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.

Predictive modelling to aid the regional-scale management of a vertebrate pest

Extensive resources are allocated to managing vertebrate pests, yet spatial understanding of pest threats, and how they respond to management, is limited at the regional scale where much decision-making is undertaken. We provide regional-scale spatial models and management guidance for European rabbits (Oryctolagus cuniculus) in a 260,791 km(2) region in Australia by determining habitat suitability, habitat susceptibility and the effects of the primary rabbit management options (barrier fence, shooting and baiting and warren ripping) or changing predation or disease control levels. A participatory modelling approach was used to develop a Bayesian network which captured the main drivers of suitability and spread, which in turn was linked spatially to develop high resolution risk maps. Policy-makers, rabbit managers and technical experts were responsible for defining the questions the model needed to address, and for subsequently developing and parameterising the model. Habitat suitability was determined by conditions required for warren-building and by above-ground requirements, such as food and harbour, and habitat susceptibility by the distance from current distributions, habitat suitability, and the costs of traversing habitats of different quality. At least one-third of the region had a high probability of being highly suitable (support high rabbit densities), with the model supported by validation. Habitat susceptibility was largely restricted by the current known rabbit distribution. Warren ripping was the most effective control option as warrens were considered essential for rabbit persistence. The anticipated increase in disease resistance was predicted to increase the probability of moderately suitable habitat becoming highly suitable, but not increase the at-risk area. We demonstrate that it is possible to build spatial models to guide regional-level management of vertebrate pests which use the best available knowledge and capture fine spatial-scale processes.

Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia

Wastewater analysis was used to examine prevalence and temporal trends in the use of two cathinones, methylone and mephedrone, in an urban population (>200,000 people) in South East Queensland, Australia. Wastewater samples were collected from the inlet of the sewage treatment plant that serviced the catchment from 2011 to 2013. Liquid chromatography coupled with tandem mass spectrometry was used to measure mephedrone and methylone in wastewater sample using direct injection mode. Mephedrone was not detected in any samples while methylone was detected in 45% of the samples. Daily mass loads of methylone were normalized to the population and used to evaluate methylone use in the catchment. Methylone mass loads peaked in 2012 but there was no clear temporal trend over the monitoring period. The prevalence of methylone use in the catchment was associated with the use of MDMA, the more popular analogue of methylone, as indicated by other complementary sources. Methylone use was stable in the study catchment during the monitoring period whereas mephedrone use has been declining after its peak in 2010. More research is needed on the pharmacokinetics of emerging illicit drugs to improve the applicability of wastewater analysis in monitoring their use in the population.

Controls on trace metals in urban stream sediments : implications for pollution monitoring using sediment chemistry data

Contamination of urban streams is a rising topic worldwide, but the assessment and investigation of stormwater induced contamination is limited by the high amount of water quality data needed to obtain reliable results. In this study, stream bed sediments were studied to determine their contamination degree and their applicability in monitoring aquatic metal contamination in urban areas. The interpretation of sedimentary metal concentrations is, however, not straightforward, since the concentrations commonly show spatial and temporal variations as a response to natural processes. The variations of and controls on metal concentrations were examined at different scales to increase the understanding of the usefulness of sediment metal concentrations in detecting anthropogenic metal contamination patterns. The acid extractable concentrations of Zn, Cu, Pb and Cd were determined from the surface sediments and water of small streams in the Helsinki Metropolitan region, southern Finland. The data consists of two datasets: sediment samples from 53 sites located in the catchment of the Stream Gräsanoja and sediment and water samples from 67 independent catchments scattered around the metropolitan region. Moreover, the sediment samples were analyzed for their physical and chemical composition (e.g. total organic carbon, clay-%, Al, Li, Fe, Mn) and the speciation of metals (in the dataset of the Stream Gräsanoja). The metal concentrations revealed that the stream sediments were moderately contaminated and caused no immediate threat to the biota. However, at some sites the sediments appeared to be polluted with Cu or Zn. The metal concentrations increased with increasing intensity of urbanization, but site specific factors, such as point sources, were responsible for the occurrence of the highest metal concentrations. The sediment analyses revealed, thus a need for more detailed studies on the processes and factors that cause the hot spot metal concentrations. The sediment composition and metal speciation analyses indicated that organic matter is a very strong indirect control on metal concentrations, and it should be accounted for when studying anthropogenic metal contamination patterns. The fine-scale spatial and temporal variations of metal concentrations were low enough to allow meaningful interpretation of substantial metal concentration differences between sites. Furthermore, the metal concentrations in the stream bed sediments were correlated with the urbanization of the catchment better than the total metal concentrations in the water phase. These results suggest that stream sediments show true potential for wider use in detecting the spatial differences in metal contamination of urban streams. Consequently, using the sediment approach regional estimates of the stormwater related metal contamination could be obtained fairly cost-effectively, and the stability and reliability of results would be higher compared to analyses of single water samples. Nevertheless, water samples are essential in analysing the dissolved concentrations of metals, momentary discharges from point sources in particular.

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.

Incorporating the interrelationship between primary and support processes in monitoring and optimising longwall coal mining efficiency

This thesis increased the researchers understanding of the relationship between operations and maintenance in underground longwall coal mines, using data from a Queensland underground coal mine. The thesis explores various relationships between recorded variables. Issues with human recorded data was uncovered, and results emphasised the significance of variables associated with conveyor operation to explain production.

Predictive technology and natural hazards: Risk for Australian planning authorities?

Purpose The object of this paper is to examine whether the improvements in technology that enhance community understanding of the frequency and severity of natural hazards also increased the risk of potential liability of planning authorities in negligence. In Australia, the National Strategy imposes a resilience based approach to disaster management and stresses that responsible land use planning can reduce or prevent the impact of natural hazards upon communities. Design/methodology/approach This paper analyses how the principles of negligence allocate responsibility for loss suffered by a landowner in a hazard prone area between the landowner and local government. Findings The analysis in this paper concludes that despite being able to establish a causal link between the loss suffered by a landowner and the approval of a local authority to build in a hazard prone area, it would be in the rarest of circumstances a negligence action may be proven. Research limitations/implications The focus of this paper is on planning policies and land development, not on the negligent provision of advice or information by the local authority. Practical implications This paper identifies the issues a landowner may face when seeking compensation from a local authority for loss suffered due to the occurrence of a natural hazard known or predicted to be possible in the area. Originality/value The paper establishes that as risk managers, local authorities must place reliance upon scientific modelling and predictive technology when determining planning processes in order to fulfil their responsibilities under the National Strategy and to limit any possible liability in negligence.

Dynamics of Finnish starlings in 1951-2005 : from monitoring to population modelling

Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Time reversal technique for health monitoring of metallic structure using Lamb waves

Time reversal active sensing using Lamb waves is investigated for health monitoring of a metallic structure. Experiments were conducted on an aluminum plate to study the time reversal behavior of A(0) and S-0 Lamb wave modes under narrow band and broad band pulse excitation. Damage in the form of a notch was introduced in the plate to study the changes in the characteristics of the time reversed Lamb wave modes experimentally. Time-frequency analysis of the time reversed signal was carried out to extract the damage information. A measure of damage based on wavelet transform was derived to quantify the hidden damage information in the time reversed signal. It has been shown that time reversal can be used to achieve temporal recompression of Lamb waves under broadband signal excitation. Further, the broad band excitation can also improve the resolution of the technique in detecting closely located defects. This is demonstrated by picking up the reflection of waves from the edge of the plate, from a defect close to the edge of the plate and from defects located near to each other. This study shows the effectiveness of Lamb wave time reversal for temporal recompression of dispersive Lamb waves for damage detection in health monitoring applications. (C) 2009 Elsevier B.V. All rights reserved.