29 resultados para management structure
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Non-Technical Summary Seafood CRC Project 2009/774. Harvest strategy evaluations and co-management for the Moreton Bay Trawl Fishery Principal Investigator: Dr Tony Courtney, Principal Fisheries Biologist Fisheries and Aquaculture, Agri-Science Queensland Department of Agriculture, Fisheries and Forestry Level B1, Ecosciences Precinct, Joe Baker St, Dutton Park, Queensland 4102 Email: tony.courtney@daff.qld.gov.au Project objectives: 1. Review the literature and data (i.e., economic, biological and logbook) relevant to the Moreton Bay trawl fishery. 2. Identify and prioritise management objectives for the Moreton Bay trawl fishery, as identified by the trawl fishers. 3. Undertake an economic analysis of Moreton Bay trawl fishery. 4. Quantify long-term changes to fishing power for the Moreton Bay trawl fishery. 5. Assess priority harvest strategies identified in 2 (above). Present results to, and discuss results with, Moreton Bay Seafood Industry Association (MBSIA), fishers and Fisheries Queensland. Note: Additional, specific objectives for 2 (above) were developed by fishers and the MBSIA after commencement of the project. These are presented in detail in section 5 (below). The project was an initiative of the MBSIA, primarily in response to falling profitability in the Moreton Bay prawn trawl fishery. The analyses were undertaken by a consortium of DAFF, CSIRO and University of Queensland researchers. This report adopted the Australian Standard Fish Names (http://www.fishnames.com.au/). Trends in catch and effort The Moreton Bay otter trawl fishery is a multispecies fishery, with the majority of the catch composed of Greasyback Prawns (Metapenaeus bennettae), Brown Tiger Prawns (Penaeus esculentus), Eastern King Prawns (Melicertus plebejus), squid (Uroteuthis spp., Sepioteuthis spp.), Banana Prawns (Fenneropenaeus merguiensis), Endeavour Prawns (Metapenaeus ensis, Metapenaeus endeavouri) and Moreton Bay bugs (Thenus parindicus). Other commercially important byproduct includes blue swimmer crabs (Portunus armatus), three-spot crabs (Portunus sanguinolentus), cuttlefish (Sepia spp.) and mantis shrimp (Oratosquilla spp.). Logbook catch and effort data show that total annual reported catch of prawns from the Moreton Bay otter trawl fishery has declined to 315 t in 2008 from a maximum of 901 t in 1990. The number of active licensed vessels participating in the fishery has also declined from 207 in 1991 to 57 in 2010. Similarly, fishing effort has fallen from a peak of 13,312 boat-days in 1999 to 3817 boat-days in 2008 – a 71% reduction. The declines in catch and effort are largely attributed to reduced profitability in the fishery due to increased operational costs and depressed prawn prices. The low prawn prices appear to be attributed to Australian aquacultured prawns and imported aquacultured vannamei prawns, displacing the markets for trawl-caught prawns, especially small species such as Greasyback Prawns which traditionally dominated landings in Moreton Bay. In recent years, the relatively high Australian dollar has resulted in reduced exports of Australian wild-caught prawns. This has increased supply on the domestic market which has also suppressed price increases. Since 2002, Brown Tiger Prawns have dominated annual reported landings in the Moreton Bay fishery. While total catch and effort in the bay have declined to historically low levels, the annual catch and catch rates of Brown Tiger Prawns have been at record highs in recent years. This appears to be at least partially attributed to the tiger prawn stock having recovered from excessive effort in previous decades. The total annual value of the Moreton Bay trawl fishery catch, including byproduct, is about $5 million, of which Brown Tiger Prawns account for about $2 million. Eastern King Prawns make up about 10% of the catch and are mainly caught in the bay from October to December as they migrate to offshore waters outside the bay where they contribute to a large mono-specific trawl fishery. Some of the Eastern King Prawns harvested in Moreton Bay may be growth overfished (i.e., caught below the size required to maximise yield or value), although the optimum size-at-capture was not determined in this study. Banana Prawns typically make up about 5% of the catch, but can exceed 20%, particularly following heavy rainfall. Economic analysis of the fishery From the economic survey, cash profits were, on average, positive for both fleet segments in both years of the survey. However, after the opportunity cost of capital and depreciation were taken into account, the residual owner-operator income was relatively low, and substantially lower than the average share of revenue paid to employed skippers. Consequently, owner-operators were earning less than their opportunity cost of their labour, suggesting that the fleets were economically unviable in the longer term. The M2 licensed fleet were, on average, earning similar boat cash profits as the T1/M1 fleet, although after the higher capital costs were accounted for the T1/M1 boats were earning substantially lower returns to owner-operator labour. The mean technical efficiency for the fleet as a whole was estimated to be 0.67. That is, on average, the boats were only catching 67 per cent of what was possible given their level of inputs (hours fished and hull units). Almost one-quarter of observations had efficiency scores above 0.8, suggesting a substantial proportion of the fleet are relatively efficient, but some are also relatively inefficient. Both fleets had similar efficiency distributions, with median technical efficiency score of 0.71 and 0.67 for the M2 and T1/M1 boats respectively. These scores are reasonably consistent with other studies of prawn trawl fleets in Australia, although higher average efficiency scores were found in the NSW prawn trawl fleet. From the inefficiency model, several factors were found to significantly influence vessel efficiency. These included the number of years of experience as skipper, the number of generations that the skipper’s family had been fishing and the number of years schooling. Skippers with more schooling were significantly more efficient than skippers with lower levels of schooling, consistent with other studies. Skippers who had been fishing longer were, in fact, less efficient than newer skippers. However, this was mitigated in the case of skippers whose family had been involved in fishing for several generations, consistent with other studies and suggesting that skill was passed through by families over successive generations. Both the linear and log-linear regression models of total fishing effort against the marginal profit per hour performed reasonably well, explaining between 70 and 84 per cent of the variation in fishing effort. As the models had different dependent variables (one logged and the other not logged) this is not a good basis for model choice. A better comparator is the square root of the mean square error (SMSE) expressed as a percentage of the mean total effort. On this criterion, both models performed very similarly. The linear model suggests that each additional dollar of average profits per hour in the fishery increases total effort by around 26 hours each month. From the log linear model, each percentage increase in profits per hour increases total fishing effort by 0.13 per cent. Both models indicate that economic performance is a key driver of fishing effort in the fishery. The effect of removing the boat-replacement policy is to increase individual vessel profitability, catch and effort, but the overall increase in catch is less than that removed by the boats that must exit the fishery. That is, the smaller fleet (in terms of boat numbers) is more profitable but the overall catch is not expected to be greater than before. This assumes, however, that active boats are removed, and that these were also taking an average level of catch. If inactive boats are removed, then catch of the remaining group as a whole could increase by between 14 and 17 per cent depending on the degree to which costs are reduced with the new boats. This is still substantially lower than historical levels of catch by the fleet. Fishing power analyses An analysis of logbook data from 1988 to 2010, and survey information on fishing gear, was performed to estimate the long-term variation in the fleet’s ability to catch prawns (known as fishing power) and to derive abundance estimates of the three most commercially important prawn species (i.e., Brown Tiger, Eastern King and Greasyback Prawns). Generalised linear models were used to explain the variation in catch as a function of effort (i.e., hours fished per day), vessel and gear characteristics, onboard technologies, population abundance and environmental factors. This analysis estimated that fishing power associated with Brown Tiger and Eastern King Prawns increased over the past 20 years by 10–30% and declined by approximately 10% for greasybacks. The density of tiger prawns was estimated to have almost tripled from around 0.5 kg per hectare in 1988 to 1.5 kg/ha in 2010. The density of Eastern King Prawns was estimated to have fluctuated between 1 and 2 kg per hectare over this time period, without any noticeable overall trend, while Greasyback Prawn densities were estimated to have fluctuated between 2 and 6 kg per hectare, also without any distinctive trend. A model of tiger prawn catches was developed to evaluate the impact of fishing on prawn survival rates in Moreton Bay. The model was fitted to logbook data using the maximum-likelihood method to provide estimates of the natural mortality rate (0.038 and 0.062 per week) and catchability (which can be defined as the proportion of the fished population that is removed by one unit of effort, in this case, estimated to be 2.5 ± 0.4 E-04 per boat-day). This approach provided a method for industry and scientists to develop together a realistic model of the dynamics of the fishery. Several aspects need to be developed further to make this model acceptable to industry. Firstly, there is considerable evidence to suggest that temperature influences prawn catchability. This ecological effect should be incorporated before developing meaningful harvest strategies. Secondly, total effort has to be allocated between each species. Such allocation of effort could be included in the model by estimating several catchability coefficients. Nevertheless, the work presented in this report is a stepping stone towards estimating essential fishery parameters and developing representative mathematical models required to evaluate harvest strategies. Developing a method that allowed an effective discussion between industry, management and scientists took longer than anticipated. As a result, harvest strategy evaluations were preliminary and only included the most valuable species in the fishery, Brown Tiger Prawns. Additional analyses and data collection, including information on catch composition from field sampling, migration rates and recruitment, would improve the modelling. Harvest strategy evaluations As the harvest strategy evaluations are preliminary, the following results should not be adopted for management purposes until more thorough evaluations are performed. The effects, of closing the fishery for one calendar month, on the annual catch and value of Brown Tiger Prawns were investigated. Each of the 12 months (i.e., January to December) was evaluated. The results were compared against historical records to determine the magnitude of gain or loss associated with the closure. Uncertainty regarding the trawl selectivity was addressed using two selectivity curves, one with a weight at 50% selection (S50%) of 7 g, based on research data, and a second with S50% of 14 g, put forward by industry. In both cases, it was concluded that any monthly closure after February would not be beneficial to the industry. The magnitude of the benefit of closing the fishery in either January or February was sensitive to which mesh selectivity curve that was assumed, with greater benefit achieved when the smaller selectivity curve (i.e., S50% = 7 g) was assumed. Using the smaller selectivity (S50% = 7 g), the expected increase in catch value was 10–20% which equates to $200,000 to $400,000 annually, while the larger selectivity curve (S50% = 14 g) suggested catch value would be improved by 5–10%, or $100,000 to $200,000. The harvest strategy evaluations showed that greater benefits, in the order of 30–60% increases in the tiger annual catch value, could have been obtained by closing the fishery early in the year when annual effort levels were high (i.e., > 10,000 boat-days). In recent years, as effort levels have declined (i.e., ~4000 boat-days annually), expected benefits from such closures are more modest. In essence, temporal closures offer greater benefit when fishing mortality rates are high. A spatial analysis of Brown Tiger Prawn catch and effort was also undertaken to obtain a better understanding of the prawn population dynamics. This indicated that, to improve profitability of the fishery, fishers could consider closing the fishery in the period from June to October, which is already a period of low profitability. This would protect the Brown Tiger Prawn spawning stock, increase catch rates of all species in the lucrative pre-Christmas period (November–December), and provide fishers with time to do vessel maintenance, arrange markets for the next season’s harvest, and, if they wish, work at other jobs. The analysis found that the instantaneous rate of total mortality (Z) for the March–June period did not vary significantly over the last two decades. As the Brown Tiger Prawn population in Moreton Bay has clearly increased over this time period, an interesting conclusion is that the instantaneous rate of natural mortality (M) must have increased, suggesting that tiger prawn natural mortality may be density-dependent at this time of year. Mortality rates of tiger prawns for June–October were found to have decreased over the last two decades, which has probably had a positive effect on spawning stocks in the October–November spawning period. Abiotic effects on the prawns The influence of air temperature, rainfall, freshwater flow, the southern oscillation index (SOI) and lunar phase on the catch rates of the four main prawn species were investigated. The analyses were based on over 200,000 daily logbook catch records over 23 years (i.e., 1988–2010). Freshwater flow was more influential than rainfall and SOI, and of the various sources of flow, the Brisbane River has the greatest volume and influence on Moreton Bay prawn catches. A number of time-lags were also considered. Flow in the preceding month prior to catch (i.e., 30 days prior, Logflow1_30) and two months prior (31–60 days prior, Logflow31_60) had strong positive effects on Banana Prawn catch rates. Average air temperature in the preceding 4-6 months (Temp121_180) also had a large positive effect on Banana Prawn catch rates. Flow in the month immediately preceding catch (Logflow1_30) had a strong positive influence on Greasyback Prawn catch rates. Air temperature in the preceding two months prior to catch (Temp1_60) had a large positive effect on Brown Tiger Prawn catch rates. No obvious or marked effects were detected for Eastern King Prawns, although interestingly, catch rates declined with increasing air temperature 4–6 months prior to catch. As most Eastern King Prawn catches in Moreton Bay occur in October to December, the results suggest catch rates decline with increasing winter temperatures. In most cases, the prawn catch rates declined with the waxing lunar phase (high luminance/full moon), and increased with the waning moon (low luminance/new moon). The SOI explains little additional variation in prawn catch rates (~ <2%), although its influence was higher for Banana Prawns. Extrapolating findings of the analyses to long-term climate change effects should be interpreted with caution. That said, the results are consistent with likely increases in abundance in the region for the two tropical species, Banana Prawns and Brown Tiger Prawns, as coastal temperatures rise. Conversely, declines in abundance could be expected for the two temperate species, Greasyback and Eastern King Prawns. Corporate management structures An examination of alternative governance systems was requested by the industry at one of the early meetings, particularly systems that may give them greater autonomy in decision making as well as help improve the marketing of their product. Consequently, a review of alternative management systems was undertaken, with a particular focus on the potential for self-management of small fisheries (small in terms of number of participants) and corporate management. The review looks at systems that have been implemented or proposed for other small fisheries internationally, with a particular focus on self-management as well as the potential benefits and challenges for corporate management. This review also highlighted particular opportunities for the Moreton Bay prawn fishery. Corporate management differs from other co-management and even self-management arrangements in that ‘ownership’ of the fishery is devolved to a company in which fishers and government are shareholders. The company manages the fishery as well as coordinates marketing to ensure that the best prices are received and that the catch taken meets the demands of the market. Coordinated harvesting will also result in increased profits, which are returned to fishers in the form of dividends. Corporate management offers many of the potential benefits of an individual quota system without formally implementing such a system. A corporate management model offers an advantage over a self-management model in that it can coordinate both marketing and management to take advantage of this unique geographical advantage. For such a system to be successful, the fishery needs to be relatively small and self- contained. Small in this sense is in terms of number of operators. The Moreton Bay prawn fishery satisfies these key conditions for a successful self-management and potentially corporate management system. The fishery is small both in terms of number of participants and geography. Unlike other fisheries that have progressed down the self-management route, the key market for the product from the Moreton Bay fishery is right at its doorstep. Corporate management also presents a number of challenges. First, it will require changes in the way fishers operate. In particular, the decision on when to fish and what to catch will be taken away from the individual and decided by the collective. Problems will develop if individuals do not join the corporation but continue to fish and market their own product separately. While this may seem an attractive option to fishers who believe they can do better independently, this is likely to be just a short- term advantage with an overall long-run cost to themselves as well as the rest of the industry. There are also a number of other areas that need further consideration, particularly in relation to the allocation of shares, including who should be allocated shares (e.g. just boat owners or also some employed skippers). Similarly, how harvesting activity is to be allocated by the corporation to the fishers. These are largely issues that cannot be answered without substantial consultation with those likely to be affected, and these groups cannot give these issues serious consideration until the point at which they are likely to become a reality. Given the current structure and complexity of the fishery, it is unlikely that such a management structure will be feasible in the short term. However, the fishery is a prime candidate for such a model, and development of such a management structure in the future should be considered as an option for the longer term.
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Aim: Resolving the origin of invasive plant species is important for understanding the introduction histories of successful invaders and aiding strategies aimed at their management. This study aimed to infer the number and origin(s) of introduction for the globally invasive species, Macfadyena unguis-cati and Jatropha gossypiifolia using molecular data. Location: Native range: Neotropics; Invaded range: North America, Africa, Europe, Asia, Pacific Islands and Australia. Methods: We used chloroplast microsatellites (cpSSRs) to elucidate the origin(s) of introduced populations and calculated the genetic diversity in native and introduced regions. Results: Strong genetic structure was found within the native range of M. unguis-cati, but no genetic structuring was evident in the native range of J. gossypiifolia. Overall, 27 haplotypes were found in the native range of M. unguis-cati. Only four haplotypes were found in the introduced range, with more than 96% of introduced specimens matching a haplotype from Paraguay. In contrast, 15 haplotypes were found in the introduced range of J. gossypiifolia, with all invasive populations, except New Caledonia, comprising multiple haplotypes. Main conclusions: These data show that two invasive plant species from the same native range have had vastly different introduction histories in their non-native ranges. Invasive populations of M. unguis-cati probably came from a single or few independent introductions, whereas most invasive J. gossypiifolia populations arose from multiple introductions or alternatively from a representative sample of genetic diversity from a panmictic native range. As introduced M. unguis-cati populations are dominated by a single haplotype, locally adapted natural enemies should make the best control agents. However, invasive populations of J. gossypiifolia are genetically diverse and the selection of bio-control agents will be considerably more complex.
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This project has contributed to the ecologically sustainable management of mangrove jack in Australia by providing comprehensive information on its biology, habitat requirements, population parameters and stock structure. Specifically, the project has resulted in an enhanced understanding of the life history of Australian mangrove jack, the levels of exploitation in its local fishery and the likely existence of a single genetic stock throughout Queensland.
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TRFLP (terminal restriction fragment length polymorphism) was used to assess whether management practices that improved disease suppression and/or yield in a 4-year ginger field trial were related to changes in soil microbial community structure. Bacterial and fungal community profiles were defined by presence and abundance of terminal restriction fragments (TRFs), where each TRF represents one or more species. Results indicated inclusion of an organic amendment and minimum tillage increased the relative diversity of dominant fungal populations in a system dependant way. Inclusion of an organic amendment increased bacterial species richness in the pasture treatment. Redundancy analysis showed shifts in microbial community structure associated with different management practices and treatments grouped according to TRF abundance in relation to yield and disease incidence. ANOVA also indicated the abundance of certain TRFs was significantly affected by farming system management practices, and a number of these TRFs were also correlated with yield or disease suppression. Further analyses are required to determine whether identified TRFs can be used as general or soil-type specific bio-indicators of productivity (increased and decreased) and Pythium myriotylum suppressiveness.
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Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.
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The emerging carbon economy will have a major impact on grazing businesses because of significant livestock methane and land-use change emissions. Livestock methane emissions alone account for similar to 11% of Australia's reported greenhouse gas emissions. Grazing businesses need to develop an understanding of their greenhouse gas impact and be able to assess the impact of alternative management options. This paper attempts to generate a greenhouse gas budget for two scenarios using a spread sheet model. The first scenario was based on one land-type '20-year-old brigalow regrowth' in the brigalow bioregion of southern-central Queensland. The 50 year analysis demonstrated the substantially different greenhouse gas outcomes and livestock carrying capacity for three alternative regrowth management options: retain regrowth (sequester 71.5 t carbon dioxide equivalents per hectare, CO2-e/ha), clear all regrowth (emit 42.8 t CO2-e/ha) and clear regrowth strips (emit 5.8 t CO2-e/ha). The second scenario was based on a 'remnant eucalypt savanna-woodland' land type in the Einasleigh Uplands bioregion of north Queensland. The four alternative vegetation management options were: retain current woodland structure (emit 7.4 t CO2-e/ha), allow woodland to thicken increasing tree basal area (sequester 20.7 t CO2-e/ha), thin trees less than 10 cm diameter (emit 8.9 t CO2-e/ha), and thin trees <20 cm diameter (emit 12.4 t CO2-e/ha). Significant assumptions were required to complete the budgets due to gaps in current knowledge on the response of woody vegetation, soil carbon and non-CO2 soil emissions to management options and land-type at the property scale. The analyses indicate that there is scope for grazing businesses to choose alternative management options to influence their greenhouse gas budget. However, a key assumption is that accumulation of carbon or avoidance of emissions somewhere on a grazing business (e.g. in woody vegetation or soil) will be recognised as an offset for emissions elsewhere in the business (e.g. livestock methane). This issue will be a challenge for livestock industries and policy makers to work through in the coming years.
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The introduction describes productive forest in Queensland and summaries the principles of native forest management that achieve optimum productivity. Case study 1 deals with thinning an even-aged regrowth forest. It shows how thinning the stand actively manages the future composition and structure to improve productivity in the best stems and increase the commercial value of the next harvest. Case study 2 describes restoring productivity in a high-graded spotted gum - ironbark forest. It shows that defective and non-saleable trees should be removed so they do not repress the future stand; and that regeneration should be thinned, retaining the best trees in adequate growing space. Case study 3 discusses on-farm value adding for hardwood forests. It shows how long-term viability and maximum productivity and returns depend on the best management practices and knowing how to obtain the best returns from a range of forest products. Case study 4 examines integrated harvesting in a eucalypt forest. It shows how integrating the harvest enables the full range of timber products are harvested and sold for their maximum value while reducing the amount of waste.
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Soft-leaf buffalo grass is increasing in popularity as an amenity turfgrass in Australia. This project was instigated to assess the adaptation of and establish management guidelines for its use in Australias vast array of growing environments. There is an extensive selection of soft-leaf buffalo grass cultivars throughout Australia and with the countrys changing climates from temperate in the south to tropical in the north not all cultivars are going to be adapted to all regions. The project evaluated 19 buffalo grass cultivars along with other warm-season grasses including green couch, kikuyu and sweet smother grass. The soft-leaf buffalo grasses were evaluated for their growth and adaptation in a number of regions throughout Australia including Western Australia, Victoria, ACT, NSW and Queensland. The growth habit of the individual cultivars was examined along with their level of shade tolerance, water use, herbicide tolerance, resistance to wear, response to nitrogen applications and growth potential in highly alkaline (pH) soils. The growth habit of the various cultivars currently commercially available in Australia differs considerably from the more robust type that spreads quicker and is thicker in appearance (Sir Walter, Kings Pride, Ned Kelly and Jabiru) to the dwarf types that are shorter and thinner in appearance (AusTine and AusDwarf). Soft-leaf buffalo grass types tested do not differ in water use when compared to old-style common buffalo grass. Thus, soft-leaf buffalo grasses, like other warm-season turfgrass species, are efficient in water use. These grasses also recover after periods of low water availability. Individual cultivar differences were not discernible. In high pH soils (i.e. on alkaline-side) some elements essential for plant growth (e.g. iron and manganese) may be deficient causing turfgrass to appear pale green, and visually unacceptable. When 14 soft-leaf buffalo grass genotypes were grown on a highly alkaline soil (pH 7.5-7.9), cultivars differed in leaf iron, but not in leaf manganese, concentrations. Nitrogen is critical to the production of quality turf. The methods for applying this essential element can be manipulated to minimise the maintenance inputs (mowing) during the peak growing period (summer). By applying the greatest proportion of the turfs total nitrogen requirements in early spring, peak summer growth can be reduced resulting in a corresponding reduction in mowing requirements. Soft-leaf buffalo grass cultivars are more shade and wear tolerant than other warm-season turfgrasses being used by homeowners. There are differences between the individual buffalo grass varieties however. The majority of types currently available would be classified as having moderate levels of shade tolerance and wear reasonably well with good recovery rates. The impact of wear in a shaded environment was not tested and there is a need to investigate this as this is a typical growing environment for many homeowners. The use of herbicides is required to maintain quality soft-leaf buffalo grass turf. The development of softer herbicides for other turfgrasses has seen an increase in their popularity. The buffalo grass cultivars currently available have shown varying levels of susceptibility to the chemicals tested. The majority of the cultivars evaluated have demonstrated low levels of phytotoxicity to the herbicides chlorsulfuron (Glean) and fluroxypyr (Starane and Comet). In general, soft leaf buffalo grasses are varied in their makeup and have demonstrated varying levels of tolerance/susceptibility/adaptation to the conditions they are grown under. Consequently, there is a need to choose the cultivar most suited to the environment it is expected to perform in and the management style it will be exposed to. Future work is required to assess how the structure of the different cultivars impacts on their capacity to tolerate wear, varying shade levels, water use and herbicide tolerance. The development of a growth model may provide the solution.
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The stable isotopes of delta O-18 and delta C-13 in sagittal otolith carbonates were used to determine the stock structure of Grey Mackerel, Scomberomorus semifasciatus. Otoliths were collected from Grey Mackerel at ten locations representing much of their distributional and fisheries range across northern Australia from 2005 to 2007. Across this broad range (similar to 6500 km), fish from four broad locations-Western Australia (S1), Northern Territory and Gulf of Carpentaria (S2, S3, S4, S5, S6, S7), Queensland east coast mid and north sites (S8, S9) and Queensland east coast south site (S10)-had stable isotope values that were significantly different indicating stock separation. Otolith stable isotopes differed more between locations than among years within a location, indicating temporal stability across years. The spatial separation of these populations indicates a complex stock structure across northern Australia. Stocks of S. semifasciatus appear to be associated with large coastal embayments. These results indicate that optimal fisheries management may require a review of the current spatial arrangements, particularly in relation to the evidence of shared stocks in the Gulf of Carpentaria. Furthermore, as the population of S. semifasciatus in Western Australia exhibited high spatial separation from those at all the other locations examined, further research activities should focus on investigating additional locations within Western Australia for an enhanced determination of stock delineation. From the issue entitled "Proceedings of the 4th International Otolith Symposium, 24-28 August 2009, Monterey, California"
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Microsatellite markers were used to examine spatio-temporal genetic variation in the endangered eastern freshwater cod Maccullochella ikei in the Clarence River system, eastern Australia. High levels of population structure were detected. A model-based clustering analysis of multilocus genotypes identified four populations that were highly differentiated by F-statistics (FST = 0· 09 − 0· 49; P < 0· 05), suggesting fragmentation and restricted dispersal particularly among upstream sites. Hatchery breeding programmes were used to re-establish locally extirpated populations and to supplement remnant populations. Bayesian and frequency-based analyses of hatchery fingerling samples provided evidence for population admixture in the hatchery, with the majority of parental stock sourced from distinct upstream sites. Comparison between historical and contemporary wild-caught samples showed a significant loss of heterozygosity (21%) and allelic richness (24%) in the Mann and Nymboida Rivers since the commencement of stocking. Fragmentation may have been a causative factor; however, temporal shifts in allele frequencies suggest swamping with hatchery-produced M. ikei has contributed to the genetic decline in the largest wild population. This study demonstrates the importance of using information on genetic variation and population structure in the management of breeding and stocking programmes, particularly for threatened species.
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Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n = 237) and the milk shark (Rhizoprionodon acutus, n = 207) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751–0.903, respectively; microsatellite loci, 0.038–0.047 respectively). Our results support the spatially homogeneous monitoring and management plan for shark species in Queensland, Australia.
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The common blacktip shark (Carcharhinus limbatus) and the Australian blacktip shark (C. tilstoni) are morphologically similar species that co-occur in subtropical and tropical Australia. In striking contrast to what has been previously reported, we demonstrate that the common blacktip shark is not rare in northern Australia but occurs in approximately equal frequencies with the Australian blacktip shark. Management of shark resources in northern Australia needs to take account of this new information. Species identification was performed using nucleotide sequences of the control, NADH dehydrogenase subunit 4 (ND4) and cytochrome oxidase I (COI) regions in the mitochondrial genome. The proportion of overall genetic variation (FST) between the two species was small (0.042, P < 0.01) based on allele frequencies at five microsatellite loci. We confirm that a third blacktip species (C. amblyrhynchoides, graceful shark) is closely related to C. tilstoni and C. limbatus and can be distinguished from them on the basis of mtDNA sequences from two gene regions. The Australian blacktip shark (C. tilstoni) was not encountered among 20 samples from central Indonesia that were later confirmed to be common blacktip and graceful sharks. Fisheries regulators urgently need new information on life history, population structure and morphological characters for species identification of blacktip shark species in Australia.
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The white-spotted eagle ray Aetobatus narinari is a species complex that occurs circumglobally throughout warm-temperate waters. Aetobatus narinari is semi-pelagic and large (up to 300 cm disc width), suggesting high dispersal capabilities and gene flow on a wide spatial scale. Sequence data from two mitochondrial genes, cytochrome b (cytb) and NADH dehydrogenase subunit 4 (ND4), were used to determine the genetic variability within and among 18 sampling locations in the central Indo-Pacific biogeographical region. Populations in the Indo-Pacific were highly genetically structured with c. 70% of the total genetic variation found among three geographical regions (East China Sea, Southeast Asia and Australia). FST was 0.64 for cytb and 0.53 for ND4, with φST values being even larger, that is, 0.78 for cytb and 0.65 for ND4. This high-level genetic partitioning provides strong evidence against extensive gene flow in A. narinari. The degree of genetic population structuring in the Indo-Pacific was similar to that found on a global scale. Global FST was 0.63 for cytb and 0.57 for ND4, and global φST values were 0.94 for cytb and 0.82 for ND4. This suggests that the A. narinari complex may be more speciose than the two or three species proposed to date. Further sampling and genetic analyses are likely to uncover the ‘evolutionarily significant’ and ‘management’ units that are critical to determine the susceptibilities of individual populations to regional fishing pressures and to provide advice on management options. Network analyses showed a close genetic relationship between haplotypes from the central Indo-Pacific and South Africa, providing support for a proposed dispersal pathway from the possible centre of origin of the A. narinari species complex in the Indo-Pacific into the Atlantic Ocean.
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Aim: This study investigated the use of stable δ13C and δ18O isotopes in the sagittal otolith carbonate of narrow-barred Spanish mackerel, Scomberomorus commerson, as indicators of population structure across Australia. Location: Samples were collected from 25 locations extending from the lower west coast of Western Australia (30°), across northern Australian waters, and to the east coast of Australia (18°) covering a coastline length of approximately 9500 km, including samples from Indonesia. Methods: The stable δ13C and δ18O isotopes in the sagittal otolith carbonate of S. commerson were analysed using standard mass spectrometric techniques. The isotope ratios across northern Australian subregions were subjected to an agglomerative hierarchical cluster analysis to define subregions. Isotope ratios within each of the subregions were compared to assess population structure across Australia. Results: Cluster analysis separated samples into four subregions: central Western Australia, north Western Australia, northern Australia and the Gulf of Carpentaria and eastern Australia. Isotope signatures for fish from a number of sampling sites from across Australia and Indonesia were significantly different, indicating population separation. No significant differences were found in otolith isotope ratios between sampling times (no temporal variation). Main conclusions: Significant differences in the isotopic signatures of S. commerson demonstrate that there is unlikely to be any substantial movement of fish among these spatially discrete adult assemblages. The lack of temporal variation among otolith isotope ratios indicates that S. commerson populations do not undergo longshore spatial shifts in distribution during their life history. The temporal persistence of spatially explicit stable isotopic signatures indicates that, at these spatial scales, the population units sampled comprise functionally distinct management units or separate ‘stocks’ for many of the purposes of fisheries management. The spatial subdivision evident among populations of S. commerson across northern and western Australia indicates that it may be advantageous to consider S. commerson population dynamics and fisheries management from a metapopulation perspective (at least at the regional level).
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The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources and their optimal use relies on robust information on the resource status. For grey mackerel (Scomberomorus semifasciatus) fisheries, each of these jurisdictions has their own management regime in their corresponding waters. The lack of information on stock structure of grey mackerel, however, means that the appropriate spatial scale of management is not known. As well, fishers require assurance of future sustainability to encourage investment and long-term involvement in a fishery that supplies lucrative overseas markets. These management and fisher-unfriendly circumstances must be viewed in the context of recent 3-fold increases in catches of grey mackerel along the Queensland east coast, combined with significant and increasing catches in other parts of the species' northern Australian range. Establishing the stock structure of grey mackerel would also immensely improve the relevance of resource assessments for fishery management of grey mackerel across northern Australia. This highlighted the urgent need for stock structure information for this species. The impetus for this project came from the strategic recommendations of the FRDC review by Ward and Rogers (2003), "Northern mackerel (Scombridae: Scomberomorus): current and future research needs" (Project No. 2002/096), which promoted the urgency for information on the stock structure of grey mackerel. In following these recommendations this project adopted a multi-technique and phased sampling approach as carried out by Buckworth et al (2007), who examined the stock structure of Spanish mackerel, Scomberomorus commerson, across northern Australia. The project objectives were to determine the stock structure of grey mackerel across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the stock structure of grey mackerel. These techniques were: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) isotope ratios, parasite abundances, and growth parameters. The advantage of using this type of multi-technique approach was that each of the different methods is informative about the fish’s life history at different spatial and temporal scales. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Growth patterns are influenced by both genetic and environmental factors. Due to these differences the use of these techniques concurrently increases the likelihood of detecting different stocks where they exist. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year: east coast, eastern Gulf of Carpentaria (GoC), western GoC, and the NW Northern Territory (NW NT). By comparing the fish samples from each of these locations, and using each of the techniques, we tested the null hypothesis that grey mackerel were comprised of a single homogeneous population across northern Australia. Having rejected the null hypothesis we re-sampled the 1st year locations to test for temporal stability in stock structure, and to assess stock structure at finer spatial scales. This included increased spatial coverage on the east coast, the GoC, and WA. From genetic approaches we determined that there at least four genetic stocks of grey mackerel across northern Australia: WA, NW NT (Timor/Arafura), the GoC and the east Grey mackerel management units in northern Australia ix coast. All markers revealed concordant patterns showing WA and NW NT to be clearly divergent stocks. The mtDNA D-loop fragment appeared to have more power to resolve stock boundaries because it was able to show that the GoC and east coast QLD stocks were genetically differentiated. Patterns of stock structure on a finer scale, or where stock boundaries are located, were less clear. From otolith stable isotope analyses four major groups of S. semifasciatus were identified: WA, NT/GoC, northern east coast and central east coast. Differences in the isotopic composition of whole otoliths indicate that these groups must have spent their life history in different locations. The magnitude of the difference between the groups suggests a prolonged separation period at least equal to the fish’s life span. The parasite abundance analyses, although did not include samples from WA, suggest the existence of at least four stocks of grey mackerel in northern Australia: NW NT, the GoC, northern east coast and central east coast. Grey mackerel parasite fauna on the east coast suggests a separation somewhere between Townsville and Mackay. The NW NT region also appears to comprise a separate stock while within the GoC there exists a high degree of variability in parasite faunas among the regions sampled. This may be due to 1. natural variation within the GoC and there is one grey mackerel stock, or 2. the existence of multiple localised adult sub-stocks (metapopulations) within the GoC. Growth parameter comparisons were only possible from four major locations and identified the NW NT, the GoC, and the east coast as having different population growth characteristics. Through the use of multiple techniques, and by integrating the results from each, we were able to determine that there exist at least five stocks of grey mackerel across northern Australia, with some likelihood of additional stock structuring within the GoC. The major management units determined from this study therefore were Western Australia, NW Northern Territory (Timor/Arafura), the Gulf of Carpentaria, northern east Queensland coast and central east Queensland coast. The management implications of these results indicate the possible need for management of grey mackerel fisheries in Australia to be carried out on regional scales finer than are currently in place. In some regions the spatial scales of management might continue as is currently (e.g. WA), while in other regions, such as the GoC and the east coast, managers should at least monitor fisheries on a more local scale dictated by fishing effort and assess accordingly. Stock assessments should also consider the stock divisions identified, particularly on the east coast and for the GoC, and use life history parameters particular to each stock. We also emphasise that where we have not identified different stocks does not preclude the possibility of the occurrence of further stock division. Further, this study did not, nor did it set out to, assess the status of each of the stocks identified. This we identify as a high priority action for research and development of grey mackerel fisheries, as well as a management strategy evaluation that incorporates the conclusions of this work. Until such time that these priorities are addressed, management of grey mackerel fisheries should be cognisant of these uncertainties, particularly for the GoC and the Queensland east coast.