Development and application of a multiple linear regression model to consider the impact of weekly waste container capacity on the yield from kerbside recycling programmes

The paper describes the development and application of a multiple linear regression model to identify how the key elements of waste and recycling infrastructure, namely container capacity and frequency of collection affect the yield from municipal kerbside recycling programmes. The overall aim of the research was to gain an understanding of the factors affecting the yield from municipal kerbside recycling programmes in Scotland. The study isolates the principal kerbside collection service offered by 32 councils across Scotland, eliminating those recycling programmes associated with flatted properties or multi occupancies. The results of a regression analysis model has identified three principal factors which explain 80% of the variability in the average yield of the principal dry recyclate services: weekly residual waste capacity, number of materials collected and the weekly recycling capacity. The use of the model has been evaluated and recommendations made on ongoing methodological development and the use of the results in informing the design of kerbside recycling programmes. The authors hope that the research can provide insights for the ongoing development of methods to optimise the design and operation of kerbside recycling programmes.

Identifying functional stakeholder clusters to maximise communication for the ecosystem approach to fisheries management

Interaction with ecological models can improve stakeholder participation in fisheries management. Problems exist in efficiently communicating outputs to stakeholders and an objective method of structuring stakeholder differences is lacking. This paper aims to inform the design of a multi-user communication interface for fisheries management by identifying functional stakeholder groups. Intuitive categorisation of stakeholders, derived from survey responses, is contrasted with an Evidence-Based method derived from analysis of stakeholder literature. Intuitive categorisation relies on interpretation and professional judgement when categorising stakeholders among conventional stakeholder groups. Evidence-Based categorisation quantitatively characterises each stakeholder with a vector of four management objective interest-strength values (Yield, Employment, Profit and Ecosystem Preservation). Survey respondents agreed little in forming intuitive groups and the groups were poorly defined and heterogeneous in interests. In contrast the Evidence-Based clusters were well defined and largely homogeneous, so more useful for identifying functional relations with model outputs. The categorisations lead to two different clusterings of stakeholders and suggest unhelpful stereotyping of stakeholders may occur with the Intuitive categorisation method. Stakeholder clusters based on literature-evidence show a high degree of common interests among clusters and is encouraging for those seeking to maximise dialogue and consensus forming. © 2013 Elsevier Ltd.

Emerging asymmetric interactions between forage and predator fisheries impose management trade-offs

A size and trait-based marine community model was used to investigate interactions, with potential implications for yields, when a fishery targeting forage fish species (whose main adult diet is zooplankton) co-occurs with a fishery targeting larger-sized predator species. Predicted effects on the size structure of the fish community, growth and recruitment of fishes, and yield from the fisheries were used to identify management trade-offs among the different fisheries. Results showed that moderate fishing on forage fishes imposed only small effects on predator fisheries, whereas predator fisheries could enhance yield from forage fisheries under some circumstances.