The potential for monitoring and control of insect pests in Southern Hemisphere forestry plantations using semiochemicals

Southern Hemisphere plantation forestry has grown substantially over the past few decades and will play an increasing role in fibre production and carbon sequestration in future. The sustainability of these plantations is, however, increasingly under pressure from introduced pests. This pressure requires an urgent and matching increase in the speed and efficiency at which tools are developed to monitor and control these pests. To consider the potential role of semiochemicals to address the need for more efficient pest control in Southern Hemisphere plantations, particularly by drawing from research in other parts of the world. Semiochemical research in forestry has grown exponentially over the last 40 years but has been almost exclusively focussed on Northern Hemisphere forests. In these forests, semiochemicals have played an important role to enhance the efficiency of integrated pest management programmes. An analysis of semiochemical research from 1970 to 2010 showed a rapid increase over time. It also indicated that pheromones have been the most extensively studied type of semiochemical in forestry, contributing to 92% of the semiochemical literature over this period, compared with research on plant kairomones. This research has led to numerous applications in detection of new invasions, monitoring population levels and spread, in addition to controlling pests by mass trapping or disrupting of aggregation and mating signals. The value of semiochemicals as an environmentally benign and efficient approach to managing forest plantation pests in the Southern Hemisphere seems obvious. There is, however, a lack of research capacity and focus to optimally capture this opportunity. Given the pressure from increasing numbers of pests and reduced opportunities to use pesticides, there is some urgency to develop semiochemical research capacity.

Monitoring wild pig populations: a review of methods

Wild pigs (Sus scrofa) are widespread across many landscapes throughout the world and are considered to be an invasive pest to agriculture and the environment, or conversely a native or desired game species and resource for hunting. Wild pig population monitoring is often required for a variety of management or research objectives, and many methods and analyses for monitoring abundance are available. Here, we describe monitoring methods that have proven or potential applications to wild pig management. We describe the advantages and disadvantages of methods so that potential users can efficiently consider and identify the option(s) best suited to their combination of objectives, circumstances, and resources. This paper offers guidance to wildlife managers, researchers, and stakeholders considering population monitoring of wild pigs and will help ensure that they can fulfill their monitoring objectives while optimizing their use of resources.

A Paddock to reef monitoring and modelling framework for the Great Barrier Reef: Paddock and catchment component

Targets for improvements in water quality entering the Great Barrier Reef (GBR) have been set through the Reef Water Quality Protection Plan (Reef Plan). To measure and report on progress towards the targets set a program has been established that combines monitoring and modelling at paddock through to catchment and reef scales; the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (Paddock to Reef Program). This program aims to provide evidence of links between land management activities, water quality and reef health. Five lines of evidence are used: the effectiveness of management practices to improve water quality; the prevalence of management practice adoption and change in catchment indicators; long-term monitoring of catchment water quality; paddock & catchment modelling to provide a relative assessment of progress towards meeting targets; and finally marine monitoring of GBR water quality and reef ecosystem health. This paper outlines the first four lines of evidence. (C) 2011 Elsevier Ltd. All rights reserved.

Circulating concentrations of leptin, ovarian follicle number, and oocyte lipid content and active mitochondria, in Zebu crossbred cows maintained on standard or improved nutrition

Zebu (Bos indicus) crossbred beef cows (Droughtmaster) were maintained long-term (16 months) on standard nutrition (SN) or improved nutrition (IN). Cows on IN had better body condition and greater (P<0.05) circulating concentrations of leptin than cows on SN (0.7±0.1n/ml and 1.7±0.1n/ml, respectively). There were no outstanding differences between SN and IN cows in basal number of ovarian follicles (≤4mm, 5-8mm, and≥9mm) and there were also no differences in number of oocytes recovered by oocyte pick-up. Cows on IN had a greater (P<0.05) number of total follicles after stimulation with FSH than cows on SN. Oocytes from cows on IN had greater (P<0.05) lipid content than cows on SN (-0.23±0.16 and 0.20±0.18 arbitrary units, respectively) and oocytes of the former cows also tended to have more active mitochondria, although this was not significant. Cows on IN showed a positive relationship (R2=0.31, P<0.05) between plasma leptin and oocyte lipid content. Lipids are utilized by oocytes during high energy consumptive processes including fertilization and early cleavage. The greater lipid content of oocytes from IN cows could therefore confer a reproductive advantage. The present study has shown relationships between nutrition, body condition, circulating leptin, and oocyte lipid content, but a clear cause-and-effect requires further investigation in the cow. © 2013 Elsevier B.V.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Effect of Broadcast Baiting on Abundance Patterns of Red Imported Fire Ants (Hymenoptera: Formicidae) and Key Local Ant Genera at Long-Term Monitoring Sites in Brisbane, Australia

In 2001, the red imported fire ant (Solenopsis invicta Buren) was identified in Brisbane, Australia. An eradication program involving broadcast bait treatment with two insect growth regulators and a metabolic inhibitor began in September of that year and is currently ongoing. To gauge the impacts of these treatments on local ant populations, we examined long-term monitoring data and quantified abundance patterns of S. invicta and common local ant genera using a linear mixed-effects model. For S. invicta, presence in pitfalls reduced over time to zero on every site. Significantly higher numbers of S. invicta workers were collected on high-density polygyne sites, which took longer to disinfest compared with monogyne and low-density polygyne sites. For local ants, nine genus groups of the 10 most common genera analyzed either increased in abundance or showed no significant trend. Five of these genus groups were significantly less abundant at the start of monitoring on high-density polygyne sites compared with monogyne and low-density polygyne sites. The genus Pheidole significantly reduced in abundance over time, suggesting that it was affected by treatment efforts. These results demonstrate that the treatment regime used at the time successfully removed S. invicta from these sites in Brisbane, and that most local ant genera were not seriously impacted by the treatment. These results have important implications for current and future prophylactic treatment efforts, and suggest that native ants remain in treated areas to provide some biological resistance to S. invicta.

Rapid monitoring of nitrogen in mango trees

Nitrogen (N) is an essential nutrient in mango, influencing both productivity and fruit quality. In Australian mango orchards, tree N is traditionally assessed once a year at the dormant pre-flowering stage using laboratory analysis of leaf N. This single assessment is insufficient to determine tree N status at all stages of the annual phenological cycle. Development of a field-based rapid N test would allow more frequent monitoring of tree N status and improved fertiliser management. These experiments examined the accuracy and useability of several devices used in other horticultural crops to rapidly assess mango leaf N in the field; the Konica Minolta 'SPAD-502 chlorophyll meter', Horiba 'Cardy Meter' and the Merck 'RQflex 10.' Regression and correlation analyses were used to determine the relationship between total leaf N and the measurements from the rapid test devices. The relationship between the chlorophyll index measured by the SPAD-502 meter and leaf N was highly significant at late fruit set (R 2=0.72, n=40) and post-harvest (R 2=0.81, n=40) stages and significant at the flowering stage (R 2=0.51, n=40) in the cultivar 'Kensington Pride', indicating the device can be used to rapidly assess mango leaf N in the field. Correlation analysis indicated the relationship between petiole sap measured with the Cardy or Merck devices and leaf N was non-significant.

Evaluating and validating abundance monitoring methods in the absence of populations of known size: review and application to a passive tracking index

Rarely is it possible to obtain absolute numbers in free-ranging populations and although various direct and indirect methods are used to estimate abundance, few are validated against populations of known size. In this paper, we apply grounding, calibration and verification methods, used to validate mathematical models, to methods of estimating relative abundance. To illustrate how this might be done, we consider and evaluate the widely applied passive tracking index (PTI) methodology. Using published data, we examine the rationality of PTI methodology, how conceptually animal activity and abundance are related and how alternative methods are subject to similar biases or produce similar abundance estimates and trends. We then attune the method against populations representing a range of densities likely to be encountered in the field. Finally, we compare PTI trends against a prediction that adjacent populations of the same species will have similar abundance values and trends in activity. We show that while PTI abundance estimates are subject to environmental and behavioural stochasticity peculiar to each species, the PTI method and associated variance estimate showed high probability of detection, high precision of abundance values and, generally, low variability between surveys, and suggest that the PTI method applied using this procedure and for these species provides a sensitive and credible index of abundance. This same or similar validation approach can and should be applied to alternative relative abundance methods in order to demonstrate their credibility and justify their use.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.