Calibration and evaluation of individual-based models using Approximate Bayesian Computation

This paper investigates the feasibility of using approximate Bayesian computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain. Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC’s accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available. It is often desirable to compare models to see whether all component modules are necessary. Here we used ABC model selection to compare the full model with a simplified version which removed the earthworm’s movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimizing an IBM’s structure and parameters within an established statistical framework, thereby making the process more transparent and objective.

Influence of individual ethical orientation on tax compliance: evidence among Ghanaian taxpayers

Even though Africa has constantly emphasized the need to reduce deficit financing through mobilization of more internal revenues, this has not been achieved. Perhaps encouraging voluntary tax compliance can improve internal revenue mobilization. This study explores the relationship between ethical orientation and tax compliance and finds that ethical persons are generally more tax compliant than unethical persons but are more influenced by considerations of tax rate and withholding positions compared to unethical persons. The findings of this study differ from Reckers et al. in a number of ways and contribute to the literature by providing a possible explanation of the cause(s) of tax non- compliance.

Unpacking the mechanism by which psychological ownership manifests at the level of the individual: a dynamic model of identity and self

Increasing prominence of the psychological ownership (PO) construct in management studies raises questions about how PO manifests at the level of the individual. In this article, we unpack the mechanism by which individuals use PO to express aspects of their identity and explore how PO manifestations can display congruence as well as incongruence between layers of self. As a conceptual foundation, we develop a dynamic model of individual identity that differentiates between four layers of self, namely, the “core self,” “learned self,” “lived self,” and “perceived self.” We then bring identity and PO literatures together to suggest a framework of PO manifestation and expression viewed through the lens of the four presented layers of self. In exploring our framework, we develop a number of propositions that lay the foundation for future empirical and conceptual work and discuss implications for theory and practice.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Individual differences in early language learning: a study of English learners of French

The present longitudinal study examines the interaction of learner variables (gender, motivation, self-efficacy and first language literacy) and their influence on second language learning outcomes. The study follows English learners of French from Year 5 in primary school (aged 9-10) to the first year in secondary school (Year 7 aged 11-12). Language outcomes were measured by two oral production tasks; a sentence repetition task and a photo description task both of which were administered at three time points. Longitudinal data on learner attitudes and motivation were collected via questionnaires. Teacher assessment data for general first language literacy attainment were also provided. The results show a great deal of variation in learner attitudes and outcomes and that there is a complex relationship between first language literacy, self-efficacy, gender and attainment. For example, in general, girls held more positive attitudes to boys and were more successful. However, the inclusion of first language ability, which explained 30-40% of variation, shows that gender differences in attitudes and outcomes are likely mediated by first language literacy and prior learning experience.

Individual and organisational leadership: the shared approach

Purpose - this paper focuses on reducing the margin for leadership error in meeting strategic aims by forming a more robust approach to developing a broader and more reliable set of leadership skills to provide a greater likelihood of strategic alignment between corporate and individual need, increasing both of their respective shelve lives.

Swift's razor

The razors, knives and “tools for cutting” that appear so often in Jonathan Swift’s writings represent linguistic instruments for the performance of speech acts. Swift often imagines them being deployed for some identifiable purpose, typically the discouragement of “fools” or “knaves” by anatomization. Their sharpness is associated with linguistic acuity, and specifically with the refinement, keenness and power of Swift’s own writing. The focus of this article, however, is on another set of associations that Swift attaches to his blades. They tend also to involve ideas of latency, divagation, bluntness, and misappropriation.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multi-model study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Inequalities in dental services utilization among Brazilian low-income children: the role of individual determinants

Objectives: To assess the role of the individual determinants on the inequalities of dental services utilization among low-income children living in the working area of Brazilian`s federal Primary Health Care program, which is called Family Health Program (FHP), in a big city in Southern Brazil. Methods: A cross-sectional population-based study was performed. The sample included 350 children, ages 0 to 14 years, whose parents answered a questionnaire about their socioeconomic conditions, perceived needs, oral hygiene habits, and access to dental services. The data analysis was performed according to a conceptual framework based on Andersen`s behavioral model of health services use. Multivariate models of logistic regression analysis instructed the hypothesis on covariates for never having had a dental visit. Results: Thirty one percent of the surveyed children had never had a dental visit. In the bivariate analysis, higher proportion of children who had never had a dental visit was found among the very young, those with inadequate oral hygiene habits, those without perceived need of dental care, and those whose family homes were under absent ownership. The mechanisms of social support showed to be important enabling factors: children attending schools/kindergartens and being regularly monitored by the FHP teams had higher odds of having gone to the dentist, even after adjusting for socioeconomic, demographic, and need variables. Conclusions: The conceptual framework has confirmed the presence of social and psychosocial inequalities on the utilization pattern of dental services for low-income children. The individual determinants seem to be important predictors of access.

Assessment of inbreeding depression in a Guzerat dairy herd: Effects of individual increase in inbreeding coefficients on production and reproduction

Influences of inbreeding on daily milk yield (DMY), age at first calving (AFC), and calving intervals (CI) were determined on a highly inbred zebu dairy subpopulation of the Guzerat breed. Variance components were estimated using animal models in single-trait analyses. Two approaches were employed to estimate inbreeding depression: using individual increase in inbreeding coefficients or using inbreeding coefficients as possible covariates included in the statistical models. The pedigree file included 9,915 animals, of which 9,055 were inbred, with an average inbreeding coefficient of 15.2%. The maximum inbreeding coefficient observed was 49.45%, and the average inbreeding for the females still in the herd during the analysis was 26.42%. Heritability estimates were 0.27 for DMY and 0.38 for AFC. The genetic variance ratio estimated with the random regression model for CI ranged around 0.10. Increased inbreeding caused poorer performance in DMY, AFC, and CI. However, some of the cows with the highest milk yield were among the highly inbred animals in this subpopulation. Individual increase in inbreeding used as a covariate in the statistical models accounted for inbreeding depression while avoiding overestimation that may result when fitting inbreeding coefficients.

The embedded cluster DBSB 48 in the nebula Hoffleit 18: Comparison with Trumpler 14

We derive fundamental parameters of the embedded cluster DBSB 48 in the southern nebula Hoffleit 18 and the very young open cluster Trumpler 14, by means of deep JHK(s) infrared photometry. We build colour-magnitude and colour-colour diagrams to derive reddening and age, based on main sequence and pre-main sequence distributions. Radial stellar density profiles are used to study cluster structure and guide photometric diagram extractions. Field-star decontamination is applied to uncover the intrinsic cluster sequences in the diagrams. Ages are inferred from K-excess fractions. A prominent pre-main sequence population is present in DBSB 48, and the K-excess fraction f(K) = 55 +/- 6% gives an age of 1.1 +/- 0.5 Myr. A mean reddening of A(Ks) = 0.9 +/- 0.03 was found, corresponding to A(v) = 8.2 +/- 0.3. The cluster CMD is consistent with the far kinematic distance of 5 kpc for Hoffleit 18. For Trumpler 14 we derived similar parameters as in previous studies in the optical, in particular an age of 1.7 +/- 0.7 Myr. The fraction of stars with infrared excess in Trumpler 14 is f(K) = 28 +/- 4%. Despite the young ages, both clusters are described by a King profile with core radii R-core = 0.46 +/- 0.05 pc and R-core = 0.35 +/- 0.04 pc, respectively, for DBSB 48 and Trumpler 14. Such cores are smaller than those of typical open clusters. Small cores are probably related to the cluster formation and/or parent molecular cloud fragmentation. In DBSB 48, the magnitude extent of the upper main sequence is Delta K-s approximate to 2 mag, while in Trumpler 14 it is Delta K-s approximate to 5 mag, consistent with the estimated ages. (c) 2008 Elsevier B.V. All rights reserved.

The old metal-poor open cluster ESO 92-SC05: accreted from a dwarf galaxy ?

The study of old open clusters outside the solar circle can bring constraints on formation scenarios of the outer disc. In particular, accretion of dwarf galaxies has been proposed as a likely mechanism in the area. We use BVI photometry for determining fundamental parameters of the faint open cluster ESO 92-SC05. Colour-magnitude diagrams are compared with Padova isochrones, in order to derive age, reddening and distance. We derive a reddening E(B - V) = 0.17, and an old age of similar to 6.0 Gyr. It is one of the rare open clusters known to be older than 5 Gyr. A metallicity of Z similar to 0.004 or [M/H] similar to -0.7 is found. The rather low metallicity suggests that this cluster might be the result of an accretion episode of a dwarf galaxy.