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Considerations in Representing Human Individuals in Social-Ecological Models

Michael J. Manfredo, Tara L. Teel, Michael C. Gavin, and David Fulton

Purpose

The most troubling problems in conservation – deforestation, land degradation, biodiversity loss, and climate change – are difficult to isolate and examine as independent phenomena. Increasingly, the view from science casts these as outcomes from complex interactions within and between human society and its biophysical context. Reductionist science is poorly suited for representing such complexity, and that has given rise to multidisciplinary, multi-level systems approaches. This increase in multidisciplinary approaches has created a transformative wave of change as the existing institutions of conservation science absorb, adapt, and give way to innovations that can advance such approaches.

In this chapter, we examine how conservation science that focuses on the human individual – particularly the tradition of social science research that has emerged under the flag of “human dimensions of natural resources” – might fit within a systems approach. Our examination of this topic has a dual purpose: to suggest the implications for (1) how ecosystem sciences can integrate the human individual into dynamic, multi-level models, and (2) how human dimensions research can envision the individual and direct new research initiatives in a broader socialecological context.

Impetus for Change Emanating from Ecological Sciences

Historically, biological traditions have set the direction of natural resources research and that is also the case in the drive toward multi-scale, multi-level and multi-disciplinary approaches. More specifically, this new direction in natural resources research is borne from the shift toward systems science in ecology.

C. S. Holling (1998) described the ecosystems approach by contrasting two cultures in the ecological sciences. The traditional approach was reductionist, narrow and targeted, experimentally focused, concerned with Type I error, hypothesis testing and standard statistics. In this culture, the environment is viewed as largely fixed and at a single scale, and causation is considered single and separable. The other fast-emerging culture was seen as broad, exploratory, multi-disciplinary and integrative, and it is focused on multiple lines of converging evidence. It uses nonstandard statistics and is concerned with Type II error. It takes a systems view of the environment, describing the environment's dynamic qualities as self-organizing with multiple interactions, and operating at multiple scales.

This systems approach views nature as complex, dynamic, and adaptive. The system reveals both chaos and order, has continuous and discontinuous elements, and is marked by abrupt change (Holling et al. 2002). Hierarchy is central to this conceptualization. Phases of change are proposed to occur within multi-scale, multi-level structures that are nested within a broader hierarchy. The structures move at separate speeds and are multi-directional in their effects. Each level experiences its own change cycle, but slower and larger scales set conditions for faster, smaller ones, whereas the latter are the sites of variation that can generate functional shifts at higher scales. Systems are seen as having varying degrees of resilience – a reference to their ability to retain crucial functions during episodes of change. Adger et al. (2005) suggest that “the concept of resilience is a profound shift in traditional perspectives, which attempt to control changes in systems that are assumed to be stable, to a more realistic viewpoint aimed at sustaining and enhancing the capacity of social-ecological systems to adapt to uncertainty and surprise” (p. 1036).

 
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