Linking the populations of barramundi and king threadfin to environmental flows in four rivers of tropical Australia

Linking the populations of barramundi and king threadfin to environmental flows in four rivers of tropical Australia

Environmental effects of vegetable production on sensitive waterways

This project investigates the impact of vegetable production systems on sensitive waterways focusing on the risk of off-site nutrient movement at farm block scale under current management practices. The project establishes a series of case studies in two environmentally important Queensland catchments and conducts a broader survey of partial nutrient budgets across tropical vegetable production. It will deliver tools to growers that can improve fertiliser use efficiency delivering profitability and environmental improvements.

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.

Introduction, establishment, and potential geographic range of Carmenta sp. nr ithacae (Lepidoptera: Sesiidae), a biological control agent for Parthenium hysterophorus (Asteraceae) in Australia

Parthenium (Parthenium hysterophorus L.), a major weed causing economic, environmental, and human and animal health problems in Australia and several countries in Asia, Africa, and the Pacific, has been a target for biological control in Australia since the mid-1970s. Nine species of insects and two rust fungi have been introduced as biological control agents into Australia. These include Carmenta sp. nr ithacae, a root feeding agent from Mexico. The larvae of C. sp. nr ithacae bore through the stem-base into the root where they feed on the cortical tissue of the taproot. During 1998-2002, 2,816 larval-infested plants and 387 adults were released at 31 sites across Queensland, Australia. Evidence of field establishment was first observed in two of the release sites in central Queensland in 2004. Annual surveys at these sites and nonrelease sites during 2006-2011 showed wide variations in the incidence and abundance of C. sp. nr ithacae between years and sites. Surveys at three of the nine release sites in northern Queensland and 16 of the 22 release sites in central Queensland confirmed the field establishment of C. sp. nr ithacae in four release sites and four nonrelease sites, all in central Queensland. No field establishment was evident in the inland region or in northern Queensland. A CLIMEX model based on the native range distribution of C. sp. nr ithacae predicts that areas east of the dividing range along the coast are more suitable for field establishment than inland areas. Future efforts to redistribute this agent should be restricted to areas identified as climatically favorable by the CLIMEX model.

Environmental and fishing effects on the dynamics of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

This analysis of the variations of brown tiger prawn (Penaeus esculentus) catch in Moreton Bay multispecies trawl fishery estimated catchability using a delay difference model. It integrated several factors responsible for variations in catchability: targeting of fishing effort, increasing fishing power and changing availability. An analysis of covariance was used to define fishing events targeted at brown tiger prawns. A general linear model estimated inter-annual variations of fishing power. Temperature-induced changes in prawn behaviour played an important role on the dynamics of this fishery. Maximum likelihood estimates of targeted catchability (4.09 ± 0.42 × 10−4 boat-day−1) were twice as large as non-targeted catchability (1.86 ± 0.25 × 10−4 boat-day−1). The causes of recent declines in fishing effort in this fishery were discussed.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Development and testing of allometric equations for estimating above-ground biomass of mixed-species environmental plantings

To quantify the impact that planting indigenous trees and shrubs in mixed communities (environmental plantings) have on net sequestration of carbon and other environmental or commercial benefits, precise and non-biased estimates of biomass are required. Because these plantings consist of several species, estimation of their biomass through allometric relationships is a challenging task. We explored methods to accurately estimate biomass through harvesting 3139 trees and shrubs from 22 plantings, and collating similar datasets from earlier studies, in non-arid (>300mm rainfallyear-1) regions of southern and eastern Australia. Site-and-species specific allometric equations were developed, as were three types of generalised, multi-site, allometric equations based on categories of species and growth-habits: (i) species-specific, (ii) genus and growth-habit, and (iii) universal growth-habit irrespective of genus. Biomass was measured at plot level at eight contrasting sites to test the accuracy of prediction of tonnes dry matter of above-ground biomass per hectare using different classes of allometric equations. A finer-scale analysis tested performance of these at an individual-tree level across a wider range of sites. Although the percentage error in prediction could be high at a given site (up to 45%), it was relatively low (<11%) when generalised allometry-predictions of biomass was used to make regional- or estate-level estimates across a range of sites. Precision, and thus accuracy, increased slightly with the level of specificity of allometry. Inclusion of site-specific factors in generic equations increased efficiency of prediction of above-ground biomass by as much as 8%. Site-and-species-specific equations are the most accurate for site-based predictions. Generic allometric equations developed here, particularly the generic species-specific equations, can be confidently applied to provide regional- or estate-level estimates of above-ground biomass and carbon. © 2013 Elsevier B.V.

A physiological framework to explain genetic and environmental regulation of tillering in sorghum

Tillering determines the plant size of sorghum (Sorghum bicolor) and an understanding of its regulation is important to match genotypes to prevalent growing conditions in target production environments. The aim of this study was to determine the physiological and environmental regulation of variability in tillering among sorghum genotypes, and to develop a framework for this regulation. * Diverse sorghum genotypes were grown in three experiments with contrasting temperature, radiation and plant density to create variation in tillering. Data on phenology, tillering, and leaf and plant size were collected. A carbohydrate supply/demand (S/D) index that incorporated environmental and genotypic parameters was developed to represent the effects of assimilate availability on tillering. Genotypic differences in tillering not explained by this index were defined as propensity to tiller (PTT) and probably represented hormonal effects. * Genotypic variation in tillering was associated with differences in leaf width, stem diameter and PTT. The S/D index captured most of the environmental effects on tillering and PTT most of the genotypic effects. * A framework that captures genetic and environmental regulation of tillering through assimilate availability and PTT was developed, and provides a basis for the development of a model that connects genetic control of tillering to its phenotypic consequences.

Modelling interactions between farm-level structural adjustment and a regional economy: A case of the Australian rice industry

Climate change and on-going water policy reforms will likely contribute to on-farm and regional structural adjustment in Australia. This paper gathers empirical evidence of farm-level structural adjustments and integrates these with a regional equilibrium model to investigate sectoral and regional impacts of climate change and recent water use policy on rice industry. We find strong evidence of adjustments to the farming system, enabled by existing diversity in on-farm production. A further loss of water with additional pressures to adopt less intensive and larger-scale farming, will however reduce the net number of farm businesses, which may affect regional rice production. The results from a regional CGE model show impacts on the regional economy over and above the direct cost of the environmental water, although a net reduction in real economic output and real income is partially offset by gains in rest of the Australia through the reallocation or resources. There is some interest within the industry and from potential new corporate entrants in the relocation of some rice production to the north. However, strong government support would be crucial to implement such relocation.

Potential Animal and Environmental Sources of Q Fever Infection for Humans in Queensland

Q fever is a vaccine-preventable disease; despite this, high annual notification numbers are still recorded in Australia. We have previously shown seroprevalence in Queensland metropolitan regions is approaching that of rural areas. This study investigated the presence of nucleic acid from Coxiella burnetii, the agent responsible for Q fever, in a number of animal and environmental samples collected throughout Queensland, to identify potential sources of human infection. Samples were collected from 129 geographical locations and included urine, faeces and whole blood from 22 different animal species; 45 ticks were removed from two species, canines and possums; 151 soil samples; 72 atmospheric dust samples collected from two locations and 50 dust swabs collected from domestic vacuum cleaners. PCR testing was performed targeting the IS1111 and COM1 genes for the specific detection of C.burnetii DNA. There were 85 detections from 1318 animal samples, giving a detection rate for each sample type ranging from 2.1 to 6.8%. Equine samples produced a detection rate of 11.9%, whilst feline and canine samples showed detection rates of 7.8% and 5.2%, respectively. Native animals had varying detection rates: pooled urines from flying foxes had 7.8%, whilst koalas had 5.1%, and 6.7% of ticks screened were positive. The soil and dust samples showed the presence of C.burnetii DNA ranging from 2.0 to 6.9%, respectively. These data show that specimens from a variety of animal species and the general environment provide a number of potential sources for C.burnetii infections of humans living in Queensland. These previously unrecognized sources may account for the high seroprevalence rates seen in putative low-risk communities, including Q fever patients with no direct animal contact and those subjects living in a low-risk urban environment.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

Evaluating and validating abundance monitoring methods in the absence of populations of known size: review and application to a passive tracking index

Rarely is it possible to obtain absolute numbers in free-ranging populations and although various direct and indirect methods are used to estimate abundance, few are validated against populations of known size. In this paper, we apply grounding, calibration and verification methods, used to validate mathematical models, to methods of estimating relative abundance. To illustrate how this might be done, we consider and evaluate the widely applied passive tracking index (PTI) methodology. Using published data, we examine the rationality of PTI methodology, how conceptually animal activity and abundance are related and how alternative methods are subject to similar biases or produce similar abundance estimates and trends. We then attune the method against populations representing a range of densities likely to be encountered in the field. Finally, we compare PTI trends against a prediction that adjacent populations of the same species will have similar abundance values and trends in activity. We show that while PTI abundance estimates are subject to environmental and behavioural stochasticity peculiar to each species, the PTI method and associated variance estimate showed high probability of detection, high precision of abundance values and, generally, low variability between surveys, and suggest that the PTI method applied using this procedure and for these species provides a sensitive and credible index of abundance. This same or similar validation approach can and should be applied to alternative relative abundance methods in order to demonstrate their credibility and justify their use.