Impact of the invasive rust Puccinia psidii (myrtle rust) on native Myrtaceae in natural ecosystems in Australia

The invasive rust Puccinia psidii (myrtle rust) was detected in Australia in 2010 and is now established along the east coast from southern New South Wales to far north Queensland. Prior to reaching Australia, severe damage from P. psidii was mainly restricted to exotic eucalypt plantations in South America, guava plantations in Brazil, allspice plantations in Jamaica, and exotic Myrtaceous tree species in the USA; the only previous record of widespread damage in native environments is of endangered Eugenia koolauensis in Hawai’i. Using two rainforest tree species as indicators of the impact of P. psidii, we report for the first time severe damage to endemic Myrtaceae in native forests in Australia, after only 4 years’ exposure to P. psidii. A 3-year disease exclusion trial in a natural stand of Rhodamnia rubescens unequivocally showed that repeated, severe infection leads to gradual crown loss and ultimately tree mortality; trees were killed in less than 4 years. Significant (p < 0.001) correlations were found between both incidence (r = 0.36) and severity (r = 0.38) of P. psidii and subsequent crown loss (crown transparency). This provided supporting evidence to conclude a causal association between P. psidii and crown loss and tree mortality in our field assessments of R. rubescens and Rhodomyrtus psidioides across their native range. Assessments revealed high levels of damage by P. psidii to immature leaves, shoots and tree crowns—averaging 76 % (R. rubescens) and 95 % (R. psidioides) crown transparency—as well as tree mortality. For R. psidioides, we saw exceptionally high levels of tree mortality, with over half the trees surveyed dead and 40 % of stands with greater than 50 % tree mortality, including two stands where all trees were dead. Tree mortality was less prevalent for R. rubescens, with only 12 % of trees surveyed dead and two sites with greater than 50 % mortality. Any alternative causal agents for this tree mortality have been discounted. The ecological implications of this are unclear, but our work clearly illustrates the potential for P. psidii to negatively affect Australia’s biodiversity.

Development of key soil health indicators for the Australian banana industry

To improve the sustainability and environmental accountability of the banana industry there is a need to develop a set of soil health indicators that integrate physical, chemical and biological soil properties. These indicators would allow banana growers, extension and research workers to improve soil health management practices. To determine changes in soil properties due to the cultivation of bananas, a paired site survey was conducted comparing soil properties under conventional banana systems to less intensively managed vegetation systems, such as pastures and forest. Measurements were made on physical, chemical and biological soil properties at seven locations in tropical and sub-tropical banana producing areas. Soil nematode community composition was used as a bioindicator of the biological properties of the soil. Soils under conventional banana production tended to have a greater soil bulk density, with less soil organic carbon (C) (both total C and labile C), greater exchangeable cations, higher extractable P, greater numbers of plant-parasitic nematodes and less nematode diversity, relative to less intensively managed plant systems. The organic banana production systems at two locations had greater labile C, relative to conventional banana systems, but there was no significant change in nematode community composition. There were significant interactions between physical, chemical and nematode community measurements in the soil, particularly with soil C measurements, confirming the need for a holistic set of indicators to aid soil management. There was no single indicator of soil health for the Australian banana industry, but a set of soil health indicators, which would allow the measurement of soil improvements should include: bulk density, soil C, pH, EC, total N, extractable P, ECEC and soil nematode community structure.

The short-term effects of a routine poisoning campaign on the movements and detectability of a social top-predator

Top-predators can be important components of resilient ecosystems, but they are still controlled in many places to mitigate a variety of economic, environmental and/or social impacts. Lethal control is often achieved through the broad-scale application of poisoned baits. Understanding the direct and indirect effects of such lethal control on subsequent movements and behaviour of survivors is an important pre-requisite for interpreting the efficacy and ecological outcomes of top-predator control. In this study, we use GPS tracking collars to investigate the fine-scale and short-term movements of dingoes (Canis lupus dingo and other wild dogs) in response to a routine poison-baiting program as an example of how a common, social top-predator can respond (behaviourally) to moderate levels of population reduction. We found no consistent control-induced differences in home range size or location, daily distance travelled, speed of travel, temporal activity patterns or road/trail usage for the seven surviving dingoes we monitored immediately before and after a typical lethal control event. These data suggest that the spatial behaviour of surviving dingoes was not altered in ways likely to affect their detectability, and if control-induced changes in dingoes' ecological function did occur, these may not be related to altered spatial behaviour or movement patterns.

Stock assessment of the Queensland east coast common coral trout (Plectropomus leopardus) fishery

Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

Improving the effectiveness of age-abundance indicators in the management of fisheries in Queensland, Australia

The development of fishery indicators is a crucial undertaking as it ultimately provides evidence to stakeholders about the status of fished species such as population size and survival rates. In Queensland, as in many other parts of the world, age-abundance indicators (e.g. fish catch rate and/or age composition data) are traditionally used as the evidence basis because they provide information on species life history traits as well as on changes in fishing pressures and population sizes. Often, however, the accuracy of the information from age-abundance indicators can be limited due to missing or biased data. Consequently, improved statistical methods are required to enhance the accuracy, precision and decision-support value of age-abundance indicators.