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.

Globular adiponectin induces platelet activation through the collagen receptor GPVI-Fc receptor gamma chain complex.

We identify gAd as a novel ligand for GPVI that stimulates tyrosine kinase-dependent platelet aggregation. Our data raise the possibility that gAd may promote unwanted platelet activation at sites of vascular injury.

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.