Integrating socio-economics and ecology: a taxonomy of quantitative methods and a review of their use in agro-ecology

Answering many of the critical questions in conservation, development and environmental management requires integrating the social and natural sciences. However, understanding the array of available quantitative methods and their associated terminology presents a major barrier to successful collaboration. We provide an overview of quantitative socio-economic methods that distils their complexity into a simple taxonomy. We outline how each has been used in conjunction with ecological models to address questions relating to the management of socio-ecological systems. We review the application of social and ecological quantitative concepts to agro-ecology and classify the approaches used to integrate the two disciplines. Our review included all published integrated models from 2003 to 2008 in 27 journals that publish agricultural modelling research. Although our focus is on agro-ecology, many of the results are broadly applicable to other fields involving an interaction between human activities and ecology. We found 36 papers that integrated social and ecological concepts in a quantitative model. Four different approaches to integration were used, depending on the scale at which human welfare was quantified. Most models viewed humans as pure profit maximizers, both when calculating welfare and predicting behaviour. Synthesis and applications. We reached two main conclusions based on our taxonomy and review. The first is that quantitative methods that extend predictions of behaviour and measurements of welfare beyond a simple market value basis are underutilized by integrated models. The second is that the accuracy of prediction for integrated models remains largely unquantified. Addressing both problems requires researchers to reach a common understanding of modelling goals and data requirements during the early stages of a project.

Genetic characterization of tick-borne flaviviruses: new insights into evolution, pathogenetic determinants and taxonomy

Here, we analyze the complete coding sequences of all recognized tick-borne flavivirus species, including Gadgets Gully, Royal Farm and Karshi virus, seabird-associated flaviviruses, Kadam virus and previously uncharacterized isolates of Kyasanur Forest disease virus and Omsk hemorrhagic fever virus. Significant taxonomic improvements are proposed, e.g. the identification of three major groups (mammalian, seabird and Kadam tick-borne flavivirus groups), the creation of a new species (Karshi virus) and the assignment of Tick-borne encephalitis and Louping ill viruses to a unique species (Tick-borne encephalitis virus) including four viral types (i.e. Western Tick-borne encephalitis virus, Eastern Tick-borne encephalitis virus, Turkish sheep Tick-borne encephalitis virus and Louping ill Tick-borne encephalitis virus). The analyses also suggest a complex relationship between viruses infecting birds and those infecting mammals. Ticks that feed on both categories of vertebrates may constitute the evolutionary bridge between the three distinct identified lineages.

Navigation assistance for wayfinding in the virtual environments: taxonomy and a survey

Efficient Navigation is essential for the user-acceptance of the Virtual Environments (VEs), but it is also inherently, a difficult task to perform. Resulting research in the area provides users with great variety of navigation assistance in VEs however it is still known to be inadequate, complex and suffers through many limitations. In this paper we discuss the task of navigation in the virtual environments and record the wayfinding assistance currently available for the VEs. The paper introduces taxonomy of navigation and categorizes the aids on basis of the functions performed. The paper provides views on current work performed in the area of non-speech auditory aids. Further we conclude by providing views on the important areas that require further investigation and research.

Taxonomy of purpose of Enterprise Architecture

Initial phase of all Enterprise Architecture (EA) initiatives is important. One of the most crucial tasks in that phase is to sell EA to the top management by explaining its purpose. In this paper, by using semiotic framework we show that there is a clear gap between the definition of EA and its purpose. Contribution of this paper is a taxonomy that expands knowledge of pragmatics of EA, and that can be used as a tool for explaining the purpose of EA. Grounded theory is used to form the taxonomy. Data is collected from a discussion group used by EA practitioners. Results indicate that the purpose of EA is to meet organisations‟ stakeholder‟s goals and to create value to organisation. Results are in line with current literature. Most interesting result is that EA practitioners seem to realise that technical solutions are not the purpose of EA, but means for fulfilling it.

Developing green supply chain management taxonomy-based decision support system

The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.