Probabilistic forecasts of the onset of the north Australian wet season

The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

Atmospheric visibility and PM10 as indicators of new particle formation in an urban environment

It is well-known that new particle formation (NPF) in the atmosphere is inhibited by pre-existing particles in the air that act as condensation sinks to decrease the concentration and, thus, the supersaturation of precursor gases. In this study, we investigate the effects of two parameters - atmospheric visibility, expressed as the particle back-scatter coefficient (BSP), and PM10 particulate mass concentration, on the occurrences of NPF events in an urban environment where the majority of precursor gases originate from motor vehicle and industrial sources. This is the first attempt to derive direct relationships between each of these two parameters and the occurrence of NPF. NPF events were identified from data obtained with a neutral cluster and air ion spectrometer over 245 days within a calendar year. Bayesian logistic regression was used to determine the probability of observing NPF as functions of BSP and PM10. We show that the BSP at 08 h on a given day is a reliable indicator of an NPF event later that day. The posterior median probability of observing an NPF event was greater than 0.5 (95%) when the BSP at 08 h was less than 6.8 Mm-1.

Self-rating scales in the assessment of current and childhood symptoms of attention deficit hyperactivity disorder in adults

Objective: Attention deficit hyperactivity disorder (ADHD) is a life-long condition, but because of its historical status as a self-remitting disorder of childhood, empirically validated and reliable methods for the assessment of adults are scarce. In this study, the validity and reliability of the Wender Utah Rating Scale (WURS) and the Adult Problem Questionnaire (APQ), which survey childhood and current symptoms of ADHD, respectively, were studied in a Finnish sample. Methods: The self-rating scales were administered to adults with an ADHD diagnosis (n = 38), healthy control participants (n = 41), and adults diagnosed with dyslexia (n = 37). Items of the self-rating scales were subjected to factor analyses, after which the reliability and discriminatory power of the subscales, derived from the factors, were examined. The effects of group and gender on the subscales of both rating scales were studied. Additionally, the effect of age on the subscales of the WURS was investigated. Finally, the diagnostic accuracy of the total scores was studied. Results: On the basis of the factor analyses, a four-factor structure for the WURS and five-factor structure for the APQ had the best fit to the data. All of the subscales of the APQ and three of the WURS achieved sufficient reliability. The ADHD group had the highest scores on all of the subscales of the APQ, whereas two of the subscales of the WURS did not statistically differ between the ADHD and the Dyslexia group. None of the subscales of the WURS or the APQ was associated with the participant's gender. However, one subscale of the WURS describing dysthymia was positively correlated with the participant's age. With the WURS, the probability of a correct positive classification was .59 in the current sample and .21 when the relatively low prevalence of adult ADHD was taken into account. The probabilities of correct positive classifications with the APQ were .71 and .23, respectively. Conclusions: The WURS and the APQ can provide accurate and reliable information of childhood and adult ADHD symptoms, given some important constraints. Classifications made on the basis of the total scores are reliable predictors of ADHD diagnosis only in populations with a high proportion of ADHD and a low proportion of other similar disorders. The subscale scores can provide detailed information of an individual's symptoms if the characteristics and limitations of each domain are taken into account. Improvements are suggested for two subscales of the WURS.

Analysis of randomly time varying systems by gaussian closure technique

The Gaussian probability closure technique is applied to study the random response of multidegree of freedom stochastically time varying systems under non-Gaussian excitations. Under the assumption that the response, the coefficient and the excitation processes are jointly Gaussian, deterministic equations are derived for the first two response moments. It is further shown that this technique leads to the best Gaussian estimate in a minimum mean square error sense. An example problem is solved which demonstrates the capability of this technique for handling non-linearity, stochastic system parameters and amplitude limited responses in a unified manner. Numerical results obtained through the Gaussian closure technique compare well with the exact solutions.

Agonosoma trilineatum (Heteroptera: Scutelleridae) a biological control agent of the weed bellyache bush, Jatropha gossypiifolia (Euphorbiaceae)

Bellyache bush, Jatropha gossypiifolia L., is a serious weed of northern Australia. Agonosoma trilineatum (F.) is an insect from tropical America released in Australia in 2003 as a biological control agent against bellyache bush. It feeds on seeds and has the potential to reduce seed production, thereby potentially reducing the rate of spread and recruitment. To test the host specificity of A. trilineatum, four biological responses to host plant species were determined: development of nymphs, oviposition preferences, adult feeding and frequency of mating. Development of nymphs to adults and adult feeding only occurred on three Jatropha spp. These species also supported mating and oogenesis but only J. gossypiifolia was accepted for oviposition. Mating did not occur in the presence of other plant species. The evidence indicates that there is little risk associated with the release of this insect species in Australia and probably other countries where this weed is a problem. The probability of this insect expanding its host range is low because multiple aspects of the biology would need to change simultaneously. A. trilineatum was released in Australia between 2003 and 2007. A Climex model indicated that coastal areas of Queensland and the Northern Territory would be climatically most suitable for this insect.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

Defining and predicting the 'break of the season' for north-east Queensland grazing areas

For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

The relationship between the determinants of rental housing satisfaction and considering moving in Finland

Purpose The purpose of this paper is to discuss the relation between dissatisfaction with housing conditions and considering moving among residents of Finnish rental multifamily buildings. The paper examines physical attributes, socioeconomic factors, and subjective opinions related to housing conditions and satisfaction with housing. Design/methodology/approach Logistic regression analysis is used to examine survey data to analyse which factors contribute to dissatisfaction with the housing unit and the apartment building and whether dissatisfaction is related to consideration of moving. Findings The findings indicate that dissatisfaction with the building and individual housing unit are associated with greater probability of considering moving. Satisfaction with kitchen, living room, storage, and building age are the most important indicators of satisfaction with the housing unit, and satisfaction with living room, bathroom, storage, and building age are associated with satisfaction with the apartment building. These are the areas in which landlords could invest in renovations to increase satisfaction in an attempt to reduce turnover. Research limitations/implications The study is conducted with Finnish data only. The sample is not a representative sample of the Finnish population. A longitudinal study would be needed to determine whether dissatisfied residents indending to move actually change residence. Originality/value This study is the first of its kind in the Finnish housing market. It tests a general model that has been suggested to be customized to local conditions. In addition, much of the research on this topic is more than 20 years old. Examination of the model under current housing and socioeconomic conditions is necessary to determine if relationships have changed over time.

Cassowary dispersal of the invasive pond apple in a tropical rainforest: the contribution of subordinate dispersal modes in invasion.

Dispersal is a significant determinant of the pattern and process of invasions; however, weed dispersal distances are rarely described and descriptions of dispersal kernels are completely lacking for vertebrate-dispersed weeds. Here, we describe dispersal kernels generated by a native disperser, the endangered southern cassowary (Casuarius casuarius, L.) for an invasive, tropical rainforest plant, pond apple (Annona glabra, L.). Pond apple is primarily water-dispersed and is managed as such. We consider whether cassowary dispersal, as a numerically subordinate dispersal mode, provides an additional dispersal service that may modify the invasion process. In infested areas, pond apple seed was common in cassowary dung. Gut passage had no effect on the probability of single seed germination but deposition in clumps or as whole fruits reduced the probability of germination below that of single seeds. Gut passage times ranged from 65 to 1675 min. Combined with cassowary movement data, this resulted in estimated dispersal distances of 12.5-5212 m, with a median distance of 387 m (quartile range 112-787 m). Native frugivores can be effective dispersers of weeds in rainforest and even terrestrial dispersers can provide long-distance dispersal. Importantly, though pond apple might be expected to be almost entirely dispersed downstream and along the margins of aquatic and marine habitats, cassowaries provide dispersal upstream and between drainages, leading to novel dispersal outcomes. Even through the provision of small quantities of novel dispersal outcomes, subordinate dispersal modes can play a significant role in determining invasion pattern and influence the ultimate success of control programs by providing dispersal to locations unattainable via the primary mode.

Learning Optimal Discriminant Functions through a Cooperative Game of Automata

The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

Management of plant invasions mediated by frugivore interactions

1. Some of the most damaging invasive plants are dispersed by frugivores and this is an area of emerging importance in weed management. It highlights the need for practical information on how frugivores affect weed population dynamics and spread, how frugivore populations are affected by weeds and what management recommendations are available. 2. Fruit traits influence frugivore choice. Fruit size, the presence of an inedible peel, defensive chemistry, crop size and phenology may all be useful traits for consideration in screening and eradication programmes. By considering the effect of these traits on the probability, quality and quantity of seed dispersal, it may be possible to rank invasive species by their desirability to frugivores. Fruit traits can also be manipulated with biocontrol agents. 3. Functional groups of frugivores can be assembled according to broad species groupings, and further refined according to size, gape size, pre- and post-ingestion processing techniques and movement patterns, to predict dispersal and establishment patterns for plant introductions. 4. Landscape fragmentation can increase frugivore dispersal of invasives, as many invasive plants and dispersers readily use disturbed matrix environments and fragment edges. Dispersal to particular landscape features, such as perches and edges, can be manipulated to function as seed sinks if control measures are concentrated in these areas. 5. Where invasive plants comprise part of the diet of native frugivores, there may be a conservation conflict between control of the invasive and maintaining populations of the native frugivore, especially where other threats such as habitat destruction have reduced populations of native fruit species. 6. Synthesis and applications. Development of functional groups of frugivore-dispersed invasive plants and dispersers will enable us to develop predictions for novel dispersal interactions at both population and community scales. Increasingly sophisticated mechanistic seed dispersal models combined with spatially explicit simulations show much promise for providing weed managers with the information they need to develop strategies for surveying, eradicating and managing plant invasions. Possible conservation conflicts mean that understanding the nature of the invasive plant-frugivore interaction is essential for determining appropriate management.

An analysis of theories of search and search behavior

Theories of search and search behavior can be used to glean insights and generate hypotheses about how people interact with retrieval systems. This paper examines three such theories, the long standing Information Foraging Theory, along with the more recently proposed Search Economic Theory and the Interactive Probability Ranking Principle. Our goal is to develop a model for ad-hoc topic retrieval using each approach, all within a common framework, in order to (1) determine what predictions each approach makes about search behavior, and (2) show the relationships, equivalences and differences between the approaches. While each approach takes a different perspective on modeling searcher interactions, we show that under certain assumptions, they lead to similar hypotheses regarding search behavior. Moreover, we show that the models are complementary to each other, but operate at different levels (i.e., sessions, patches and situations). We further show how the differences between the approaches lead to new insights into the theories and new models. This contribution will not only lead to further theoretical developments, but also enables practitioners to employ one of the three equivalent models depending on the data available.

Traffic safety at road–rail level crossings using a driving simulator and traffic simulation

Several intelligent transportation systems (ITS) were used with an advanced driving simulator to assess its influence on driving behavior. Three types of ITS interventions were tested: video in vehicle, audio in vehicle, and on-road flashing marker. The results from the driving simulator were inputs for a developed model that used traffic microsimulation (VISSIM 5.4) to assess the safety interventions. Using a driving simulator, 58 participants were required to drive through active and passive crossings with and without an ITS device and in the presence or absence of an approaching train. The effect of changes in driver speed and compliance rate was greater at passive crossings than at active crossings. The slight difference in speed of drivers approaching ITS devices indicated that ITS helped drivers encounter crossings in a safer way. Since the traffic simulation was not able to replicate a dynamic speed change or a probability of stopping that varied depending on ITS safety devices, some modifications were made to the traffic simulation. The results showed that exposure to ITS devices at active crossings did not influence drivers’ behavior significantly according to the traffic performance indicator, such as delay time, number of stops, speed, and stopped delay. However, the results of traffic simulation for passive crossings, where low traffic volumes and low train headway normally occur, showed that ITS devices improved overall traffic performance.

A scientific approach to agent selection

The prioritisation of potential agents on the basis of likely efficacy is an important step in biological control because it can increase the probability of a successful biocontrol program, and reduce risks and costs. In this introductory paper we define success in biological control, review how agent selection has been approached historically, and outline the approach to agent selection that underpins the structure of this special issue on agent selection. Developing criteria by which to judge the success of a biocontrol agent (or program) provides the basis for agent selection decisions. Criteria will depend on the weed, on the ecological and management context in which that weed occurs, and on the negative impacts that biocontrol is seeking to redress. Predicting which potential agents are most likely to be successful poses enormous scientific challenges. 'Rules of thumb', 'scoring systems' and various conceptual and quantitative modelling approaches have been proposed to aid agent selection. However, most attempts have met with limited success due to the diversity and complexity of the systems in question. This special issue presents a series of papers that deconstruct the question of agent choice with the aim of progressively improving the success rate of biological control. Specifically they ask: (i) what potential agents are available and what should we know about them? (ii) what type, timing and degree of damage is required to achieve success? and (iii) which potential agent will reach the necessary density, at the right time, to exert the required damage in the target environment?

Weed eradication - an economic perspective

There has been recent interest in determining the upper limits to the feasibility of weed eradication. Although a number of disparate factors determine the success of an eradication program, ultimately eradication feasibility must be viewed in the context of the amount of investment that can be made. The latter should reflect the hazard posed by an invasion, with greater investment justified by greater threats. In simplest terms, the effort (and hence investment) to achieve weed eradication comprises the detection effort required to delimit an invasion plus the search and control effort required to prevent reproduction until extirpation occurs over the entire infested area. The difficulty of estimating the required investment at the commencement of a weed eradication program (as well as during periodic reviews) is a serious problem. Bioeconomics show promise in determining the optimal approach to managing weed invasions, notwithstanding ongoing difficulties in estimating the costs and benefits of eradication and alternative invasion management strategies. A flexible approach to the management of weed invasions is needed, allowing for the adoption of another strategy when it becomes clear that the probability of eradication is low, owing to resourcing or intractable technical issues. Whether the considerable progress that has been achieved towards eradication of the once massive witchweed invasion can be duplicated for other weeds of agricultural systems will depend to a large extent upon investment (. $250 million over 50 yr in this instance). Weeds of natural ecosystems seem destined to remain more difficult eradication targets for a variety of reasons, including higher impedance to eradication, more difficulty in valuing the benefits arising from eradication, and possibly less willingness to pay from society at large.