Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

The accuracy of varietal selection using factor analytic models for multi-environment plant breeding trials

Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

Buffel grass in Queensland's semi-arid woodlands: response to local and landscape scale variables, and relationship with grass, forb and reptile species.

Buffel grass [Pennisetum ciliare (L.) Link] has been widely introduced in the Australian rangelands as a consequence of its value for productive grazing, but tends to competitively establish in non-target areas such as remnant vegetation. In this study, we examined the influence landscape-scale and local-scale variables had upon the distribution of buffel grass in remnant poplar box (Eucalyptus populnea F. Muell.) dominant woodland fragments in the Brigalow Bioregion, Queensland. Buffel grass and variables thought to influence its distribution in the region were measured at 60 sites, which were selected based on the amount of native woodland retained in the landscape and patch size. An information-theoretic modelling approach and hierarchical partitioning revealed that the most influential variable was the percent of retained vegetation within a 1-km spatial extent. From this, we identified a critical threshold of similar to 30% retained vegetation in the landscape, above which the model predicted buffel grass was not likely to occur in a woodland fragment. Other explanatory variables in the model were site based, and included litter cover and long-term rainfall. Given the paucity of information on the effect of buffel grass upon biodiversity values, we undertook exploratory analyses to determine whether buffel grass cover influenced the distribution of grass, forb and reptile species. We detected some trends; hierarchical partitioning revealed that buffel grass cover was the most important explanatory variable describing habitat preferences of four reptile species. However, establishing causal links - particularly between native grass and forb species and buffel grass - was problematic owing to possible confounding with grazing pressure. We conclude with a set of management recommendations aimed at reducing the spread of buffel grass into remnant woodlands.

Tertiary Treatment of Ayr Municipal Wastewater using Bioremediation: A Pilot-Scale Study. A Report Prepared for the Burdekin Shire Council and the Burdekin Rangeland Reef Initiative

This joint DPI/Burdekin Shire Council project assessed the efficacy of a pilot-scale biological remediation system to recover Nitrogen (N) and Phosphorous (P) nutrients from secondary treated municipal wastewater at the Ayr Sewage Treatment Plant. Additionally, this study considered potential commercial uses for by-products from the treatment system. Knowledge gained from this study can provide directions for implementing a larger-scale final effluent treatment protocol on site at the Ayr plant. Trials were conducted over 10 months and assessed nutrient removal from duckweed-based treatments and an algae/fish treatment – both as sequential and as stand-alone treatment systems. A 42.3% reduction in Total N was found through the sequential treatment system (duckweed followed by algae/fish treatment) after 6.6 days Effluent Retention Time (E.R.T.). However, duckweed treatment was responsible for the majority of this nutrient recovery (7.8 times more effective than algae/fish treatment). Likewise, Total P reduction (15.75% reduction after 6.6 days E.R.T.) was twice as great in the duckweed treatment. A phytoplankton bloom, which developed in the algae/fish tanks, reduced nutrient recovery in this treatment. A second trial tested whether the addition of fish enhanced duckweed treatment by evaluating systems with and without fish. After four weeks operation, low DO under the duckweed blanket caused fish mortalities. Decomposition of these fish led to an additional organic load and this was reflected in a breakdown of nitrogen species that showed an increase in organic nitrogen. However, the Dissolved Inorganic Nitrogen (DIN: ammonia, nitrite and nitrate) removal was similar between treatments with and without fish (57% and 59% DIN removal from incoming, respectively). Overall, three effluent residence times were evaluated using duckweed-based treatments; i.e. 3.5 days, 5.5 days and 10.4 days. Total N removal was 37.5%, 55.7% and 70.3%, respectively. The 10.4-day E.R.T. trial, however, was evaluated by sequential nutrient removal through the duckweed-minus-fish treatment followed by the duckweed-plus-fish treatment. Therefore, the 70.3% Total N removal was lower than could have been achieved at this retention time due to the abovementioned fish mortalities. Phosphorous removal from duckweed treatments was greatest after 10.4-days E.R.T. (13.6%). Plant uptake was considered the most important mechanism for this P removal since there was no clay substrate in the plastic tanks that could have contributed to P absorption as part of the natural phosphorous cycle. Duckweed inhibited phytoplankton production (therefore reducing T.S.S) and maintained pH close to neutral. DO beneath the duckweed blanket fell to below 1ppm; however, this did not limit plant production. If fish are to be used as part of the duckweed treatment, air-uplifts can be installed that maintain DO levels without disturbing surface waters. Duckweed grown in the treatments doubled its biomass on average every 5.7 days. On a per-surface area basis, 1.23kg/m2 was harvested weekly. Moisture content of duckweed was 92%, equating to a total dry weight harvest of 0.098kg/m2/week. Nutrient analysis of dried duckweed gave an N content of 6.67% and a P content of 1.27%. According to semi-quantitative analyses, harvested duckweed contained no residual elements from the effluent stream that were greater than ANZECC toxicant guidelines proposed for aquaculture. In addition, jade perch, a local aquaculture species, actively consumed and gained weight on harvested duckweed, suggesting potential for large-scale fish production using by-products from the effluent treatment process. This suggests that a duckweed-based system may be one viable option for tertiary treatment of Ayr municipal wastewater. The tertiary detention lagoon proposed by the Burdekin Shire Council, consisting of six bays approximately 290 x 35 metres (x 1.5 metres deep), would be suitable for duckweed culture with minor modification to facilitate the efficient distribution of duckweed plants across the entire available growing surface (such as floating containment grids). The effluent residence time resulting from this proposed configuration (~30 days) should be adequate to recover most effluent nutrients (certainly N) based on the current trial. Duckweed harvest techniques on this scale, however, need to be further investigated. Based on duckweed production in the current trial (1.23kg/m2/week), a weekly harvest of approximately 75 000kg (wet weight) could be expected from the proposed lagoon configuration under full duckweed production. A benefit of the proposed multi-bay lagoon is that full lagoon production of duckweed may not be needed to restore effluent to a desirable standard under the present nutrient load, and duckweed treatment may be restricted to certain bays. Restored effluent could be released without risk of contaminating the receiving waterway with duckweed by evacuating water through an internal standpipe located mid-way in the water column.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

A multi-field bio-economic model of irrigated grain-cotton farming systems.

We present a participatory modelling framework that integrates information from interviews and discussions with farmers and consultants, with dynamic bio-economic models to answer complex questions on the allocation of limited resources at the farm business level. Interviews and discussions with farmers were used to: describe the farm business; identify relevant research questions; identify potential solutions; and discuss and learn from the whole-farm simulations. The simulations are done using a whole-farm, multi-field configuration of APSIM (APSFarm). APSFarm results were validated against farmers' experience. Once the model was accepted by the participating farmers as a fair representation of their farm business, the model was used to explore changes in the tactical or strategic management of the farm and results were then discussed to identify feasible options for improvement. Here we describe the modelling framework and present an example of the application of integrative whole farm system tools to answer relevant questions from an irrigated farm business case study near Dalby (151.27E - 27.17S), Queensland, Australia. Results indicated that even though cotton crops generates more farm income per hectare a more diversified rotation with less cotton would be relatively more profitable, with no increase in risk, as a more cotton dominated traditional rotation. Results are discussed in terms of the benefits and constraints from developing and applying more integrative approaches to represent farm businesses and their management in participatory research projects with the aim of designing more profitable and sustainable irrigated farming systems.

A framework for optimising capital investment and operations in livestock logistics

Despite the longevity, scale and importance of northern Australia's beef industry, recent disruptions to external markets have demonstrated a degree of vulnerability to shocks in the supply chain. Matching the industry's long-evident resilience to climatic variability with resilience to changes in markets and supply chains requires careful planning. One component of this is how investments in infrastructure will need to be planned to facilitate adaptive responses to market changes. This paper provides an outline of a modelling framework that links strategic and operational dynamic models of logistics along the supply chain from the property to the abattoir or port. A novelty of the methodology is that it takes into account the high granularity of individual livestock transport vehicle movements and the ability to scale up to an almost complete view of logistics costs across the entire beef industry of northern Australia. The paper illustrates how the methodology could be used to examine the effects of changes in logistics infrastructure on efficiency and costs using examples from the states of Northern Territory, Western Australia and Queensland.

Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method

Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.