Refining the process of agent selection through understanding plant demography and plant response to herbivory

Understanding plant demography and plant response to herbivory is critical to the selection of effective weed biological control agents. We adopt the metaphor of 'filters' to suggest how agent prioritisation may be improved to narrow our choices down to those likely to be most effective in achieving the desired weed management outcome. Models can serve to capture our level of knowledge (or ignorance) about our study system and we illustrate how one type of modelling approach (matrix models) may be useful in identifying the weak link in a plant life cycle by using a hypothetical and an actual weed example (Parkinsonia aculeata). Once the vulnerable stage has been identified we propose that studying plant response to herbivory (simulated and/or actual) can help identify the guilds of herbivores to which a plant is most likely to succumb. Taking only potentially effective agents through the filter of host specificity may improve the chances of releasing safe and effective agents. The methods we outline may not always lead us definitively to the successful agent(s), but such an empirical, data-driven approach will make the basis for agent selection explicit and serve as testable hypotheses once agents are released.

Refining Integrated Pest Management (IPM) of eggfruit caterpillar

Investigations into pheromone monitoring and efficacy of insecticides to improve Integrated Pest Management (IPM) of eggfruit caterpillar.

Refining low-volume, high-concentration herbicide applications to control Chromolaena odorata (L.) King & Robinson (Siam weed) in remote areas

Chromolaena odorata (L.) King and Robinson (Siam weed) is a highly invasive plant and a high priority for control in north Queensland. It can be effectively treated using high-volume, groundbased herbicide spray equipment, but operational information shows that this control method becomes increasingly difficult in areas where vehicle access is prevented by rougher terrain. Low-volume, high-concentration herbicide applications have proven capable of causing high mortality in these remote situations. Two trials were undertaken between May 2010 and May 2012 to refine effective rates of aminopyralid/fluroxypyr, fluroxypyr and metsulfuron-methyl, only using low-volume, high-concentration applications on Siam weed. Fluroxypyr on its own was as effective as aminopyralid/fluroxypyr as both herbicides caused 95-100% mortality at overlapping rates containing 5 to 18.85 g a.i. L-1 of fluroxypyr. Metsulfuron-methyl caused 100% mortality when applied at 3 and 6 g a.i. L-1. Effective control was achieved with approximately 16 to 22 mL of the solutions per plant, so a 5 L mixture in a backpack could treat 170 to 310 adult plants. There are several options for treating Siam weed on the ground and the choice of methods reflects the area, plant density and accessibility of the infestation. Control information from Siam weed field crews shows that low volume, high concentration herbicide applications applied using a splatter gun are a more efficient method for controlling larger, denser remote infestations than physical removal. By identifying effective herbicides that are applied through low-volume equipment, these trials provide an additional and more efficient tool for controlling Siam weed in remote areas.

Progress towards the eradication of three melastome shrub species from northern Australian rainforests

To eradicate a weed incursion, its extent must be delimited and each infestation extirpated. Measures for delimitation and extirpation are utilized to assess the progress of eradication programs currently targeting three melastome shrub species (Clidemia hirta, Miconia nervosa and M. racemosa) in north-eastern Australia. The main infested area for each species was determined during the year after initial detection, but expanded surveys have led to the discovery of isolated, smaller outlying patches. Programs are refining survey methods (including search frequency) to prevent reproduction. Weed incursions that are limited to single infestations represent a prime opportunity for eradication. However, population and dispersal data indicate that eradication will require an ongoing investment for some time for all three species. Highly persistent seed and dispersal by frugivores suggest that eradication may prove extraordinarily difficult should any of these species spread or be discovered at more locations.

Membrane fractionation technologies for high quality mill sugar and value-added by products - an integrated sugar production process concept model.

Membrane filtration technology has been proven to be a technically sound process to improve the quality of clarified cane juice and subsequently to increase the productivity of crystallisation and the quality of sugar production. However, commercial applications have been hindered because the benefits to crystallisation and sugar quality have not outweighed the increased processing costs associated with membrane applications. An 'Integrated Sugar Production Process (ISPP) Concept Model' is proposed to recover more value from the non-sucrose streams generated by membrane processing. Pilot scale membrane fractionation trials confirmed the technical feasibility of separating high-molecular weight, antioxidant and reducing sugar fractions from cane juice in forms suitable for value recovery. It was also found that up to 40% of potassium salts from the juice can be removed by membrane application while removing the similar amount of water with potential energy saving in subsequent evaporation. Application of ISPP would allow sugar industry to co-produce multiple products and high quality mill sugar while eliminating energy intensive refining processes.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

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.

Projecting future expansion of invasive species: Comparing and improving methodologies for species distribution modeling

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.