Bycatch weight, composition and preliminary estimates of the impact of bycatch reduction devices in Queensland's trawl fishery

This report provides quantitative information on the effects of turtle excluder devices (TEDs) and bycatch reduction devices (BRDs) on the catch rates of bycatch, prawns, scallops and byproduct species, such as Moreton Bay bugs and Balmain bugs, in Queensland’s major trawl fishing sectors. It also provides biological information on, and management advice for several species referred to in the Fishery Management Plan as the permitted species. Several recommendations are included for reducing bycatch in the trawl fishery and for sustaining stocks of the permitted species.

Estimating an Aggregate Economic Genotype to Facilitate Breeding and Selection of Strawberry Genotypes in Southeast Queensland

The Queensland strawberry (Fragaria ×ananassa) breeding program in subtropical Australia aims to improve sustainable profitability for the producer. Selection must account for the relative economic importance of each trait and the genetic architecture underlying these traits in the breeding population. Our study used estimates of the influence of a trait on production costs and profitability to develop a profitability index (PI) and an economic weight (i.e., change in PI for a unit change in level of trait) for each trait. The economic weights were then combined with the breeding values for 12 plant and fruit traits on over 3000 genotypes that were represented in either the current breeding population or as progenitors in the pedigree of these individuals. The resulting linear combination (i.e., sum of economic weight × breeding value for all 12 traits) estimated the overall economic worth of each genotype as H, the aggregate economic genotype. H values were validated by comparisons among commercial cultivars and were also compared with the estimated gross margins. When the H value of ‘Festival’ was set as zero, the H values of genotypes in the pedigree ranged from –0.36 to +0.28. H was highly correlated (R2 = 0.77) with the year of selection (1945–98). The gross margins were highly linearly related (R2 > 0.98) to H values when the genotype was planted on less than 50% of available area, but the relationship was non-linear [quadratic with a maximum (R2 > 0.96)] when the planted area exceeded 50%. Additionally, with H values above zero, the variation in gross margin increased with increasing H values as the percentage of area planted to a genotype increased. High correlations among some traits allowed the omission of any one of three of the 12 traits with little or no effect on ranking (Spearman’s rank correlation 0.98 or greater). Thus, these traits may be dropped from the aggregate economic genotype, leading to either cost reductions in the breeding program or increased selection intensities for the same resources. H was efficient in identifying economically superior genotypes for breeding and deployment, but because of the non-linear relationship with gross margin, calculation of a gross margin for genotypes with high H is also necessary when cultivars are deployed across more than 50% of the available area.

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.

Floristic composition and pasture condition of Aristida/Bothriochloa pastures in central Queensland. I. Pasture floristics

A survey was conducted in central inland Queensland, Australia of 108 sites that were deemed to contain Aristida/Bothriochloa native pastures to quantitatively describe the pastures and attempt to delineate possible sub-types. The pastures were described in terms of their floristic composition, plant density and crown cover. There were generally ~20 (range 5–33) main pasture species at a site. A single dominant perennial grass was rare with three to six prominent species the norm. Chrysopogon fallax (golden-beard grass) was the perennial grass most consistently found in all pastures whereas Aristida calycina (dark wiregrass), Enneapogon spp. (bottlewasher grasses), Brunoniella australis (blue trumpet) and Panicum effusum (hairy panic) were all regularly present. The pastures did not readily separate into broad floristic sub-groups, but three groups that landholders could recognise from a combination of the dominant tree and soil type were identified. The three groups were Eucalyptus crebra (narrow-leaved ironbark), E. melanophloia (silver-leaved ironbark) and E. populnea (poplar box). The pastures of the three main sub-groups were then characterised by the prominent presence, singly or in combination, of Bothriochloa ewartiana (desert bluegrass), Eremochloa bimaculata (poverty grass), Bothriochloa decipiens (pitted bluegrass) or Heteropogon contortus (black speargrass). The poplar box group had the greatest diversity of prominent grasses whereas the narrow-leaved ironbark group had the least. Non-native Cenchrus ciliaris (buffel grass) and Melinis repens (red Natal grass) were generally present at low densities. Describing pastures in terms of frequency of a few species or species groups sometimes failed to capture the true nature of the pasture but plant abundance for most species, as density, herbage mass of dry matter or plant crown cover, was correlated with its recorded frequency. A quantitative description of an average pasture in fair condition is provided but it was not possible to explain why some species often occur together or fail to co-exist in Aristida/Bothriochloa pastures, for example C. ciliaris and E. bimaculata rarely co-exist whereas Tragus australianus (small burrgrass) and Enneapogon spp. are frequently recorded together. Most crown cover was provided by perennial grasses but many of these are Aristida spp. (wiregrasses) and not regarded as useful forage for livestock. No new or improved categorisation of the great variation evident in the Aristida/Bothriochloa native pasture type can be given despite the much improved detail provided of the floristic composition by this survey.

Stock assessment of whaler and hammerhead sharks (Carcharhinidae and Sphyrnidae) in Queensland

This stock assessment provides detailed results for the most common sharks encountered by Queensland commercial fishers. These sharks come from the whaler (Carcharhinidae) and hammerhead (Sphyrnidae) families and comprise sharpnose sharks (Rhizoprionodon taylori and R. oligolinx), the milk shark (R. acutus), the creek whaler (Carcharhinus fitzroyensis), the hardnose shark (C. macloti), the spot-tail shark (C. sorrah), the Australian blacktip shark (C. tilstoni), the common blacktip shark (C. limbatus), the spinner shark (C. brevipinna), bull and pigeye sharks (C. leucas and C. amboinensis), the winghead shark (Eusphyra blochii), the scalloped hammerhead (Sphyrna lewini) and the great hammerhead (S. mokarran). Reef sharks were excluded because fishery observer data indicated that they were largely spatially segregated from sharks caught in the inshore net fisheries. The three common species of reef sharks in Queensland, which are all whaler sharks, are the grey reef shark Carcharhinus amblyrhynchos, the blacktip reef shark C. melanopterus and the whitetip reef shark Triaenodon obesus.