Fisheries Queensland Long Term Monitoring Program Underwater Visual Census of twenty-four reefs on the Great Barrier Reef between 1999 and 2004.

In 1999, the Department of Employment, Economic Development and Innovation (DEEDI), Fisheries Queensland undertook a new initiative to collect long term monitoring data of various important stocks including reef fish. This data and monitoring manual for the reef fish component of that program which was based on Underwater Visual Census methodology of 24 reefs on the Great Barrier Reef between 1999 and 2004. Data was collected using six 50m x 5m transects at 4 sites on 24 reefs. Benthic cover type was also recorded for 10m of each transect. The attached Access Database contains 5 tables being: SITE DETAILS TABLE Survey year Data entry complete REF survey site ID Site # (1-4) Location (reef name) Site Date (date surveyed) Observer 1 (3 initials to identify who estimated fish lengths and recorded benthic cover) TRANSECT DETAILS Survey ID Transect Number (1-6) Time (the transect was surveyed) Visibility (in metres) Minimum Depth surveyed (m) Maximum Depth surveyed (m) Percent of survey completed (%) Comments SUBSTRATE Survey ID Transect Number (1-6) then % cover of each of eth following categories of benthic cover types Dead Coral Live Coral Soft Coral Rubble Sand Sponge Algae Sea Grass Other COORDINATES (over survey sites) from -14 38.792 to -19 44.233 and from 145 21.507 to 149 55.515 SIGHTINGS ID Survey ID Transect Number (1-6) CAAB Code Scientific Name Reef Fish Length (estimated Fork Length of fish; -1 = unknown or not recorded) Outside Transect (if a fish was observed outside a transect -1 was recorded) Morph Code (F = footballer morph for Plectropomus laevis, S = Spawning colour morph displayed)

Desk Review of Queensland shark stock assessment for Fisheries Queensland

An independent desk review of the document entitled “Stock assessment of whaler and hammerhead sharks (Carcharhinidae and Sphyrnidae) in Queensland” commissioned by the Queensland’s Department of Agriculture and Fisheries was undertaken during January 15-February 12, 2016.

A new data source for fisheries resource assessment: genetic estimates of the effective number of spawners. Final Report to the Fisheries Research and Development Corporation.

The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

Grey Mackerel (Scomberomorus semifasciatus) microsatellite genotypes (nine loci) representing twelve regions along Australia's northern coastline from the eastern coast of Queensland to the western coast of Western Australia.

Scomberomorus semifasciatus is an Australian endemic found in tropical, coastal waters from eastern to western Australia. Commercial and recreational exploitation is common and regulated by state-based authorities. This study used mitochondrial DNA sequence and microsatellite markers to elucidate the population structure of Scomberomorus semifasciatus collected from twelve, equidistant sampling locations. Samples (n=544) were genotyped with nine microsatellite loci, and 353 were sequenced for d-loop (384 bp) and ATP (800bp) mitochondrial DNA gene regions. Combined interpretation of microsatellite and mtDNA data identified four genetic stocks of S. semifasciatus: Western Australia, northwest coast of the Northern Territory, Gulf of Carpentaria and the east coast of Queensland. Connectivity among stocks across northern Australia from the Northern Territory to the east coast of Queensland was high, but in contrast, there was a clear genetic break between populations in Western Australia compared to the rest of northern Australia. This indicates a restriction to gene flow possibly associated with suboptimal habitat along the Kimberley coast (northwestern Australia). The appropriate scale of management for this species corresponds to the jurisdictions of the three Australian states, except that the Gulf of Carpentaria stock should be co-managed by authorities in Queensland and Northern Territory.

Drywood termites in Queensland.

Discusses: Biology and damage, native drywood termite, West Indian drywood termite, building inspection, prevention, treating active infestation.

Queensland Spanner Crab Fishery: Commercial quota setting for June 2016 – May 2018

The Queensland (QLD) fishery for spanner crabs primarily lands live crab for export overseas, with gross landings valued around A$5 million per year. Quota setting rules are used to assess and adjust total allowable harvest (quota) around an agreed target harvest of 1631 t and capped at a maximum of 2000 t. The quota varies based on catch rate indicators from the commercial fishery and a fishery independent survey. Quota management applies only to ‘Managed Area A’ which includes waters between Rockhampton and the New South Wales (NSW) border. This report has been prepared to inform Fisheries Queensland (Department of Agriculture and Fisheries) and stakeholders of catch trends and the estimated quota of spanner crabs in Managed Area A for the forthcoming annual quota periods (1 June 2016–31 May 2018). The quota calculations followed the methodology developed by the crab fishery Scientific Advisory Group (SAG) between November 2007 and March 2008. The QLD total reported spanner crab harvest was 1170 t for the 2015 calendar year. In 2015, a total of 55 vessels were active in the QLD fishery, down from 262 vessels at the fishery’s peak activity in 1994. Recent spanner crab harvests from NSW waters average about 125 t per year, but fell to 80 t in 2014–2015. The spanner crab Managed Area A commercial standardised catch rate averaged 0.818 kg per net-lift in 2015, 22.5% below the target level of 1.043. Compared to 2014, mean catch rates in 2015 were marginally improved south of Fraser Island. The NSW–QLD survey catch rate in 2015 was 20.541 crabs per ground-line, 33% above the target level of 13.972. This represented an increase in survey catch rates of about four crabs per groundline, compared to the 2014 survey. The QLD spanner crab total allowable harvest (quota) was set at 1923 t in the 2012-13 and 2013-14 fishing years, 1777 t in 2014-15 and 1631 t in 2015-16. The results from the current analysis rules indicate that the quota for the next two fishing years be retained at the base quota of 1631 t.

Queensland Spanner Crab Fishery : Commercial quota setting for June 2015 – May 2016

The Australian fishery for spanner crabs is the largest in the world, with the larger Queensland (QLD) sector’s landings primarily exported live overseas and GVP valued ~A$5 million per year. Spanner crabs are unique in that they may live up to 15 years, significantly more than blue swimmer crabs (Portunus armatus) and mud crabs (Scylla serrata), the two other important crab species caught in Queensland. Spanner crabs are caught using a flat net called a dilly, on which the crabs becoming entangled via the swimming legs. Quota setting rules are used to assess and adjust total allowable harvest (quota) around an agreed target harvest of 1631 t and capped at a maximum of 2000 t. The quota varies based on catch rate indicators from the commercial fishery and a fishery-independent survey from the previous two years, compared to target reference points. Quota management applies only to ‘Managed Area A’ which includes waters between Rockhampton and the New South Wales (NSW) border. This report has been prepared to inform Fisheries Queensland (Department of Agriculture and Fisheries) and stakeholders of catch trends and the estimated quota of spanner crabs in Managed Area A for the forthcoming quota period (1 June 2015–31 May 2016). The quota calculations followed the methodology developed by the crab fishery Scientific Advisory Group (SAG) between November 2007 and March 2008. The total reported spanner crab harvest was 917 t for the 2014 calendar year, almost all of which was taken from Managed Area A. In 2014, a total of 59 vessels were active in the QLD fishery, the lowest number since the peak in 1994 of 262 vessels. Recent spanner crab harvests from NSW waters have been about 125 t per year. The spanner crab Managed Area A commercial standardised catch rate averaged 0.739 kg per net-lift in 2014, 24% below the target level of 1.043. Mean catch rates declined in the commercial fishery in 2014, although the magnitude of the decreases was highest in the area north of Fraser Island. The NSW–QLD survey catch rate in 2014 was 16.849 crabs per ground-line, 22% above the target level of 13.972. This represented a decrease in survey catch rates of 0.366 crabs per ground-line, compared to the 2013 survey. The Queensland spanner crab total allowable harvest (quota) was set at 1923 t in 2012 and 2013. In 2014, the quota was calculated at the base level of 1631 t. However, given that the 2012 fisheryindependent survey was not undertaken for financial reasons, stakeholders proposed that the total allowable commercial catch (TACC) be decreased to 1777 t; a level that was halfway between the 2012/13 quota of 1923 t and the recommended base quota of 1631 t. The results from the current analysis indicate that the quota for the 2015-2016 financial year be decreased from 1777 t to the base quota of 1631 t.

Queensland shark control program non-target statistics by year

Spreadsheet of non-target species (bycatch) numbers in the Shark Control Program by species, date of capture, location, size and sex from 2001 onwards The shark control program (SCP) relies on nets or drumlines, or a combination of both, to minimise the threat of shark attack on humans in particular locations. Following is information on numbers and locations of sharks that have been caught by the SCP. It is important to reduce the inadvertent impacts of the SCP on other marine animals (bycatch) without compromising human safety. Bycatch levels are carefully monitored and research is focused on minimising impacts on non-target species. This dataset contains details of non-target numbers in the Shark Control program by species, date of capture, and location from 2001

Horse and Cattle Brands in Queensland

Horse and Cattle Brands in Queensland since 1872 to current year 2015

Sheep Brands in Queensland

Sheep Brands in Queensland since the 1896 to year 2015.

Composite of coastal seagrass meadows in Queensland, Australia - November 1984 to June 2010

Approximately 18,400 km**2 of seagrass habitat has been mapped within the coastal waters (<15 m) of Queensland (Australia) between November 1984 and June 2010. The total seagrass meadow distribution was calculated by merging maps from 115 separate mapping surveys (varying locations and dates). Due to tropical seagrass dynamism, meadow distribution can change seasonally and between years, and as a consequence, the composite represents the maximum area of seabed where seagrass has been observed/recorded. Mapping survey methodologies followed standardised global seagrass research methods (McKenzie et al. 2001) where the presence of seagrass was determined from in situ visual assessment of the seabed by either divers or drop cameras at GPS marked positions. Seagrass meadow boundaries were determined based on the positions of survey sites and the presence of seagrass, coupled with depth contours and remote sensing (e.g. aerial photography) where available. The merged meadow boundary accuracy was dependent on the original survey maps and varied from 10-100 m. The resulting composite seagrass distribution was saved as an ArcMap polygon shapefile, and projected to Geocentric Datum of Australia GDA94.

Stout Whiting Fishery Summary : Queensland Total Allowable Catch for 2016

In Queensland, stout whiting are fished by Danish seine and fish otter-trawl methods between Sandy Cape and the Queensland-New South Wales border. The fishery is currently identified by a T4 symbol and is operated by two primary quota holders. Since 1997, T4 management has been informed by annual stock assessments in order to determine a total allowable commercial catch (TACC) quota. The TACC is assessed before the start of each fishing year using statistical methodologies. This includes evaluation of trends in fish catch-rates and catch-at-age frequencies against management reference points. The T4 stout whiting TACC for 2014 was adjusted down to 1150 t as a result of elevated estimates of fishing mortality and remained unchanged in 2015 (2013 TACC = 1350 t quota). Two T4 vessels fished for stout whiting in the 2015 fishing year, harvesting 663 t from Queensland waters. Annual T4 landings of stout whiting averaged about 713 t for the fishing years 2013–2015, with a maximum harvest in the last 10 fishing years of 1140 t and a maximum historical harvest of 2400 t in the 1995. Stout whiting catch rates from both Queensland and New South Wales were analysed for all vessels, areas and fishing gears. The 2015 catch rate index was equal to 0.85, down 15% compared to the 2010–2015 fishing year average (reference point =1). The stout whiting fish length and otolith weight frequencies indicated larger and older fish in the calendar year 2014. This data was translated to show improved measures of fish survival at about 38% per year and near the reference point of about 41%. Together, the stout whiting catch rate and survival indicators show the fishery was sustainable. Earlier population modelling conducted for the year 2013 also suggested the stock was sustainable, but the estimate was only marginally above the biomass for maximum sustainable yield. Irrespective, reasons for reduced catch rates should be examined further and interpreted with precaution, particularly given the TACC has been under-caught in many years. For setting of the 2016 TACC, alternate analyses and reference points were compared to address data uncertainties and provide options for quota change. The results were dependent on the stock indicator and harvest procedure used. Uncertainty in all TACC estimates should be considered as they were sensitive to the data inputs and assumptions. For the 2016 T4 fishing year, upper levels of harvest should be limited to 1000–1100 t following procedure equation 1, with target levels of harvest at 750–850 t for procedure equation 2. Use of these estimates to set TACC will depend on management and industry intentions.

Queensland Forest & Timber Industry : an overview

The publication provides a snapshot of the forest and timber industry’s contribution to the Queensland economy and highlights the scope, innovation and features of the state’s forest and timber products that are produced from Queensland’s unique resources.