51 resultados para East River


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Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

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Dry seeding of aman rice can facilitate timely crop establishment and early harvest and thus help to alleviate the monga (hunger) period in the High Ganges Flood Plain of Bangladesh. Dry seeding also offers many other potential benefits, including reduced cost of crop establishment and improved soil structure for crops grown in rotation with rice. However, the optimum time for seeding in areas where farmers have access to water for supplementary irrigation has not been determined. We hypothesized that earlier sowing is safer, and that increasing seed rate mitigates the adverse effects of significant rain after sowing on establishment and crop performance. To test these hypotheses, we analyzed long term rainfall data, and conducted field experiments on the effects of sowing date (target dates of 25 May, 10 June, 25 June, and 10 July) and seed rate (20, 40, and 60 kg ha−1) on crop establishment, growth, and yield of dry seeded Binadhan-7 (short duration, 110–120 d) during the 2012 and 2013 rainy seasons. Wet soil as a result of untimely rainfall usually prevented sowing on the last two target dates in both years, but not on the first two dates. Rainfall analysis also suggested a high probability of being able to dry seed in late May/early June, and a low probability of being able to dry seed in late June/early July. Delaying sowing from 25 May/10 June to late June/early July usually resulted in 20–25% lower plant density and lower uniformity of the plant stand as a result of rain shortly after sowing. Delaying sowing also reduced crop duration, and tillering or biomass production when using a low seed rate. For the late June/early July sowings, there was a strong positive relationship between plant density and yield, but this was not the case for earlier sowings. Thus, increasing seed rate compensated for the adverse effect of untimely rains after sowing on plant density and the shorter growth duration of the late sown crops. The results indicate that in this region, the optimum date for sowing dry seeded rice is late May to early June with a seed rate of 40 kg ha−1. Planting can be delayed to late June/early July with no yield loss using a seed rate of 60 kg ha−1, but in many years, the soil is simply too wet to be able to dry seed at this time due to rainfall.

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The gall rusts on Acacia spp. and Paraserianthes falcataria are caused by species of Uromycladium. Morphology and a phylogenetic analysis of four loci from ribosomal (SSU, ITS, LSU) and mitochondrial (CO3) DNA, showed that the rust on P. falcataria differed from U. tepperianum. Uromycladium falcatarium sp. nov. is described to accommodate this taxon, which can be differentiated from other species of Uromycladium by teliospore wall morphology, host genus and DNA sequence data.