24 resultados para Allozymes,Cooper Creek, Fish, Genetic Structuring, Lake Eyre Basin, Microsatellites, Mitochondrial DNA, Warrego River

em eResearch Archive - Queensland Department of Agriculture


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Species delineation in the spotted gum complex was revisited focusing on Corymbia maculata. This study expands the range of C. maculata analysed with microsatellite markers to include populations from the north of the species range. It supported earlier findings that it is a cohesive genetic entity, well resolved from northern spotted gum taxa, Corymbia citriodora and Corymbia henryi; and inferences that its insularity is due to early lineage divergence and historical isolation. The northern extent of C. maculata sampled, as defined by chloroplast and nuclear genomes predominantly of C. maculata character, was the location of Kiwarrak, south of the Manning River near Taree in New South Wales. Trees from a recognised intergrade zone at the Yarratt locality, around 26 km north of Kiwarrak, also possessed a uniquely C. maculata chloroplast haplotype, but their nuclear genomes were predominantly of northern taxa ancestry. Range expansion of northern taxa leading to southerly gene movement into populations formerly C. maculata, would account for this apparent instance of chloroplast capture. Two subpopulations were identified in C. maculata, a northern population of which the Ourimbah locality was the most southerly studied, and a southern population of which Wingello was the most northerly locality studied. Diminished levels of northern taxa ancestry, i.e. C. citriodora or C. henryi, in individuals from the southern, relative to the northern subpopulation of C. maculata, suggested that secondary contact with northern taxa contributes to its substructure.

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Using mitochondrial DNA for species identification and population studies assumes that the genome is maternally inherited, circular, located in the cytoplasm and lacks recombination. This study explores the mitochondrial genomes of three anomalous mackerel. Complete mitochondrial genome sequencing plus nuclear microsatellite genotyping of these fish identified them as Scomberomorus munroi (spotted mackerel). Unlike normal S. munroi, these three fish also contained different linear, mitochondrial genomes of Scomberomorus semifasciatus (grey mackerel). The results are best explained by hybridisation, paternal leakage and mitochondrial DNA linearization. This unusual observation may provide an explanation for mtDNA outliers in animal population studies. © 2013.

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The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.

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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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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.

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Background:Quantifying genetic diversity and metapopulation structure provides insights into the evolutionary history of a species and helps develop appropriate management strategies. We provide the first assessment of genetic structure in spinner sharks (Carcharhinus brevipinna), a large cosmopolitan carcharhinid, sampled from eastern and northern Australia and South Africa. Methods and Findings:Sequencing of the mitochondrial DNA NADH dehydrogenase subunit 4 gene for 430 individuals revealed 37 haplotypes and moderately high haplotype diversity (h = 0.6770 ±0.025). While two metrics of genetic divergence (ΦST and FST) revealed somewhat different results, subdivision was detected between South Africa and all Australian locations (pairwise ΦST, range 0.02717–0.03508, p values ≤ 0.0013; pairwise FST South Africa vs New South Wales = 0.04056, p = 0.0008). Evidence for fine-scale genetic structuring was also detected along Australia’s east coast (pairwise ΦST = 0.01328, p < 0.015), and between south-eastern and northern locations (pairwise ΦST = 0.00669, p < 0.04).Conclusions: The Indian Ocean represents a robust barrier to contemporary gene flow in C. brevipinna between Australia and South Africa. Gene flow also appears restricted along a continuous continental margin in this species, with data tentatively suggesting the delineation of two management units within Australian waters. Further sampling, however, is required for a more robust evaluation of the latter finding. Evidence indicates that all sampled populations were shaped by a substantial demographic expansion event, with the resultant high genetic diversity being cause for optimism when considering conservation of this commercially-targeted species in the southern Indo-Pacific.

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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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Coastal seagrass habitats in tropical and subtropical regions support aggregations of resident green turtles (Chelonia mydas) from several genetically distinct breeding populations. Migration of individuals to their respective dispersed breeding sites provides a complex pattern of migratory connectivity among nesting and feeding habitats of this species. An understanding of this pattern is important in regions where the persistence of populations is under threat from anthropogenic impacts. The present study uses mitochondrial DNA and mixed-stock analyses to assess the connectivity among seven feeding grounds across the north Australian coast and adjacent areas and 17 genetically distinct breeding populations from the Indo-Pacific region. It was hypothesised that large and geographically proximate breeding populations would dominate at nearby feeding grounds. As expected, each sampled feeding area appears to support multiple breeding populations, with two aggregations dominated by a local breeding population. Geographic distance between breeding and feeding habitat strongly influenced whether a breeding population contributed to a feeding ground (wi = 0.654); however, neither distance nor size of a breeding population was a good predictor of the extent of their contribution. The differential proportional contributions suggest the impact of anthropogenic mortality at feeding grounds should be assessed on a case-by-case basis.

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Mitochondrial DNA D-loop (control) region (426-bp) was used to infer the genetic structure of Spanish mackerel (Scomberomorus commerson) from populations in Southeast Asia (Brunei, East and West Malaysia, Philippines, Thailand, Singapore, and China) and northern Australia (including western Timor). An east–west division along Wallace’s Line was strongly supported by a significant AMOVA, with 43% of the total sequence variation partitioned among groups of populations. Phylogenetic and network analyses supported two clades: clade A and clade B. Members of clade A were found in Southeast Asia and northern Australia, but not in locations to the west (Gulf of Thailand) or north (China). Clade B was found exclusively in Southeast Asia. Genetic division along Wallace’s Line suggests that co-management of S. commerson populations for future sustainability may not be necessary between Southeast Asian nations and Australia, however all countries should share the task of management of the species in Southeast Asia equally. More detailed genetic studies of S. commerson populations in the region are warranted.

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Background: The territorial fishing zones of Australia and Indonesia are contiguous to the north of Australia in the Timor and Arafura Seas and in the Indian Ocean to the north of Christmas Island. The area surrounding the shared boundary consists of a variety of bio-diverse marine habitats including shallow continental shelf waters, oceanic trenches and numerous offshore islands. Both countries exploit a variety of fisheries species, including whaler (Carcharhinus spp.) and hammerhead sharks (Sphyrna spp.). Despite their differences in social and financial arrangements, the two countries are motivated to develop complementary co-management practices to achieve resource sustainability. An essential starting point is knowledge of the degree of population subdivision, and hence fisheries stock status, in exploited species. Results: Populations of four commercially harvested shark species (Carcharhinus obscurus, Carcharhinus sorrah, Prionace glauca, Sphyrna lewini) were sampled from northern Australia and central Indonesia. Neutral genetic markers (mitochondrial DNA control region sequence and allelic variation at co-dominant microsatellite loci) revealed genetic subdivision between Australian and Indonesian populations of C. sorrah. Further research is needed to address the possibility of genetic subdivision among C. obscurus populations. There was no evidence of genetic subdivision for P. glauca and S. lewini populations, but the sampling represented a relatively small part of their distributional range. For these species, more detailed analyses of population genetic structure is recommended in the future. Conclusion: Cooperative management between Australia and Indonesia is the best option at present for P. glauca and S. lewini, while C. sorrah and C. obscurus should be managed independently. On-going research on these and other exploited shark and ray species is strongly recommended. Biological and ecological similarity between species may not be a predictor of population genetic structure, so species-specific studies are recommended to provide new data to assist with sustainable fisheries management.

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‘Sustainable Grazing in the Channel Country Floodplains’ was initiated by industry to redress the lack of objective information for sustainable management in the floodplains of Cooper Creek and the Diamantina and Georgina Rivers. The project has maintained links with the grazing community and has extensively drawn upon expert local experience and knowledge. The project has provided tools for managers to better anticipate the size of beneficial flooding arising from rains in the upper catchment and to more objectively assess the value of the pasture resulting from flooding. The latest information from the project has enabled customisation of the EDGENetwork™ Grazing Land Management training package for the Channel Country. In combination, these tools will assist in making earlier cattle stocking decisions, including when cattle may need to be mustered out of floodplain paddocks, how many additional cattle will be required to take advantage of the flood–grown pasture, and the timing of cattle turnoff. These will reduce costs by providing a greater lead time to plan cattle movements and purchases, and may enhance the sustainability of the resource base by better matching cattle numbers with the feed on offer.

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Invasive species pose a major threat to aquatic ecosystems. Their impact can be particularly severe in tropical regions, like those in northern Australia, where >20 invasive fish species are recorded. In temperate regions, environmental DNA (eDNA) technology is gaining momentum as a tool to detect aquatic pests, but the technology's effectiveness has not been fully explored in tropical systems with their unique climatic challenges (i.e. high turbidity, temperatures and ultraviolet light). In this study, we modified conventional eDNA protocols for use in tropical environments using the invasive fish, Mozambique tilapia (Oreochromis mossambicus) as a detection model. We evaluated the effects of high water temperatures and fish density on the detection of tilapia eDNA, using filters with larger pores to facilitate filtration. Large-pore filters (20 μm) were effective in filtering turbid waters and retaining sufficient eDNA, whilst achieving filtration times of 2-3 min per 2-L sample. High water temperatures, often experienced in the tropics (23, 29, 35 °C), did not affect eDNA degradation rates, although high temperatures (35 °C) did significantly increase fish eDNA shedding rates. We established a minimum detection limit for tilapia (1 fish/0.4 megalitres/after 4 days) and found that low water flow (3.17 L/s) into ponds with high fish density (>16 fish/0.4 megalitres) did not affect eDNA detection. These results demonstrate that eDNA technology can be effectively used in tropical ecosystems to detect invasive fish species. © 2016 John Wiley & Sons Ltd.

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Soybean Stem Fly (SSF), Melanagromyza sojae (Zehntner), belongs to the family Agromyzidae and is highly polyphagous, attacking many plant species of the family Fabaceae, including soybean and other beans. SSF is regarded as one of the most important pests in soybean fields of Asia (e.g., China, India), North East Africa (e.g., Egypt), parts of Russia, and South East Asia. Despite reports of Agromyzidae flies infesting soybean fields in Rio Grande do Sul State (Brazil) in 1983 and 2009 and periodic interceptions of SSF since the 1940s by the USA quarantine authorities, SSF has not been officially reported to have successfully established in the North and South Americas. In South America, M. sojae was recently confirmed using morphology and its complete mitochondrial DNA (mtDNA) was characterized. In the present study, we surveyed the genetic diversity of M. sojae, collected directly from soybean host plants, using partial mtDNA cytochrome oxidase I (COI) gene, and provide evidence of multiple (>10) maternal lineages in SSF populations in South America, potentially representing multiple incursion events. However, a single incursion involving multiple-female founders could not be ruled out. We identified a haplotype that was common in the fields of two Brazilian states and the individuals collected from Australia in 2013. The implications of SSF incursions in southern Brazil are discussed in relation to the current soybean agricultural practices, highlighting an urgent need for better understanding of SSF population movements in the New World, which is necessary for developing effective management options for this significant soybean pest. © FUNPEC-RP.

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Patterns of mitochondrial DNA (mtDNA) variation were used to analyse the population genetic structure of southwestern Indian Ocean green turtle (Chelonia mydas) populations. Analysis of sequence variation over 396 bp of the mtDNA control region revealed seven haplotypes among 288 individuals from 10 nesting sites in the Southwest Indian Ocean. This is the first time that Atlantic Ocean haplotypes have been recorded among any Indo-Pacific nesting populations. Previous studies indicated that the Cape of Good Hope was a major biogeographical barrier between the Atlantic and Indian Oceans because evidence for gene flow in the last 1.5 million years has yet to emerge. This study, by sampling localities adjacent to this barrier, demonstrates that recent gene flow has occurred from the Atlantic Ocean into the Indian Ocean via the Cape of Good Hope. We also found compelling genetic evidence that green turtles nesting at the rookeries of the South Mozambique Channel (SMC) and those nesting in the North Mozambique Channel (NMC) belong to separate genetic stocks. Furthermore, the SMC could be subdivided in two different genetic stocks, one in Europa and the other one in Juan de Nova. We suggest that this particular genetic pattern along the Mozambique Channel is attributable to a recent colonization from the Atlantic Ocean and is maintained by oceanic conditions in the northern and southern Mozambique Channel that influence early stages in the green turtle life cycle.

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Small juveniles of the nine species of scombrids in Australian waters are morphologically similar to one another and, consequently, difficult to identify to species level. We show that the sequence of the mitochondrial DNA cytochrome b gene region is a powerful tool for identification of these young fish. Using this method, we identified 50 juvenile scombrids collected from Exmouth Bay, Western Australia. Six species of scombrids were apparent in this sample of fish: narrow-barred Spanish mackerel (Scomberomorus commerson), Indian mackerel (Rastrelliger kanagurta), frigate tuna (Auxis thazard), bullet tuna (Auxis rochei), leaping bonito (Cybiosarda elegans), and kawakawa (Euthynnus affinis). The presence of Indian mackerel, frigate tuna, leaping bonito, and kawakawa is the first indication that coastal waters may be an important spawning habitat for these species, although offshore spawning may also occur. The occurrence of small juvenile S. commerson was predicted from the known spawning patterns of that species, but other mackerel species (Scomberomorus munroi, Scomberomorus queenslandicus, Scomberomorus semifasiciatus) likely to be spawning during the sampling period were not detected among the 50 small juveniles analyzed here.