extended peer networks and sets of guiding principles and questions. Hence the importance of networks and communities of practice that cross not only disciplinary boundaries but also boundaries that have traditionally separated academic scholarship from community-based research and indigenous knowledge (Berger-González et al., Chapter 6, this volume).
The Ecosystem Approach
Ecosystem approaches are distinguished from other approaches in environmental and resources management by the use of the ecosystem construct as a metaphor for holistic thinking, attention to the evolutionary and dynamic nature of complex situations, and the incorporation of processes to accommodate management of such situations with multiple interests and stakeholders, and across multiple jurisdictions (Yaffee, 1999). Figure 4.1 presents a version of the ‘diamond diagram’ that represents the adaptive ecosystem approach that has influenced many ecohealth applications. This version of the ecosystem approach (Bunch, 2001) was based on that developed by James Kay and his colleagues in the 1990s (Kay et al., 1999) and further elaborated in the book The Ecosystem Approach: Complexity, Uncertainty and Managing for Sustainability (Waltner-Toews et al., 2008). This expression of the ecosystem approach is explicitly positioned as PNS and informed by ideas about self-organizing, holarchic and open (SOHO) systems. While challenging to understand for the novice, the language and theory of these systems has provided a useful way to think about, and manage, what might otherwise appear to be a kind of paralysing complexity and to anticipate and plan for unintended consequences.
Fig. 4.1. A framework for an adaptive ecosystem approach. From Bunch (2001), adapted from Kay et al., 1999.
Self-organization is a characteristic of complex systems that leads to emergence, and is related to systems and complexity science concepts such as resilience, adaptation, regime change and tipping points. Within the One Health field, one might think of the health of individual animals and people being embedded in, and interacting with, families or herds, which are nested within larger social and ecological units, which are further nested within – affecting and being affected by – global trading and climate systems. People and individual animals have their own particular characteristics (emergent properties), as do families and herds and so on. Each unit (person/animal, herd/family) can be viewed as both a whole, with its own internal dynamics, and also as a part of something larger. Philosopher Arthur Koestler (1968) referred to such ‘two-faced’ units as holons, and the nested organization as a holarchy.
This way of looking at the world implies the need to identify appropriate scales of attention as well as within- and across-scale interactions – which for many human health and animal health workers is a formalization of common sense. Does one target individuals, households, communities (or their animal counterparts), or some combination? The ‘open systems’ of the SOHO concept refers to the fact that such systems are those in which information, energy or matter (inputs) flow through, are transformed in, and drive the processes occurring within systems. The SOHO concepts are some of the systems thinking ideas used by practitioners throughout the application of the ecosystem approach.
There are three general phases evident in the ecosystem approach framework presented in Fig. 4.1: (i) problem identification and system description (the box at the top of the diagram); (ii) making decisions and taking action; and (iii) ongoing learning, adaptation and management that subsumes and iterates the process. In this general framework methods and techniques are not prescribed, although both systems approaches and collaborative process are intended to operate the approach throughout.
Problem identification and system description (sometimes called a system study) begin the engagement with a messy problematic situation, including stakeholders and actors. An important part of this is the identification and description of the ‘problemshed’. (This may be tied to geographic constructs such as watersheds.) It involves developing an appreciation of the nature and spatial and temporal scales of relationships associated with a problematic situation. It is a collaborative process of discovery to understand historical context, identify and meaningfully engage and empower actors and stakeholders, develop knowledge about key components and relationships, understand pertinent values and preferences and physical and cultural possibilities. This work draws key relationships in the system to the fore, indicating their spatial and temporal footprint and bounding the situation so as to identify the system, its wider systems and environments and subsystems and components.
The social-ecological system identification generates understanding of systemic possibilities that might exist in the situation. From this, researchers work with stakeholders to identify alternative futures (scenarios) that are systemically desirable and culturally feasible. One of these alternatives is selected to inform intervention. This is a different role for researchers than that with which traditional scientists will be familiar, and it is a characteristic of working in the ‘post-normal’ mode in situations of uncertainty and complexity. James Kay (2008), a key formulator of this type of approach, explains that:
Investigators into complexity do not seek prediction, control, right answers or efficiency. These are not sensible goals under conditions of complexity. Rather, the investigators seek understanding, adaptability, and resilience. Scientific inquiry, more than ever, becomes an act of collaborative learning and knowledge integration. The role of the expert shifts from problem solving to an exploration of possibilities and from giving correct advice to sharing information about options and trade-offs. In fact, those who cling to being the old sort of expert lose their expertise.
(Kay, 2008, p. 80)
This new role for experts derives from the failure to manage complex situations using reductionist and mechanistic ways. Such situations are characterized by discontinuities in linear chains of cause and effect. They cannot be managed as if they were sets of levers and cogs in a machine. Instead, complex systems must be encouraged to self-organize around desirable alternative system configurations. A system’s trajectory of change cannot be entirely controlled, and there may be surprises along the way. It is more analogous to raising a baby to adulthood than to sending a spacecraft to the moon. With the rocket, there is a relatively high degree of certainty of the outcome, each successive attempt is similar in critical ways and sending one successful rocket improves the chances of the next. In raising a child, experience and expertise help, but the outcome remains uncertain. Each child is unique and formulae have limited application (Glouberman and Zimmerman, 2002).
Thus, when we attempt to understand and intervene in complex situations, we need to monitor key relationships to learn about system behaviour. This is necessary to be adaptive. Applied research, public health interventions, and other projects that attempt to engage with complex environment-and-health problems must constantly re-evaluate the conceptual model of the system and the efficacy and outcomes of interventions. There should be openness, even an orientation to revising and adjusting the strategy. The ecosystem approach is an adaptive management approach. Practitioners of adaptive management monitor in order to support collaborative learning.
Based on the ‘diamond diagram’ in Fig. 4.1, AMESH (Adaptive Methodology for Ecosystem Sustainability and Health) was developed
