241 resultados para fire tolerant species
Resumo:
Invasive and noxious weeds are well known as a pervasive problem, imposing significant economic burdens on all areas of agriculture. Whilst there are multiple possible pathways of weed dispersal in this industry, of particular interest to this discussion is the unintended dispersal of weed seeds within fodder. During periods of drought or following natural disasters such as wild fire or flood, there arises the urgent need for 'relief' fodder to ensure survival and recovery of livestock. In emergency situations, relief fodder may be sourced from widely dispersed geographic regions, and some of these regions may be invaded by an extensive variety of weeds that are both exotic and detrimental to the intended destination for the fodder. Pasture hay is a common source of relief fodder and it typically consists of a mixture of grassy and broadleaf species that may include noxious weeds. When required urgently, pasture hay for relief fodder can be cut, baled, and transported over long distances in a short period of time, with little opportunity for prebaling inspection. It appears that, at the present time, there has been little effort towards rapid testing of bales, post-baling, for the presence of noxious weeds, as a measure to prevent dispersal of seeds. Published studies have relied on the analysis of relatively small numbers of bales, tested to destruction, in order to reveal seed species for identification and enumeration. The development of faster, more reliable, and non-destructive sampling methods is essential to increase the fodder industry's capacity to prevent the dispersal of noxious weeds to previously unaffected locales.
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Emerging literature on climate adaptation suggests the need for effective ways of engaging or activating communities and supporting community roles, coupled with whole-of-system approaches to understanding climate change and adaptation needs. We have developed and evaluated a participatory approach to elicit community and stakeholder understanding of climate change adaptation needs, and connect diverse community members and local office bearers towards potential action. The approach was trialed in a series of connected social-ecological systems along a transect from a rural area to the coast and islands of ecologically sensitive Moreton Bay in Queensland, Australia. We conducted ‘climate roundtables’ in each of three areas along the transect, then a fourth roundtable reviewed and extended the results to the region as a whole. Influence diagrams produced through the process show how each climate variable forecast to affect this region (heat, storm, flood, sea-level rise, fire, drought) affects the natural environment, infrastructure, economic and social behaviour patterns, and psychosocial responses, and how sets of people, species and ecosystems are affected, and act, differentially. The participatory process proved effective as a way of building local empathy, a local knowledge base and empowering participants to join towards future climate adaptation action. Key principles are highlighted to assist in adapting the process for use elsewhere.
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Two previously unrecognisable species of Australian thrips described by A.A. Girault are placed generically. Giraultithrips gen. n. is described to include G. nigricoxa (Girault), comb, n., originally placed in Bagnalliella Karny and currently included in Haplothrips Amyot & Serville, while Azaleothrips perniger (Girault), comb. n. is transferred from Glyptothrips Hood.
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Three new species of Tilletia are described from species of Eriachne (Poaceae) in the arid tropics of north-western Australia. In Western Australia, T. mactaggartii sp. nov. infects E. burkittii, and T. geeringii sp. nov. infects E. festucacea. Tilletia marjaniae sp. nov. infects E. pulchella subsp. dominii in Western Australia and the Northern Territory. These species are the first records of Tilletia on Eriachne. Phylogenetic relationships of these species were inferred from internal transcribed spacer of ribosomal RNA region and large subunit ribosomal RNA gene sequences.
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The Australian lungfish is a unique living representative of an ancient dipnoan lineage, listed as ‘vulnerable’ to extinction under Australia’s
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Novel species of Cercospora and Pseudocercospora are described from Australian native plant species. These taxa are Cercospora ischaemi sp. nov. on Ischaemum australe (Poaceae); Pseudocercospora airliensis sp. nov. on Polyalthia nitidissima (Annonaceae); Pseudocercospora proiphydis sp. nov. on Proiphys amboinensis (Amaryllidaceae); and Pseudocercospora jagerae sp. nov. on Jagera pseudorhus var. pseudorhus (Sapindaceae). These species were characterised by morphology and an analysis of partial nucleotide sequence data for the three gene loci, ITS, LSU and EF-1α. Recent divergence of closely related Australian species of Pseudocercospora on native plants is proposed.
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The black rot disease of Vitis species and other host genera of Vitacease is caused by Phyllosticta ampelicida and allied taxa which is considered to be a species complex. In this paper, we introduce four new species of Phyllosticta, including two from the P. ampelicida complex, based on a polyphasic characterization including disease symptoms and host association, morphology, and molecular phylogeny. The phylogenetic analysis was conducted based on the ribosomal internal transcribed spacer (ITS) region and a combined multi-locus alignment of the ITS, actin (ACT), partial translation elongation factor 1-alpha (TEF-1), and glyceraldehydes 3-phosphate dehydrogenase (GPDH) gene regions. Our study confirms the phylogenetic distinctions of the four new species, as well as their phenotypic differences with known species in the genus.
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AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.
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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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Puccinia psidii, the causal agent of myrtle rust, was first recorded from Latin America more than 100 years ago. It occurs on many native species of Myrtaceae in Latin America and also infects non-native plantation-grown Eucalyptus species in the region. The pathogen has gradually spread to new areas including Australia and most recently South Africa. The aim of this study was to consider the susceptibility of selected Eucalyptus genotypes, particularly those of interest to South African forestry, to infection by P. psidii. In addition, risk maps were compiled based on suitable climatic conditions and the occurrence of potential susceptible tree species. This made it possible to identify the season when P. psidii would be most likely to infect and to define the geographic areas where the rust disease would be most likely to establish in South Africa. As expected, variation in susceptibility was observed between eucalypt genotypes tested. Importantly, species commonly planted in South Africa show good potential for yielding disease-tolerant material for future planting. Myrtle rust is predicted to be more common in spring and summer. Coastal areas, as well as areas in South Africa with subtropical climates, are more conducive to outbreaks of the pathogen.
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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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Partial virus genome sequence with high nucleotide identity to Cotton leafroll dwarf virus (CLRDV) was identified from two cotton (Gossypium hirsutum) samples from Thailand displaying typical cotton leaf roll disease symptoms. We developed and validated a PCR assay for the detection of CLRDV isolates from Thailand and Brazil.
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A quarter of Australia’s sunflower production is from the central highlands region of Queensland and is currently worth six million dollars ($AUD) annually. From the early 2000s a severe necrosis disorder of unknown aetiology was affecting large areas of sunflower crops in central Queensland, leading to annual losses of up to 20%. Other crops such as mung bean and cotton were also affected. This PhD study was undertaken to determine if the causal agent of the necrosis disorder was of viral origin and, if so, to characterise its genetic diversity, biology and disease cycle, and to develop effective control strategies. The research described in this thesis identified Tobacco streak virus (TSV; genus Ilarvirus, family Bromoviridae) as the causal agent of the previously unidentified necrosis disorder of sunflower in central Queensland. TSV was also the cause of commonly found diseases in a range of other crops in the same region including cotton, chickpea and mung bean. This was the first report from Australia of natural field infections of TSV from these four crops. TSV strains have previously been reported from other regions of Australia in several hosts based on serological and host range studies. In order to determine the relatedness of previously reported TSV strains with TSV from central Queensland, we characterised the genetic diversity of the known TSV strains from Australia. We identified two genetically distinct TSV strains from central Queensland and named them based on their major alternative hosts, TSV-parthenium from Parthenium hysterophorus and TSV-crownbeard from Verbesina encelioides. They share only 81 % total-genome nucleotide sequence identity. In addition to TSV-parthenium and TSV-crownbeard from central Queensland, we also described the complete genomes of two other ilarvirus species. This proved that previously reported TSV strains, TSV-S isolated from strawberry and TSV-Ag from Ageratum houstonianum, were actually the first record of Strawberry necrotic shock virus from Australia, and a new subgroup 1 ilarvirus, Ageratum latent virus. Our results confirmed that the TSV strains found in central Queensland were not related to previously described strains from Australia and may represent new incursions. This is the first report of the genetic diversity within subgroup 1 ilarviruses from Australia. Based on field observations we hypothesised that parthenium and crownbeard were acting as symptomless hosts of TSV-parthenium and TSV-crownbeard, respectively. We developed strain-specific multiplex PCRs for the three RNA segments to accurately characterise the range of naturally infected hosts across central Queensland. Results described in this thesis show compelling evidence that parthenium and crownbeard are the major (symptomless) alternative hosts of TSV-parthenium and TSV-crownbeard. While both TSV strains had wide natural host ranges, the geographical distribution of each strain was closely associated with the respective distribution of their major alternative hosts. Both TSV strains were commonly found across large areas of central Queensland, but we only found strong evidence for the TSV-parthenium strain being associated with major disease outbreaks in nearby crops. The findings from this study demonstrate that both TSV-parthenium and TSV-crownbeard have similar life cycles but some critical differences. We found both TSV strains to be highly seed transmitted from their respective major alternative hosts from naturally infected mother plants and survived in seed for more than 2 years. We conclusively demonstrated that both TSV strains were readily transmitted via virus-infected pollen taken from the major alternative hosts. This transmission was facilitated by the most commonly collected thrips species, Frankliniella schultzei and Microcephalothrips abdominalis. These results illustrate the importance of seed transmission and efficient thrips vector species for the effective survival of these TSV strains in an often harsh environment and enables the rapid development of TSV disease epidemics in surrounding crops. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was naturally infected by, and an experimental host of TSV-parthenium. However, this infection combination resulted in non-viable crownbeard seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. Based on our field observations we hypothesised that there were differences in relative tolerance to TSV infection between different sunflower hybrids and that seasonal variation in disease levels was related to rainfall in the critical early crop stage. Results from our field trials conducted over multiple years conclusively demonstrated significant differences in tolerance to natural infections of TSV-parthenium in a wide range of sunflower hybrids. Glasshouse tests indicate the resistance to TSV-parthenium identified in the sunflower hybrids is also likely to be effective against TSV-crownbeard. We found a significant negative association between TSV disease incidence in sunflowers and accumulated rainfall in the months of March and April with increasing rainfall resulting in reduced levels of disease. Our results indicate that the use of tolerant sunflower germplasm will be a critical strategy to minimise the risk of TSV epidemics in sunflower.
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Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.
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Vertebrate fauna was studied over 10 years following revegetation of a Eucalyptus tereticornis ecosystem on former agricultural land. We compared four vegetation types: remnant forest, plantings of a mix of native tree species on cleared land, natural regeneration of partially cleared land after livestock removal, and cleared pasture land with scattered paddock trees managed for livestock production. Pasture differed significantly from remnant in both bird and nonbird fauna. Although 10 years of ecosystem restoration is relatively short term in the restoration process, in this time bird assemblages in plantings and natural regeneration had diverged significantly from pasture, but still differed significantly from remnant. After 10 years, 70 and 66% of the total vertebrate species found in remnant had been recorded in plantings and natural regeneration, respectively. Although the fauna assemblages within plantings and natural regeneration were tracking toward those of remnant, significant differences in fauna between plantings and natural regeneration indicated community development along different restoration pathways. Because natural regeneration contained more mature trees (dbh > 30 cm), native shrub species, and coarse woody debris than plantings from the beginning of the study, these features possibly encouraged different fauna to the revegetation areas from the outset. The ability of plantings and natural regeneration to transition to the remnant state will be governed by a number of factors that were significant in the analyses, including shrub cover, herbaceous biomass, tree hollows, time since fire, and landscape condition. Both active and passive restoration produced significant change from the cleared state in the short term.