7 resultados para distribution pattern

em eResearch Archive - Queensland Department of Agriculture


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A spatially explicit multi-competitor coexistence model was developed for meta-populations of prawns (shrimp) occupying habitat patches across the Great Barrier Reef, where dispersal was localised and dispersal rates varied between species. Prawns were modelled as individuals moving to and from patches or cells according to pre-set decision rules. The landscape was simulated as a matrix of cells with each cell having a spatially explicit survival index for each species. Mixed species prawn assemblages moved over this simplified spatially explicit landscape. A low level of chronic random environmental disturbance was assumed (cyclone and tropical storm damage) with additional acute spatially confined disturbance due to commercial trawling, modelled as an increase in mortality affecting inter-specific competition. The general form of the results was for increased disturbance to favour good-colonising "generalist" species at the expense of good-competitor "specialists". Increasing fishing mortality (local patch extinctions) combined with poor colonising ability resulted in low equilibrium abundance for even the best competitor, while in the same circumstances the poorest competitor but best coloniser could have the highest equilibrium abundance. This mimics the switch from high-value prawn species to lower-value prawn species as trawl effort increases, reflected in historic catch and effort logbook data and reported anecdotaly from the north Queensland trawl fleet. To match the observed distribution and behaviour of prawn assemblages, a combination inter-species competition, a spatially explicit landscape, and a defined pattern of disturbance (trawling) was required. Modelling this combination could simulate not only general trends in spatial distribution of each of prawn species but also localised concentrations observed in the survey data

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Data from the eradication of the incursion of Bactrocera papayae Drew and Hancock (Dipt.: Tephritidae) in Australia (1995-1998) are used to assess the significance of various aspects of invasion theory, including the influence of towns on establishment, influence of propagule pressure on the pattern of establishment, and the existence of source-sink dynamics. Because there were no sentinel traps in place, considerable spread had occurred before the eradication campaign started. The distribution of fly density around the epicentre in the town of Cairns and a transect along the main traffic routes to the north and south fitted a Cauchy model with a tail having the same slope as a power model with an exponent of -2.4 extending to 160 km. The Cauchy model indicated that 50% of the flies on the transect would have occurred within 3.2 km of the epicentre, 90% within 13.2 km, and 99% within 60 km. The two major satellites at Mareeba (35 km from the epicentre in Cairns) and Mossman (65 km) were not used for the transect data and had respectively 15 and 30 times the density predicted by the model. The proportion of traps that caught flies (a measure of site occupancy) fell with distance from the epicentre. B. papayae was trapped consistently on only three of the 16 rainforest transects that were surveyed and these were relatively close to urban areas where eradication efforts were intense. Despite there being no eradication effort in the rainforest, the trends to extinction were similar to those in adjacent areas. The strategy of initially concentrating eradication efforts on the core and major satellites while maintaining a quarantine barrier at the airport and the boundaries of the infested area appears to be the key to the containment and rapid eradication of the incursion.

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Factors that influence the localized abundance and distribution of lesser mealworm, Alphitobius diaperinus (Panzer), in litter of two compacted earth-floor broiler houses in subtropical Australia were studied using various experimental manipulations. Numbers of lesser mealworms substantially increased inside caged areas and under uncaged empty feed pans placed in open areas of the houses. These populations were found to be localized and independent of chicken-feed, manure, and high beetle populations that normally occur under existing feed pans. Substantial horizontal movement of larvae to under feed pans was recorded. Placing metal barriers around these pans significantly restricted this movement. In almost all treatments, lesser mealworms typically peaked in numbers during the middle of the flock time. This temporal pattern of abundance also was observed under pans within barriers, where relatively low insect numbers occurred, but it was not observed in uncaged open areas (where chickens had complete access). It is likely that larvae do not establish in open areas, but fluctuate in numbers as they either move to refuges away from chickens or suffer high rates of mortality. In these refuges, larvae peak in numbers and then leave the litter environment to pupate in the earth floor before the end of the flock time. This behavior might be exploited for management of lesser mealworm by targeting applications of control agents.

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Electroreception is an ancient sense found in many aquatic animals, including sharks, which may be used in the detection of prey, predators and mates. Wobbegong sharks (Orectolobidae) and angel sharks (Squatinidae) represent two distantly related families that have independently evolved a similar dorso-ventrally compressed body form to complement their benthic ambush feeding strategy. Consequently, these groups represent useful models in which to investigate the specific morphological and physiological adaptations that are driven by the adoption of a benthic lifestyle. In this study, we compared the distribution and abundance of electrosensory pores in the spotted wobbegong shark (Orectolobus maculatus) with the Australian angel shark (Squatina australis) to determine whether both species display a similar pattern of clustering of sub-dermal electroreceptors and to further understand the functional importance of electroreception in the feeding behaviour of these benthic sharks. Orectolobus maculatus has a more complex electrosensory system than S. australis, with a higher abundance of pores and an additional cluster of electroreceptors positioned in the snout (the superficial ophthalmic cluster). Interestingly, both species possess a cluster of pores (the hyoid cluster, positioned slightly posterior to the first gill slit) more commonly found in rays, but which may be present in all benthic elasmobranchs to assist in the detection of approaching predators.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships with four modeling methods run with multiple scenarios of (1) sources of occurrences and geographically isolated background ranges for absences, (2) approaches to drawing background (absence) points, and (3) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved by using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e. into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g. boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post-hoc test conducted on a new Partenium dataset from Nepal validated excellent predictive performance of our “best” model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for Parthenium hysterophorus L. (Asteraceae; parthenium). However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed. This article is protected by copyright. All rights reserved.

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Banana bunchy top virus (BBTV; family Nanoviridae, genus Babuvirus) is a multi-component single-stranded DNA virus, which infects banana plants in many regions of the world, often resulting in large-scale crop losses. Weanalyzed 171 banana leaf samples from fourteen countries and recovered, cloned, and sequenced 855 complete BBTV components including ninety-four full genomes. Importantly, full genomes were determined from eight countries, where previously no full genomes were available (Samoa, Burundi, Republic of Congo, Democratic Republic of Congo, Egypt, Indonesia, the Philippines, and the USA [HI]). Accounting for recombination and genome component reassortment, we examined the geographic structuring of global BBTV populations to reveal that BBTV likely originated in Southeast Asia, that the current global hotspots of BBTV diversity are Southeast Asia/Far East and India, and that BBTV populations circulating elsewhere in the world have all potentially originated from infrequent introductions. Most importantly, we find that rather than the current global BBTV distribution being due to increases in human-mediated movements of bananas over the past few decades, it is more consistent with a pattern of infrequent introductions of the virus to different parts of the world over the past 1,000 years.