Patterns in the distribution and abundance of female eastern king prawns, Melicertus plebejus (Hess, 1865), capable of spawning and reproductive potential in waters off

Linear mixed models were used to test the null hypothesis that there were no differences between seasons and locations in the reproductive potential of female eastern king prawns, Melicertus plebejus along the east coast of Australia. Three samples were collected in each season between autumn 1991 and winter 1992 (inclusive). Females capable of spawning were found at all locations but proportions were greater in lower than higher latitudes. Females capable of spawning were not found at the southern (highest latitude) most location in all seasons. There was a significant interaction in reproductive potential between seasons and locations suggesting that patterns among seasons differed between locations and vice versa. Reproductive potential was greatest amongst the northern (lower latitudes) most locations and was greatest in autumn at these locations. Seasonal patterns were less pronounced further south (higher latitudes). The length composition of females in catches differed between locations with more larger prawns found in samples from northern locations. The challenge that remains is to quantify the oceanic sources of larvae that contribute to recruitment in each nursery area and the estuarine sources of juveniles that contribute adults back to the effective spawning stock. Maintaining the effective spawning stock and important nursery areas are crucial to the sustainability of this resource.

Fishing power and standardised catch rates: Implications of missing vessel-characteristic data from the Australian eastern king prawn fishery

Standardised time series of fishery catch rates require collations of fishing power data on vessel characteristics. Linear mixed models were used to quantify fishing power trends and study the effect of missing data encountered when relying on commercial logbooks. For this, Australian eastern king prawn (Melicertus plebejus) harvests were analysed with historical (from vessel surveys) and current (from commercial logbooks) vessel data. Between 1989 and 2010, fishing power increased up to 76%. To date, both forward-filling and, alternatively, omitting records with missing vessel information from commercial logbooks produce broadly similar fishing power increases and standardised catch rates, due to the strong influence of years with complete vessel data (16 out of 23 years of data). However, if gaps in vessel information had not originated randomly and skippers from the most efficient vessels were the most diligent at filling in logbooks, considerable errors would be introduced. Also, the buffering effect of complete years would be short lived as years with missing data accumulate. Given ongoing changes in fleet profile with high-catching vessels fishing proportionately more of the fleet’s effort, compliance with logbook completion, or alternatively ongoing vessel gear surveys, is required for generating accurate estimates of fishing power and standardised catch rates.

Soil carbon stock in the tropical rangelands of Australia: Effects of soil type and grazing pressure, and determination of sampling requirement.

On-going, high-profile public debate about climate change has focussed attention on how to monitor the soil organic carbon stock (C(s)) of rangelands (savannas). Unfortunately, optimal sampling of the rangelands for baseline C(s) - the critical first step towards efficient monitoring - has received relatively little attention to date. Moreover, in the rangelands of tropical Australia relatively little is known about how C(s) is influenced by the practice of cattle grazing. To address these issues we used linear mixed models to: (i) unravel how grazing pressure (over a 12-year period) and soil type have affected C(s) and the stable carbon isotope ratio of soil organic carbon (delta(13)C) (a measure of the relative contributions of C(3) and C(4) vegetation to C(s)); (ii) examine the spatial covariation of C(s) and delta(13)C; and, (iii) explore the amount of soil sampling required to adequately determine baseline C(s). Modelling was done in the context of the material coordinate system for the soil profile, therefore the depths reported, while conventional, are only nominal. Linear mixed models revealed that soil type and grazing pressure interacted to influence C(s) to a depth of 0.3 m in the profile. At a depth of 0.5 m there was no effect of grazing on C(s), but the soil type effect on C(s) was significant. Soil type influenced delta(13)C to a soil depth of 0.5 m but there was no effect of grazing at any depth examined. The linear mixed model also revealed the strong negative correlation of C(s) with delta(13)C, particularly to a depth of 0.1 m in the soil profile. This suggested that increased C(s) at the study site was associated with increased input of C from C(3) trees and shrubs relative to the C(4) perennial grasses; as the latter form the bulk of the cattle diet, we contend that C sequestration may be negatively correlated with forage production. Our baseline C(s) sampling recommendation for cattle-grazing properties of the tropical rangelands of Australia is to: (i) divide the property into units of apparently uniform soil type and grazing management; (ii) use stratified simple random sampling to spread at least 25 soil sampling locations about each unit, with at least two samples collected per stratum. This will be adequate to accurately estimate baseline mean C(s) to within 20% of the true mean, to a nominal depth of 0.3 m in the profile.

Fishing power increases continue in Queensland's east coast trawl fishery, Australia

The Queensland east coast trawl fishery is by far the largest prawn and scallop otter trawl fleet in Australia in terms of number of vessels, with 504 vessels licensed to fish for species including tiger prawns, endeavour prawns, red spot king prawns, eastern king prawns and saucer scallops by the end of 2004. The vessel fleet has gradually upgraded characteristics such as engine power and use of propeller nozzles, quad nets, global positioning systems (GPS) and computer mapping software. These changes, together with the ever-changing profile of the fleet, were analysed by linear mixed models to quantify annual efficiency increases of an average vessel at catching prawns or scallops. The analyses included vessel characteristics (treated as fixed effects) and vessel identifier codes (treated as random effects). For the period from 1989 to 2004 the models estimated overall fishing power increases of 6% in the northern tiger, 6% in the northern endeavour, 12% in the southern tiger, 18% in the red spot king, 46% in the eastern king prawn and 15% in the saucer scallop sector. The results illustrate the importance of ongoing monitoring of vessel and fleet characteristics and the need to use this information to standardise catch rate indices used in stock assessment and management.

The use of genetic correlations to evaluate associations between SNP markers and quantitative traits

Open-pollinated progeny of Corymbia citriodora established in replicated field trials were assessed for stem diameter, wood density, and pulp yield prior to genotyping single nucleotide polymorphisms (SNP) and testing the significance of associations between markers and assessment traits. Multiple individuals within each family were genotyped and phenotyped, which facilitated a comparison of standard association testing methods and an alternative method developed to relate markers to additive genetic effects. Narrow-sense heritability estimates indicated there was significant additive genetic variance within this population for assessment traits ( h ˆ 2 =0.28to0.44 ) and genetic correlations between the three traits were negligible to moderate (r G = 0.08 to 0.50). The significance of association tests (p values) were compared for four different analyses based on two different approaches: (1) two software packages were used to fit standard univariate mixed models that include SNP-fixed effects, (2) bivariate and multivariate mixed models including each SNP as an additional selection trait were used. Within either the univariate or multivariate approach, correlations between the tests of significance approached +1; however, correspondence between the two approaches was less strong, although between-approach correlations remained significantly positive. Similar SNP markers would be selected using multivariate analyses and standard marker-trait association methods, where the former facilitates integration into the existing genetic analysis systems of applied breeding programs and may be used with either single markers or indices of markers created with genomic selection processes.

The effect of pasture utilization rate on stocks of soil organic carbon and total nitrogen in a semi-arid tropical grassland

The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha−1 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.

Flying-Fox Roost Disturbance and Hendra Virus Spillover Risk

Bats of the genus Pteropus (flying-foxes) are the natural host of Hendra virus (HeV) which periodically causes fatal disease in horses and humans in Australia. The increased urban presence of flying-foxes often provokes negative community sentiments because of reduced social amenity and concerns of HeV exposure risk, and has resulted in calls for the dispersal of urban flying-fox roosts. However, it has been hypothesised that disturbance of urban roosts may result in a stress-mediated increase in HeV infection in flying-foxes, and an increased spillover risk. We sought to examine the impact of roost modification and dispersal on HeV infection dynamics and cortisol concentration dynamics in flying-foxes. The data were analysed in generalised linear mixed models using restricted maximum likelihood (REML). The difference in mean HeV prevalence in samples collected before (4.9%), during (4.7%) and after (3.4%) roost disturbance was small and non-significant (P = 0.440). Similarly, the difference in mean urine specific gravity-corrected urinary cortisol concentrations was small and non-significant (before = 22.71 ng/mL, during = 27.17, after = 18.39) (P= 0.550). We did find an underlying association between cortisol concentration and season, and cortisol concentration and region, suggesting that other (plausibly biological or environmental) variables play a role in cortisol concentration dynamics. The effect of roost disturbance on cortisol concentration approached statistical significance for region, suggesting that the relationship is not fixed, and plausibly reflecting the nature and timing of disturbance. We also found a small positive statistical association between HeV excretion status and urinary cortisol concentration. Finally, we found that the level of flying-fox distress associated with roost disturbance reflected the nature and timing of the activity, highlighting the need for a ‘best practice’ approach to dispersal or roost modification activities. The findings usefully inform public discussion and policy development in relation to Hendra virus and flying-fox management.

Improved models for estimating temporal changes in carbon sequestration in above-ground biomass of mixed-species environmental plantings

Plantings of mixed native species (termed 'environmental plantings') are increasingly being established for carbon sequestration whilst providing additional environmental benefits such as biodiversity and water quality. In Australia, they are currently one of the most common forms of reforestation. Investment in establishing and maintaining such plantings relies on having a cost-effective modelling approach to providing unbiased estimates of biomass production and carbon sequestration rates. In Australia, the Full Carbon Accounting Model (FullCAM) is used for both national greenhouse gas accounting and project-scale sequestration activities. Prior to undertaking the work presented here, the FullCAM tree growth curve was not calibrated specifically for environmental plantings and generally under-estimated their biomass. Here we collected and analysed above-ground biomass data from 605 mixed-species environmental plantings, and tested the effects of several planting characteristics on growth rates. Plantings were then categorised based on significant differences in growth rates. Growth of plantings differed between temperate and tropical regions. Tropical plantings were relatively uniform in terms of planting methods and their growth was largely related to stand age, consistent with the un-calibrated growth curve. However, in temperate regions where plantings were more variable, key factors influencing growth were planting width, stand density and species-mix (proportion of individuals that were trees). These categories provided the basis for FullCAM calibration. Although the overall model efficiency was only 39-46%, there was nonetheless no significant bias when the model was applied to the various planting categories. Thus, modelled estimates of biomass accumulation will be reliable on average, but estimates at any particular location will be uncertain, with either under- or over-prediction possible. When compared with the un-calibrated yield curves, predictions using the new calibrations show that early growth is likely to be more rapid and total above-ground biomass may be higher for many plantings at maturity. This study has considerably improved understanding of the patterns of growth in different types of environmental plantings, and in modelling biomass accumulation in young (<25. years old) plantings. However, significant challenges remain to understand longer-term stand dynamics, particularly with temporal changes in stand density and species composition. © 2014.

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.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

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.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

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.

Previous land use and climate influence differences in soil organic carbon following reforestation of agricultural land with mixed-species plantings

Reforestation of agricultural land with mixed-species environmental plantings (native trees and shrubs) can contribute to mitigation of climate change through sequestration of carbon. Although soil carbon sequestration following reforestation has been investigated at site- and regional-scales, there are few studies across regions where the impact of a broad range of site conditions and management practices can be assessed. We collated new and existing data on soil organic carbon (SOC, 0–30 cm depth, N = 117 sites) and litter (N = 106 sites) under mixed-species plantings and an agricultural pair or baseline across southern and eastern Australia. Sites covered a range of previous land uses, initial SOC stocks, climatic conditions and management types. Differences in total SOC stocks following reforestation were significant at 52% of sites, with a mean rate of increase of 0.57 ± 0.06 Mg C ha−1 y−1. Increases were largely in the particulate fraction, which increased significantly at 46% of sites compared with increases at 27% of sites for the humus fraction. Although relative increase was highest in the particulate fraction, the humus fraction was the largest proportion of total SOC and so absolute differences in both fractions were similar. Accumulation rates of carbon in litter were 0.39 ± 0.02 Mg C ha−1 y−1, increasing the total (soil + litter) annual rate of carbon sequestration by 68%. Previously-cropped sites accumulated more SOC than previously-grazed sites. The explained variance differed widely among empirical models of differences in SOC stocks following reforestation according to SOC fraction and depth for previously-grazed (R2 = 0.18–0.51) and previously-cropped (R2 = 0.14–0.60) sites. For previously-grazed sites, differences in SOC following reforestation were negatively related to total SOC in the pasture. By comparison, for previously-cropped sites, differences in SOC were positively related to mean annual rainfall. This improved broad-scale understanding of the magnitude and predictors of changes in stocks of soil and litter C following reforestation is valuable for the development of policy on carbon markets and the establishment of future mixed-species environmental plantings.