325 resultados para Weed infestation


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Prickly acacia (Vachellia nilotica subsp. indica), a native multipurpose tree in India, is a weed of National significance, and a target for biological control in Australia. Based on plant genetic and climatic similarities, native range surveys for identifying potential biological control agents for prickly acacia were conducted in India during 2008-2011. In the survey leaf-feeding geometrid, Isturgia disputaria Guenee (syn. Tephrina pulinda), widespread in Tamil Nadu and Karnataka States, was prioritized as a potential biological control agent based on field host range, damage potential and no choice test on non target plant species. Though the field host range study exhibited that V. nilotica ssp. indica and V. nilotica ssp. tomentosa were the primary hosts for successful development of the insect, I. disputaria, replicated no - choice larval feeding and development tests conducted on cut foliage and live plants of nine non-target acacia test plant species in India revealed the larval feeding and development on three of the nine non-target acacia species, V. tortilis, V. planiferons and V. leucophloea in addition to the V. nilotica ssp. indica and V. nilotica ssp. tomentosa. However, the proportion of larvae developing into adults was higher on V. nilotica subsp. indica and V. nilotica subsp. tomentosa, with 90% and 80% of the larvae completing development, respectively. In contrast, the larval mortality was higher on V. tortilis (70%), V. leucophloea (90%) and V. planiferons (70%). The no-choice test results support the earlier host specificity test results of I. disputaria from Pakistan, Kenya and under quarantine in Australia. Contrasting results between field host range and host use pattern under no-choice conditions are discussed.

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Cyperus iria is a weed of rice with widespread occurrence throughout the world. Because of concerns about excessive and injudicious use of herbicides, cultural weed management approaches that are safe and economical are needed. Developing such approaches will require a better understanding of weed biology and ecology, as well as of weed response to increases in crop density and nutrition. Knowledge of the effects of nitrogen (N) fertilizer on crop-weed competitive interactions could also help in the development of integrated weed management strategies. The present study was conducted in a screenhouse to determine the effects of rice planting density (0, 5, 10, and 20 plants pot−1) and N rate (0, 50, 100, and 150 kg ha−1) on the growth of C. iria. Tiller number per plant decreased by 73–88%, leaf number by 85–94%, leaf area by 85–98%, leaf biomass by 92–99%, and inflorescence biomass by 96–99% when weed plants were grown at 20 rice plants pot−1 (i.e., 400 plants m−2) compared with weed plants grown alone. All of these parameters increased when N rates were increased. On average, weed biomass increased by 118–389% and rice biomass by 121–275% with application of 50–150 kg N ha−1, compared to control. Addition of N favored weed biomass production relative to rice biomass. Increased N rates reduced the root-to-shoot weight ratio of C. iria. Rice interference reduced weed growth and biomass and completely suppressed C. iria when no N was applied at high planting densities (i.e., 20 plants pot−1). The weed showed phenotypic plasticity in response to N application, and the addition of N increased the competitive ability of the weed over rice at densities of 5 and 10 rice plants pot−1 compared with 20 plants pot−1. The results of the present study suggest that high rice density (i.e., 400 plants m−2) can help suppress C. iria growth even at high N rates (150 kg ha−1).

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Weather is a general stochastic influence on the life history of weeds. In contrast, anthropogenic disturbance (e.g. land use) is an important deterministic influence on weed demography. Our aim with this study was to investigate the relative contributions of land use and weather on the demography of Lantana camara (lantana), a weed of agricultural and natural habitats, based on the intensive monitoring of lantana populations under three land uses (viz. farm[pasture], and burnt and grazed forests) in subtropical Australia. Lantana populations were growing vigorously across all land uses (asymptotic population growth rate, λ > 3). Examination of historical demography using retrospective perturbation analyses showed that weather was a strong influence on lantana demography with the transition from an El Niño (2008–09) to a La Niña (2009–10) year having a strong positive effect on population growth rate. This effect was most marked at the grazed site, and to a lesser extent at the burnt site, with seedling-to-juvenile and juvenile-to-adult transitions contributing most to these effects. This is likely the result of burning and grazing having eliminated/reduced interspecific competition at these sites. Prospective perturbation analyses revealed that λ was most sensitive to proportionate changes in growth transitions, followed by fecundity and survival transitions. Examination of context-specific patterns in elasticity revealed that growth and fecundity transitions are likely to be the more critical vital rates to reduce λ in wet years at the burnt and grazed forest sites, compared to the farm/pasture site. Management of lantana may need to limit the transition of juveniles into the adult stages, especially in sites where lantana is free from competition (e.g. in the presence of fire or grazing), and this particularly needs to be achieved in wet years. Collectively, these results shed light on aspects of spatial and temporal variation in the demography of lantana, and offer insights on its context-specific management.

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In semi-arid sub-tropical areas, a number of studies concerning no-till (NT) farming systems have demonstrated advantages in economic, environmental and soil quality aspects over conventional tillage (CT). However, adoption of continuous NT has contributed to the build-up of herbicide resistant weed populations, increased incidence of soil- and stubble-borne diseases, and stratification of nutrients and organic carbon near the soil surface. Some farmers often resort to an occasional strategic tillage (ST) to manage these problems of NT systems. However, farmers who practice strict NT systems are concerned that even one-time tillage may undo positive soil condition benefits of NT farming systems. We reviewed the pros and cons of the use of occasional ST in NT farming systems. Impacts of occasional ST on agronomy, soil and environment are site-specific and depend on many interacting soil, climatic and management conditions. Most studies conducted in North America and Europe suggest that introducing occasional ST in continuous NT farming systems could improve productivity and profitability in the short term; however in the long-term, the impact is negligible or may be negative. The short term impacts immediately following occasional ST on soil and environment include reduced protective cover, soil loss by erosion, increased runoff, loss of C and water, and reduced microbial activity with little or no detrimental impact in the long-term. A potential negative effect immediately following ST would be reduced plant available water which may result in unreliability of crop sowing in variable seasons. The occurrence of rainfall between the ST and sowing or immediately after the sowing is necessary to replenish soil water lost from the seed zone. Timing of ST is likely to be critical and must be balanced with optimising soil water prior to seeding. The impact of occasional ST varies with the tillage implement used; for example, inversion tillage using mouldboard tillage results in greater impacts as compared to chisel or disc. Opportunities for future research on occasional ST with the most commonly used implements such as tine and/or disc in Australia’s northern grains-growing region are presented in the context of agronomy, soil and the environment.

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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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We investigate the role of plant species in crops, pasture and native vegetation remnants in supporting agronomic pests and their predators. The study was conducted in three Australian States and across 290 sites sampled monthly for two years. Pastures played a key role in harbouring pest species consistent across States, while native vegetation hosted relatively more predators than other habitat types within each State. Furthermore, native plant species supported the lowest pest density and more predators than pests; in contrast, 75 of the exotic weed species surveyed hosted more pests than predators. Despite the role of pasture in harbouring pests, we found in NSW that pasture also supported the highest proportion of juvenile predators, while native vegetation remnants had the lowest. Our results indicate that non-crop habitat (native remnants or pasture) with few exotic weeds supports high predator and low pest arthropod densities, and that weeds are associated with high pest densities. By linking broad response variables such as ‘all pests’ with specific predictors such as ‘plant species’, our study will inform on-farm management actions of which weeds to control and which natives to plant or regenerate. This study shows the importance of knowing the function of habitats and plants species in supporting pests and predators in agricultural landscapes across multiple regions.

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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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Diseases caused by Tobacco streak virus (TSV) have resulted in significant crop losses in sunflower and mung bean crops in Australia. Two genetically distinct strains from central Queensland, TSV-parthenium and TSV-crownbeard, have been previously described. They share only 81% total-genome nucleotide sequence identity and have distinct major alternative hosts, Parthenium hysterophorus (parthenium) and Verbesina encelioides (crownbeard). We developed and used strain-specific multiplex Polymerase chain reactions (PCRs) for the three RNA segments of TSV-parthenium and TSV-crownbeard to accurately characterise the strains naturally infecting 41 hosts species. Hosts included species from 11 plant families, including 12 species endemic to Australia. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was both a natural host of, and experimentally infected by TSV-parthenium but this infection combination resulted in non-viable seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. TSV-crownbeard was seed transmitted from naturally infected crownbeard at a rate of between 5% and 50% and was closely associated with the geographical distribution of crownbeard in central Queensland. TSV-parthenium and TSV-crownbeard were also seed transmitted in experimentally infected ageratum (Ageratum houstonianum) at rates of up to 40% and 27%, respectively. The related subgroup 1 ilarvirus, Ageratum latent virus, was also seed transmitted at a rate of 18% in ageratum which is its major alternative host. Thrips species Frankliniella schultzei and Microcephalothrips abdominalis were commonly found in flowers of TSV-affected crops and nearby weed hosts. Both species readily transmitted TSV-parthenium and TSV-crownbeard. The results are discussed in terms of how two genetically and biologically distinct TSV strains have similar life cycle strategies in the same environment.

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The ornamental tree 'Cascabela thevetia', from tropical America, has naturalised and formed large infestations at several locations in northern Australia. Some understanding of its ecology and invasiveness was gleaned from a field experiment undertaken in North Queensland. The experiment quantified the growth, time to seed formation and survival of seedlings of the peach biotype growing under light and dense canopy cover within a riparian habitat. Growth, reproduction and survival of young plants varied. Growth was most rapid for seedlings away from, or on the edge of infestations because they were constrained by parent plants. The findings also suggested that land managers have at least 12 months following control to detect new plants, or regrowth, before plants set seed and replenish soil seed banks.

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Diaporthe (syn. Phomopsis) species are well-known saprobes, endophytes or pathogens on a range of plants. Several species have wide host ranges and multiple species may sometimes colonise the same host species. This study describes eight novel Diaporthe species isolated from live and/or dead tissue from the broad acre crops lupin, maize, mungbean, soybean and sunflower, and associated weed species in Queensland and New South Wales, as well as the environmental weed bitou bush (Chrysanthemoides monilifera subsp. rotundata) in eastern Australia. The new taxa are differentiated on the basis of morphology and DNA sequence analyses based on the nuclear ribosomal internal transcribed spacer region, and part of the translation elongation factor-1α and ß-tubulin genes. The possible agricultural significance of live weeds and crop residues ('green bridges') as well as dead weeds and crop residues ('brown bridges') in aiding survival of the newly described Diaporthe species is discussed.