INTRODUCTION

The emerging field of community and ecosystem genetics has so far focused on how the genetic variation in one species can influence the composition of associated communities and ecosystem processes such as decomposition (see definitions in Table 3–1; reviews by Whitham et al. 2003, 2006; Johnson & Stinchcombe 2007; Hughes et al. 2008). A key component of this approach has been an emphasis on understanding how the genetics of foundation plant species influence a much larger community. It is reasoned that because foundation species structure their ecosystems by creating locally stable conditions and provide specific resources for diverse organisms (Dayton 1972; Ellison et al. 2005), the genetics of these species as “community drivers” are most important to understand and most likely to have cascading ecological and evolutionary effects throughout an ecosystem (Whitham et al. 2006). For example, when a foundation species’ genotype influences the relative fitness of other species, it constitutes an indirect genetic interaction (Shuster et al. 2006), and when these interactions change species composition and abundance among individual tree genotypes, they result in individual genotypes having distinct community and ecosystem phenotypes. Thus, in addition to an individual genotype having the “traditional” phenotype that population geneticists typically consider as the expression of a trait at the individual and population level, community geneticists must also consider higher-level phenotypes at the community and ecosystem level. The predictability of phenotypes at levels higher than the population can be quantified as community heritability (i.e., the tendency for related individuals to support similar communities of organisms and ecosystem processes; Whitham et al. 2003, 2006; Shuster et al. 2006).

Introduction

The objective of this chapter is to provide an insight in to the background research, development, and practical application of the Integrated Performance Measurement Systems (IPMS) Reference Model and the associated audit method. The research described was conducted by a multidisciplinary team based at the Centre for Strategic Manufacturing, University of Strathclyde. The research was funded through EPSRC and industry.

The point of departure for this work was that:

1. 1 There are various performance measurement systems models, frameworks, and methodologies available – such as SMART (Cross and Lynch, 1988–9), Performance Measurement Questionnaire (Dixon, Nanni, and Vollmann, 1990), Performance Measurement for World Class Manufacture (Maskell, 1989), Performance Criteria System (Globerson, 1985), Cambridge Performance Measurement Design Process (Neely, Gregory, and Platts, 1995; Neely et al., 1996) and Balanced Scorecards (Kaplan and Norton, 1992 and 1996).

2. 2 Other fields, such as Quality Management and Environmental Management, have auditable reference models and standards that describe the structure and content of a robust management system, i. e. ISO9000, QS9000, and ISO14000.

3. 3 However, an auditable reference model, which describes the structure and constituent parts of a robust, integrated, efficient, and effective performance measurement system, was not available (Bititci, Carrie, and McDevitt, 1996).

The overall aim of the work was to establish whether an auditable reference model for IPMS could be developed. The more specific objectives included:

• to research and model the hierarchical structure and relationships between performance measures.

• to research and develop a reference model for comparison and benchmarking of integrated performance measurement systems;

• to provide a workbook and computer-based analysis tool to assist companies in auditing their performance measurement systems;

• to illustrate the methods developed using industrial case studies.