Optimizing Western Flower Thrips Management on French Beans by Combined Use of Beneficials and Imidacloprid

Western flower thrips (WFT), Frankliniella occidentalis (Pergande), is an important pest of vegetable crops worldwide and has developed resistance to many insecticides. The predatory mites Neoseiulus (=Amblyseius) cucumeris (Oudemans), the entomopathogenic fungus Metarhizium anisopliae (Metsch.), and an insecticide (imidacloprid) were tested for their efficacy to reduce WFT population density and damage to French bean (Phaseolus vulgaris L.) pods under field conditions in two planting periods. Metarhizium anisopliae was applied as a foliar spray weekly at a rate of one litre spray volume per plot while imidacloprid was applied as a soil drench every two weeks at a rate of two litres of a mixture of water and imidacloprid per m(2). Neoseiulus cucumeris was released every two weeks on plant foliage at a rate of three mites per plant. Single and combined treatment applications reduced WFT population density by at least three times and WFT damage to French bean pods by at least 1.7 times compared with untreated plots. The benefit-cost ratios in management of WFT were profitable with highest returns realized on imidacloprid treated plots. The results indicate that M. anisopliae, N. cucumeris, and imidacloprid have the potential for use in developing an integrated pest management program against WFT on French beans.

Assessment of a Planned Municipal Solid Waste Management System in Sri Lanka

Systematic Municipal Solid Waste Management (MSWM) authorities of Sri Lanka contributes to exchange some productive outputs with localities; however it is still not in a successful mode due to limitations and environmental failures in their operation. Most of these local administrations are directly dumping Municipal Solid Waste (MSW) to an open dumping site, this manner of inappropriate disposal of MSW is become a major threat to the environment and public health in developing countries like Sri Lanka. This study was conducted for the MSWM practices of Balangoda Urban Council. The research was performed based on analyzing information obtained from field observations; reports; literature; questionnaire distribution among community; and a series of formal interviews with major stakeholders. The ongoing MSWM practices of Balangoda Urban Council encompass six categories as waste minimization and handling; waste collection; on-site separation; waste transportation; further management including grading, composting, recycling, producing sludge fertilizer; and final disposal to an open dump site. Apart from those, training sessions on MSWM are also being conducted. The purpose of this paper is to assess current status of urban waste management scenario and highlight strengths and weaknesses to understand the sustainability of the system which would help any local authority to improve MSWM.

Barriers and drivers of new public-private infrastructure: sewer mining

The rate of water reform in Australia is gathering pace with Federal and State initiatives promoting a more integrated approach to water management. This approach encompasses a more competitive environment and a greater role for the private sector. There is a growing recognition of the importance of water recycling in these initiatives and the need to provide opportunities for its development. In March 2008 the Productivity Commission published its discussion paper on urban water reform (Productivity Commission, 2008). The paper cited inadequate institutional arrangements for the management of Australian urban water resources and noted the benefits to be gained from a comprehensive public review of urban water management. This development can be supported through the promotion of a sewer mining industry. This industry, offers flexible and innovative solutions to water recycling demands in a variety of situations and structures. In addition it has the capability of satisfying government competition and private sector policy initiatives.

Eco-retrofitting - from managerialism to design

As all environmental problems are caused by human systems of design, sustainability can be seen as a design problem. Given the massive energy and material flows through the built environment, sustainability simply cannot be achieved without the re-design of our urban areas. ‘Eco-retrofitting’, as used here, means modifying buildings and/or urban areas to create net positive social and environmental impacts – both on site and off site. While this has probably not been achieved anywhere as yet, myriad but untapped eco-solutions are already available which could be up-scaled to the urban level. It is now well established that eco-retrofitting buildings and cities with appropriate design technology can pay for itself through lower health costs, productivity increases and resource savings. Good design would also mean happier human and ecological communities at a much lower cost over time. In fact, good design could increase life quality and the life support services of nature while creating sustainable‘economic’growth. The impediments are largely institutional and intellectual, which can be encapsulated in the term ‘managerial’. There are, however, also systems design solutions to the managerial obstacles that seem to be stalling the transition to sustainable systems designs. Given the sustainability imperative, then, why is the adoption of better management systems so slow? The oral presentation will show examples of ways in which built environment design can create environments that not only reduce the ongoing damage of past design, but could theoretically generate net positive social and ecological outcomes over their life cycle. These illustrations show that eco-retrofitting could cost society less than doing nothing - especially given the ongoing renovations of buildings - but for managerial hurdles. The paper outlines on how traditional managerial approaches stand in the way of ‘design for ecosystem services’, and list some management solutions that have long been identified, but are not yet widely adopted. Given the pervasive nature of these impediments and their alternatives, they are presented by way of examples. A sampling of eco-retrofitting solutions are also listed to show that ecoretrofitting is a win-win-win solution that stands ready to be implemented by people having management skills and/or positions of influence.

Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

The influence of habitat heterogeneity on patterns of connectivity among rabbit populations in southern Queensland

Patterns of connectivity among local populations influence the dynamics of regional systems, but most ecological models have concentrated on explaining the effect of connectivity on local population structure using dynamic processes covering short spatial and temporal scales. In this study, a model was developed in an extended spatial system to examine the hypothesis that long term connectivity levels among local populations are influenced by the spatial distribution of resources and other habitat factors. The habitat heterogeneity model was applied to local wild rabbit populations in the semi-arid Mitchell region of southern central Queensland (the Eastern system). Species' specific population parameters which were appropriate for the rabbit in this region were used. The model predicted a wide range of long term connectivity levels among sites, ranging from the extreme isolation of some sites to relatively high interaction probabilities for others. The validity of model assumptions was assessed by regressing model output against independent population genetic data, and explained over 80% of the variation in the highly structured genetic data set. Furthermore, the model was robust, explaining a significant proportion of the variation in the genetic data over a wide range of parameters. The performance of the habitat heterogeneity model was further assessed by simulating the widely reported recent range expansion of the wild rabbit into the Mitchell region from the adjacent, panmictic Western rabbit population system. The model explained well the independently determined genetic characteristics of the Eastern system at different hierarchic levels, from site specific differences (for example, fixation of a single allele in the population at one site), to differences between population systems (absence of an allele in the Eastern system which is present in all Western system sites). The model therefore explained the past and long term processes which have led to the formation and maintenance of the highly structured Eastern rabbit population system. Most animals exhibit sex biased dispersal which may influence long term connectivity levels among local populations, and thus the dynamics of regional systems. When appropriate sex specific dispersal characteristics were used, the habitat heterogeneity model predicted substantially different interaction patterns between female-only and combined male and female dispersal scenarios. In the latter case, model output was validated using data from a bi-parentally inherited genetic marker. Again, the model explained over 80% of the variation in the genetic data. The fact that such a large proportion of variability is explained in two genetic data sets provides very good evidence that habitat heterogeneity influences long term connectivity levels among local rabbit populations in the Mitchell region for both males and females. The habitat heterogeneity model thus provides a powerful approach for understanding the large scale processes that shape regional population systems in general. Therefore the model has the potential to be useful as a tool to aid in the management of those systems, whether it be for pest management or conservation purposes.

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Host use and crop impacts of Oribius Marshall species (Coleoptera: Curculionidae) in Eastern Highlands Province, Papua New Guinea

Oribius species are small flightless weevils endemic to the island of New Guinea and far northern Cape York, Australia. The adults feed externally on leaves, developing fruit and green bark, but their impact as pests and general host use patterns are poorly known. Working in Eastern Highlands Province, Papua New Guinea, we carried out structured host use surveys, farmer surveys, shade-house growth trials, and on-farm and on-station impact trials to: (i) estimate the host range of the local Oribius species; (ii) understand adult daily activity patterns; (iii) elucidate feeding habits of the soil dwelling larvae; and (iv) quantify the impacts of adult feeding damage. Oribius inimicus and O. destructor accounted for nearly all the Oribius species encountered locally: of these two O. inimicus was the most abundant. Weevils were collected from 31 of 33 plants surveyed in the Aiyura Valley and a combination of farmer interviews and literature records provided evidence for the beetles being pestiferous on 43 crops currently or previously grown in the Highlands. Adult weevils had a distinct diurnal pattern of being in the upper plant canopy early in the morning and, to a lesser extent, again late in the afternoon. For the remainder of the day beetles resided within the canopy, or possibly off the plant. Movement of adults between plants appeared frequent. Pot trials confirmed the larvae are root feeders. Quantified impact studies showed that the weevils are damaging to a range of vegetable and orchard crops (broccoli, capsicum, celery, French bean, Irish potato, lettuce, orange and strawberry), causing average yield losses of around 30-40%, but up to 100% on citrus. Oribius weevils pose a significant and apparently growing problem for Highland’s agriculture.

Geostatistical analysis of adult Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) in wheat stored at constant temperatures

Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of insect pests. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 dimensions showed that, in both the horizontal and vertical directions and at all temperatures examined, insect numbers were positively correlated over short (0-5cm) distances, and negatively correlated over longer (≥10cm) distances. Analysis in 3 dimensions showed a similar pattern, with positive correlations over short distances and negative correlations at longer distances. At 35°C, insects were located significantly further from the grain surface than at 25 and 30°C. Dispersion metrics showed statistically significant aggregation in all cases. This is the first research using small sample units, high sampling intensities, and a range of temperatures, to show spatial structuring of R. dominica populations over short distances. This research will have significant implications for sampling in the stored grains industry.

Population structure of Bactrocera dorsalis s.s., B. papayae and B. philippinensis (Diptera: Tephritidae) in southeast Asia: evidence for a single species hypothesis using mitochondrial DNA and wingshape data

Background Bactrocera dorsalis s.s. is a pestiferous tephritid fruit fly distributed from Pakistan to the Pacific, with the Thai/Malay peninsula its southern limit. Sister pest taxa, B. papayae and B. philippinensis, occur in the southeast Asian archipelago and the Philippines, respectively. The relationship among these species is unclear due to their high molecular and morphological similarity. This study analysed population structure of these three species within a southeast Asian biogeographical context to assess potential dispersal patterns and the validity of their current taxonomic status. Results Geometric morphometric results generated from 15 landmarks for wings of 169 flies revealed significant differences in wing shape between almost all sites following canonical variate analysis. For the combined data set there was a greater isolation-by-distance (IBD) effect under a ‘non-Euclidean’ scenario which used geographical distances within a biogeographical ‘Sundaland context’ (r2 = 0.772, P < 0.0001) as compared to a ‘Euclidean’ scenario for which direct geographic distances between sample sites was used (r2 = 0.217, P < 0.01). COI sequence data were obtained for 156 individuals and yielded 83 unique haplotypes with no correlation to current taxonomic designations via a minimum spanning network. BEAST analysis provided a root age and location of 540kya in northern Thailand, with migration of B. dorsalis s.l. into Malaysia 470kya and Sumatra 270kya. Two migration events into the Philippines are inferred. Sequence data revealed a weak but significant IBD effect under the ‘non-Euclidean’ scenario (r2 = 0.110, P < 0.05), with no historical migration evident between Taiwan and the Philippines. Results are consistent with those expected at the intra-specific level. Conclusions Bactrocera dorsalis s.s., B. papayae and B. philippinensis likely represent one species structured around the South China Sea, having migrated from northern Thailand into the southeast Asian archipelago and across into the Philippines. No migration is apparent between the Philippines and Taiwan. This information has implications for quarantine, trade and pest management.

A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

Uncertainty analysis of pollutant build-up modelling based on a Bayesian Weighted Least Squares approach

Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

The influence of temperature and introduction point on the detection of Rhyzopertha dominica in stored grain

The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

Hydrolysis of triasulfuron, metsulfuron-methyl and chlorsulfuron in alkaline soil and aqueous solutions

The hydrolysis of triasulfuron, metsulfuron-methyl and chlorsulfuron in aqueous buffer solutions and in soil suspensions at pH values ranging from 5.2 to 11.2 was investigated. Hydrolysis of all three compounds in both aqueous buffer and soil suspensions was highly pH-sensitive. The rate of hydrolysis was much faster in the acidic pH range (5.2-6.2) than under neutral and moderately alkaline conditions (8.2-9.4), but it increased rapidly as the pH exceeded 10.2. All three compounds degraded faster at pH 5.2 than at pH 11.2. Hydrolysis rates of all three compounds could be described well with pseudo-first-order kinetics. There were no significant differences (P =0.05) in the rate constants (k, day-1) of the three compounds in soil suspensions from those in buffer solutions within the pH ranges studied. A functional relationship based on the propensity of nonionic and anionic species of the herbicides to hydrolyse was used to describe the dependence of the 'rate constant' on pH. The hydrolysis involving attack by neutral water was at least 100-fold faster when the sulfonylurea herbicides were undissociated (acidic conditions) than when they were present as the anion at near neutral pH. In aqueous buffer solution at pH > 11, a prominent degradation pathway involved O-demethylation of metsulfuron-methyl to yield a highly polar degradate, and hydrolytic opening of the triazine ring. It is concluded that these herbicides are not likely to degrade substantially through hydrolysis in most agricultural (C) 2000 Society of Chemical Industry.