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.

Domestication for Conservation of an Endangered Species: The Case of the Wollemi Pine

A small population of tall slender conifers was discovered in 1994 in a deep rainforest canyon of the Wollemi National Park, New SouthWales, Australia. The living trees closely resembled fossils that were more than 65 million years old, and this ‘living fossil’ was recognised as a third extant genus in the Araucariaceae (Araucaria, Agathis and now Wollemia). The species was named the Wollemi pine (W. nobilis). Extensive searches uncovered very few populations, with the total number of adult trees being less than 100. Ex situ collections were quickly established in Sydney as part of the Wollemi Pine Recovery Plan. The majority of the ex situ population was later transferred to our custom-built facility in Queensland for commercial multiplication. Domestication has relied very heavily on the species’ amenability to vegetative propagation because seed collection from the natural populations is dangerous, expensive, and undesirable for conservation reasons. Early propagation success was poor, with only about 25% of cuttings producing roots. However, small increases in propagation success have a very large impact on a domestication program because plant production can be modelled on an exponential curve where each rooted cutting develops into a mother plant that, in turn, provides more rooted cuttings. An extensive research program elevated rooting percentages to greater than 80% and also provided in vitro methods for plant multiplication. These successes have enabled international release of the Wollemi pine as a new and attractive species for ornamental horticulture.

Using catch rate data for simple cost-effective quota setting in the Australian spanner crab (Ranina ranina) fishery.

For many fisheries, there is a need to develop appropriate indicators, methodologies, and rules for sustainably harvesting marine resources. Complexities of scientific and financial factors often prevent addressing these, but new methodologies offer significant improvements on current and historical approaches. The Australian spanner crab fishery is used to demonstrate this. Between 1999 and 2006, an empirical management procedure using linear regression of fishery catch rates was used to set the annual total allowable catch (quota). A 6-year increasing trend in catch rates revealed shortcomings in the methodology, with a 68% increase in quota calculated for the 2007 fishing year. This large quota increase was prevented by management decision rules. A revised empirical management procedure was developed subsequently, and it achieved a better balance between responsiveness and stability. Simulations identified precautionary harvest and catch rate baselines to set quotas that ensured sustainable crab biomass and favourable performance for management and industry. The management procedure was simple to follow, cost-effective, robust to strong trends and changes in catch rates, and adaptable for use in many fisheries. Application of such “tried-and-tested” empirical systems will allow improved management of both data-limited and data-rich fisheries.

Host Tree Influences on Longicorn Beetle (Coleoptera: Cerambycidae) Attack in Subtropical Corymbia (Myrtales: Myrtaceae)

Phoracantha longicorn beetles are endemic to Australia, and some species have become significant pests of eucalypts worldwide, yet little is known about their host plant interactions and factors influencing tree susceptibility in Australia. Here, we investigate the host relationships of Phoracantha solida (Blackburn, 1894) on four eucalypt taxa (one pure species and three hybrid families), examining feeding site physical characteristics including phloem thickness, density, and moisture content, and host tree factors such as diameter, height, growth, taper, and survival. We also determine the cardinal and vertical (within-tree) and horizontal (between-tree) spatial distribution of borers. Fewer than 10% of P. solida attacks were recorded from the pure species (Corymbia citriodora subsp. variegate (Hook)), and this taxon also showed the highest survival, phloem thickness, relative growth rate, and bark:wood area. For the two most susceptible taxa, borer severity was negatively correlated with moisture content, and positively related to phloem density. Borers were nonrandomly and nonuniformly distributed within trees, and were statistically aggregated in 32% of plots. More attacks were situated on the northern side of the tree than the other aspects, and most larvae fed within the lower 50 cm of the bole, with attack height positively correlated with severity. Trees with borers had more dead neighbors, and more bored neighbors, than trees without borers, while within plots, borer incidence and severity were positively correlated. Because the more susceptible taxa overlapped with less susceptible taxa for several physical tree factors, the role of primary and secondary chemistries in determining host suitability needs to be investigated. Nevertheless, taxon, moisture content, phloem density, tree size, and mortality of neighboring trees appeared the most important physical characteristics influencing host suitability for P. solida at this site.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.