Consumption of crops by feral pigs (Sus scrofa) in a fragmented agricultural landscape

Feral pigs (Sus scrofa) consume and damage crops and impact the environment through predation, competition and habitat disturbance, although supporting dietary data are lacking in agricultural landscapes. This study was undertaken to determine the relative importance of food items in the diet of feral pigs in a fragmented agricultural landscape, particularly to assist in predicting the breadth of likely impacts. Diet composition was assessed from the stomach contents of 196 feral pigs from agricultural properties in southern Queensland. Feral pigs were herbivorous, with plant matter comprising >99% of biomass consumed. Crops were consumed more frequently than non-crop species, and comprised >60% of dietary biomass, indicating a clear potential for direct economic losses. Consumption of pasture and forage species also suggests potential competition for pasture with domestic stock. There is little evidence of direct predation on native fauna, but feral pig feeding activities may impact environmental values. Seasonal differences in consumption of crop, pasture or animal food groups probably reflect the changing availability of food items. We recommend that future dietary studies examine food availability to determine any dietary preferences to assist in determining the foods most susceptible to damage. The outcomes of this study are important for developing techniques for monitoring the impacts of feral pigs, essential for developing management options to reduce feral pig damage on agricultural lands.

Effect of added nitrogen on plant litter decomposition depends on initial soil carbon and nitrogen stoichiometry

Increasing organic carbon inputs to agricultural soils through the use of pastures or crop residues has been suggested as a means of restoring soil organic carbon lost via anthropogenic activities, such as land use change. However, the decomposition and retention of different plant residues in soil, and how these processes are affected by soil properties and nitrogen fertiliser application, is not fully understood. We evaluated the rate and extent of decomposition of 13C-pulse labelled plant material in response to nitrogen addition in four pasture soils of varying physico-chemical characteristics. Microbial respiration of buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) residues was monitored over 365-days. A double exponential model fitted to the data suggested that microbial respiration occurred as an early rapid and a late slow stage. A weighted three-compartment mixing model estimated the decomposition of both soluble and insoluble plant 13C (mg C kg−1 soil). Total plant material decomposition followed the alkyl C: O-alkyl C ratio of plant material, as determined by solid-state 13C nuclear magnetic resonance spectroscopy. Urea-N addition increased the decomposition of insoluble plant 13C in some soils (≤0.1% total nitrogen) but not others (0.3% total nitrogen). Principal components regression analysis indicated that 26% of the variability of plant material decomposition was explained by soil physico-chemical characteristics (P = 0.001), which was primarily described by the C:N ratio. We conclude that plant species with increasing alkyl C: O-alkyl C ratio are better retained as soil organic matter, and that the C:N stoichiometry of soils determines whether N addition leads to increases in soil organic carbon stocks.

Exotic plant pests–a threat to the sustainability of Australia’s grains industry

Exotic plant pests (EPPs) threaten production, market access and sustainability of Australian plant production systems. For the grains industry there are over 600 identified EPPs of which 54 are considered high priority, posing a significant threat. Despite Australia’s geographical isolation and strong quarantine systems, the threat from EPPs has never been higher with the increasing levels of travel and trade, emphasising the need for improving our efforts in prevention, preparedness and surveillance for EPPs.

Halosulfuron-methyl: A selective herbicide option for the control of the invasive 'Cyperus aromaticus' (Ridley) Mattf. and Kukenth (Navua sedge)

There are currently limited options for the control of the invasive tropical perennial sedge 'Cyperus aromaticus' (Ridley) Mattf. and Kukenth (Navua sedge). The potential for halosulfuron-methyl as a selective herbicide for Navua sedge control in tropical pastures was investigated by undertaking successive field and shade house experiments in North Queensland, Australia. Halosulfuron-methyl and adjuvant rates, and combinations with other herbicides, were examined to identify a herbicide regime that most effectively reduced Navua sedge. Our research indicated that combining halosulfuron- methyl with other herbicides did not improve efficacy for Navua sedge control. We also identified that low rates of halosulfuron-methyl (25 g ha-1 a.i.) were just as effective as higher rates (73 g ha-1 a.i.) at controlling the sedge, and that this control relied on the addition of the adjuvant Bonza at the recommended concentration (1% of the spray volume). Pot trials in the controlled environment of the shade house achieved total mortality under these regimes. Field trials demonstrated more variable results with reductions in Navua sedge ranging between 40-95% at 8-10 weeks after treatment. After this period (16-24 weeks after treatment), regrowth of sedge, either from newly germinated seed, or of small plants protected from initial treatment, indicated sedge populations can rapidly increase to levels similar to pre-application, depending on the location and climatic conditions. Such variable results highlight the need for concerted monitoring of pastures to identify optimal treatment times. Ideally, initial treatment should be done when the sedge is healthy and actively growing, with follow up-treatments applied when new seed heads are produced from regrowth.

Fine-tuning of unmanned aerial surveillance for ecological systems

Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.

Constrained linear minimax filter for systems with large plant uncertainties

This paper presents a method of designing a minimax filter in the presence of large plant uncertainties and constraints on the mean squared values of the estimates. The minimax filtering problem is reformulated in the framework of a deterministic optimal control problem and the method of solution employed, invokes the matrix Minimum Principle. The constrained linear filter and its relation to singular control problems has been illustrated. For the class of problems considered here it is shown that the filter can he constrained separately after carrying out the mini maximization. Numorieal examples are presented to illustrate the results.

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.

Responses of fruit flies (Tephritidae: Dacinae) to novel male attractants in north Queensland, Australia, and improved lures for some pest species

Male fruit fly attractants, cue-lure and methyl eugenol (ME), have been successfully used for the last 50 years in the monitoring and control of Dacini fruit flies (Bactrocera and Dacus species). However, over 50% of Dacini are non-responsive to either lure, including some pest species. A new lure, zingerone, has been found to weakly attract cue- and ME-responsive species in Malaysia. In Australia it attracted a weakly cue-responsive minor pest Bactrocera jarvisi (Tryon) and three non-responsive' species. Similar compounds were tested in Queensland and attracted cue- and ME-responsive species and two non-responsive' species. In this study, 14 novel compounds, including raspberry ketone formate (RKF) (Melolure) and zingerone, were field tested in comparison with cue-lure and ME at 17 sites in north Queensland. The most attractive novel lures were isoeugenol, methyl-isoeugenol, dihydroeugenol and zingerone. Several non-responsive' species responded to the new lures: Bactrocera halfordiae (Tryon), a species of some market access concern, was most attracted to isoeugenol; B.barringtoniae (Tryon), B.bidentata (May) and B.murrayi (Perkins) responded to isoeugenol, methyl-isoeugenol and dihydroeugenol; two new species of Dacus responded to zingerone. Bactrocera kraussi (Hardy), a cue-responsive minor pest in north Queensland, was significantly more attracted to isoeugenol than cue-lure. The cue-responsive D.absonifacies (May) and D.secamoneaeDrew were significantly more attracted to zingerone than cue-lure. Bactrocera yorkensisDrew & Hancock, a ME-responsive species was significantly more attracted to isoeugenol, methyl-isoeugenol and dihydroeugenol than ME. The preferential response to RKF or cue-lure was species specific. Six species were significantly more attracted to RKF, including the pests B.tryoni (Froggatt), B.frauenfeldi (Schiner) and minor pest B.bryoniae (Tryon); eight species were significantly more attracted to cue-lure including the pest B.neohumeralis (Hardy). These findings have significance in the search for optimal male lures for pest species elsewhere in the world.

Precise determination of aquatic plant wet mass using a salad spinner

The reliable assessment of macrophyte biomass is fundamental for ecological research and management of freshwater ecosystems. While dry mass is routinely used to determine aquatic plant biomass, wet (fresh) mass can be more practical. We tested the accuracy and precision of wet mass measurements by using a salad spinner to remove surface water from four macrophyte species differing in growth form and architectural complexity. The salad spinner aided in making precise and accurate wet mass with less than 3% error. There was also little difference between operators, with a user bias estimated to be below 5%. To achieve this level of precision, only 10–20 turns of the salad spinner are needed. Therefore, wet mass of a sample can be determined in less than 1 min. We demonstrated that a salad spinner is a rapid and economical technique to enable precise and accurate macrophyte wet mass measurements and is particularly suitable for experimental work. The method will also be useful for fieldwork in situations when sample sizes are not overly large.

Management of mango decline using thiophanate methyl and plant activators through a macro infusion system

Mango decline disease has become a major cause of tree losses of about 7-10% in all mango growing areas of Pakistan. This study evaluated the effectiveness of plant activators used in conjunction with the fungicide thiophanate methyl in managing mango decline disease. The study was conducted in the Multan district using trees rated as 1-2 on a decline severity scale and displaying symptoms of gummosis, bark splitting, canker formation, and leaf drooping. Experimental treatments included three plant activators viz. Bion, Planofix, and Root king in conjunction with or without thiophanate methyl, delivered through a macro infusion system. This was the first time a macro infusion system had been used in Pakistan. The injection system delivered the fungicide/activator mixture into the tree trunk under pressure through a series of holes bored into the xylem tissue. Tree disease symptoms were recorded fortnightly to assess the treatment efficacy. After three months, thiophanate methyl, in combination with Bion, was found to be the most effective treatment with trees displaying no apparent disease symptoms. When thiophanate methyl was used alone, or in combination with Root king and Planofix, the symptoms of bark splitting and gummosis persisted.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Symposium: Food pricing and affordability of ‘healthy’ versus ‘less healthy’ diets: An international approach to monitoring and surveillance

Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.