Host recognition by a polyphagous lepidopteran (Helicoverpa armigera): Primary host plants, host produced volatiles and neurosensory stimulation

An important question in the host-finding behaviour of a polyphagous insect is whether the insect recognizes a suite or template of chemicals that are common to many plants? To answer this question, headspace volatiles of a subset of commonly used host plants (pigeon pea, tobacco, cotton and bean) and nonhost plants (lantana and oleander) of Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) are screened by gas chromatography (GC) linked to a mated female H. armigera electroantennograph (EAG). In the present study, pigeon pea is postulated to be a primary host plant of the insect, for comparison of the EAG responses across the test plants. EAG responses for pigeon pea volatiles are also compared between females of different physiological status (virgin and mated females) and the sexes. Eight electrophysiologically active compounds in pigeon pea headspace are identified in relatively high concentrations using GC linked to mass spectrometry (GC-MS). These comprised three green leaf volatiles [(2E)-hexenal, (3Z)-hexenylacetate and (3Z)-hexenyl-2-methylbutyrate] and five monoterpenes (α-pinene, β-myrcene, limonene, E-β-ocimene and linalool). Other tested host plants have a smaller subset of these electrophysiologically active compounds and even the nonhost plants contain some of these compounds, all at relatively lower concentrations than pigeon pea. The physiological status or sex of the moths has no effect on the responses for these identified compounds. The present study demonstrates how some host plants can be primary targets for moths that are searching for hosts whereas the other host plants are incidental or secondary targets.

In vitro detection and primary cultivation of bacteria producing materials inhibitory to ruminal methanogens.

A novel method for screening bacterial isolates for their potential to inhibit the growth of ruminal methanogenic Archaea was developed using a modification of the soft agar overlay technique, formally used for the isolation of lytic bacteriophages. This method may be used in the specific, hydrogen-rich conditions required for the growth of ruminal methanogenic Archaea.

IUCN classification zones concord with, but underestimate, the population genetic structure of the zebra shark Stegostoma fasciatum in the Indo-West Pacific

The Indo-West Pacific (IWP), from South Africa in the western Indian Ocean to the western Pacific Ocean, contains some of the most biologically diverse marine habitats on earth, including the greatest biodiversity of chondrichthyan fishes. The region encompasses various densities of human habitation leading to contrasts in the levels of exploitation experienced by chondrichthyans, which are targeted for local consumption and export. The demersal chondrichthyan, the zebra shark, Stegostoma fasciatum, is endemic to the IWP and has two current regional International Union for the Conservation of Nature (IUCN) Red List classifications that reflect differing levels of exploitation: ‘Least Concern’ and ‘Vulnerable’. In this study, we employed mitochondrial ND4 sequence data and 13 microsatellite loci to investigate the population genetic structure of 180 zebra sharks from 13 locations throughout the IWP to test the concordance of IUCN zones with demographic units that have conservation value. Mitochondrial and microsatellite data sets from samples collected throughout northern Australia and Southeast Asia concord with the regional IUCN classifications. However, we found evidence of genetic subdivision within these regions, including subdivision between locations connected by habitat suitable for migration. Furthermore, parametric FST analyses and Bayesian clustering analyses indicated that the primary genetic break within the IWP is not represented by the IUCN classifications but rather is congruent with the Indonesian throughflow current. Our findings indicate that recruitment to areas of high exploitation from nearby healthy populations in zebra sharks is likely to be minimal, and that severe localized depletions are predicted to occur in zebra shark populations throughout the IWP region.

Determination of management units for grey mackerel fisheries in northern Australia.

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.

Testing the effectiveness of the SKIM foam fractionator to reduce nutrient levels in prawn farm effluent

To experimentally investigate the effect of the “SKIM” mechanical foam fractionator on suspended material and the nutrient levels in prawn farm effluent, a series of standardised short-term treatments were applied to various effluent types in a static 10,000-litre water body. Prawn pond effluents were characterised by watercolour and dominance of phytoplankton species. Three effluent types were tested, namely 1) particulate-rich effluent with little apparent phytoplankton, 2) green mircoalgal bloom predominately made up of single celled phytoplankton, and 3) brown microalgal bloom with higher prevalence of diatoms. The effluent types were similar (P>0.05) in non-volatile particulate material, and nitrate/nitrite but varied from each other in the following ways: 1) The particulate-rich effluents were lower (P<0.05) in volatile solids (compared to brown blooms), total Kjeldahl nitrogen, dissolved organic nitrogen, dissolved organic phosphorus and chlorophyll a (compared to both green and brown blooms). 2) The brown blooms were higher (P<0.05) in ammonia (compared to green blooms), total nitrogen and total phosphorus (compared to both green and particulate-rich effluent), but were lower (P<0.05) in inorganic phosphorus (compared to both green and particulate-rich effluent). 3) The green blooms were higher (P<0.05) in dissolved (both organic and inorganic) phosphorus (compared to both brown and particulate-rich effluents). Although the effluent types varied significantly in these aspects the effect of the Skim treatment was similar for all parameters measured except total phosphorus. Bloom type and Skim-treatment period significantly (P<0.05) affected total Kjeldahl phosphorus concentrations. For all effluent types there was a continuous significant reduction (P<0.05) in total Kjeldahl phosphorus during the initial 6-hour treatment period. Levels of total suspended solids and volatile suspended solids in all effluent types were significantly (P<0.05) reduced in the first 2 hours but not thereafter. Non-volatile suspended solids were also significantly (P<0.05) reduced in the first 2 hours (30 to 40 % reduction) and a further 40% reduction occurred in the particulate-rich effluent over the next 2 hours. Mean values for total ammonia, dissolved organic nitrogen, total Kjeldahl nitrogen, total nitrogen, chlorophyll a and dissolved organic or inorganic phosphorus levels were not significantly (P>0.05) affected by the Skim unit in any bloom type during the initial 6 hours of testing. Nevertheless, non-significant nitrogen reductions did occur. Foam production by the Skim unit varied with different blooms, resulting in different concentrate volumes and different end points for separate experiments. Concentrate volumes were generally high for the particulate-rich and green blooms (175 – 370 litres) and low for the brown blooms (25 – 80 litres). This was due to the low tendency of the brown bloom to produce foam. This generated higher nutrient concentrations in the associated condensed foam, but may have limited the treatment efficiency. The results suggest that in this application, the Skim unit did not remove micro-algae as effectively as was anticipated. However, it was effective at removing other suspended solids. Considering these attributes and the other uses of this machinery documented by the manufactures, the unit’s oxygenation mixing capacities coupled with inorganic solids removal may provide a suitable mechanism for construction of a continuously mixed bioreactor that utilises the filtration and profit making abilities of bivalves.

Multiple host use by a sap-sucking membracid: population consequences of nymphal development on primary and secondary host plant species

Aconophora compressa is a gregarious, sap-sucking insect that uses multiple host plant species. Nymphal host plant species (and variety) significantly affected nymphal survival, nymphal development rate and the subsequent size and fecundity of adults, with fiddlewood ( Citharexylum spinosum ) being significantly best in all respects. Nymphs that developed on a relatively poor host ( Duranta erecta var “geisha girl”) and which were moved to fiddlewood as adults laid significantly fewer eggs (mean ± SE = 836 ± 130) than those that developed solely on fiddlewood (1,329 ± 105). Adults on geisha girl, regardless of having been reared as nymphs on fiddlewood or geisha girl, laid significantly fewer eggs (342 ± 83 and 317 ± 74, respectively) than adults on fiddlewood. A simple model that incorporates host plant related survival, development rate and fecundity suggests that the population dynamics of A. compressa are governed mainly by fiddlewood, the primary host. The results have general implications for understanding the population dynamics of herbivores that use multiple host plant species, and also for the way in which weed biological control host testing methods should be conducted.