by maximum likelihood to be equal to 0.032 ± 0.002 week−1, approximately 30% lower than the fixed value used in previous models of this fishery (0.045 week−1).