Rapid rural appraisal
The forerunners to contemporary approaches to involve people in natural resource research and development emerged from the use of Rapid Rural Appraisal (RRA) to assist agricultural development, particularly in developing countries, in the late 1970s. The importance of understanding the goals and circumstances of the farming family was acknowledged, and the generation of relevant technologies based on this improved understanding was the main aim of this approach. Essentially, RRA provides an array of methods and techniques (participant observation, focus groups, mental maps, etc.) to help researchers better understand the local systems they are trying to improve. As the RRA practitioner then takes this information back to the office or field station where it is used to develop or improve a subsequent technology, this approach can be regarded as 'consultative'.
Similar approaches can be seen in developed country research institutions where, despite a growing recognition of the increasing complexity and social construction of natural resource management issues, there have been few recent innovations in research methodology other than the development of quantitative modelling and an increased focus on the development of expert systems (Ison & Ampt 1992; Whittaker 1993). Traditional approaches to the development of these models have, as Argent et al. (1999 p. 696) put it, 'involved a researcher, an office, a computer, and some computer code, perhaps with a pile of journal papers, a questionnaire, some monitoring, a considerable amount of thought, and, possibly, a dart board thrown in!' In addition, the research systems in which these DSS have been developed have been, and still are, largely characterised by the linear transfer of technology (TOT) model of agricultural research and development (Russell et al. 1989). The dominant metaphors are those of 'information transfer', 'channels of communication' and 'teaching', most of which arise from mistakenly seeing human communication in the same way as data transferred between computers (Ison 1993a p.157).
This organisational perspective of R&D can be characterised as technological problem-solving in the narrow sense and fails to view real-life problems as a set of changing, interdependent systems perceived in subjectively different ways by different people. Solutions typically focus on the immediate situation and treat only the symptoms of a problem. Not surprisingly, as Dahlberg (1991 p. 338) points out, these approaches tend to be reductionist and based on single disciplines. The primary focus is on the end state, with success being measured through narrow economic or productivity criteria.
Essentially, the above approaches seek to improve hard systems, and 'make possible the efficient achievement of goals or objectives, taking goal-seeking to be an adequate model of human behaviour' (Checkland 1985a p. 765). These approaches are particularly suited to the management of hard system problem situations characterised by 'easy-to-define objectives, clearly defined decision-taking procedures and quantitative measures of performance' (Checkland 1981b p. 288). The underlying question being asked in this sense is, 'Can we do it'? Thus R&D is seen essentially as a problem-solving approach based upon tactical and situation-oriented decision making. The result is an emphasis on changing the physical environment, while leaving the basic value systems untouched (Petak 1980 p. 288).
Participatory Rural Appraisal
At the end of the 1980s Participatory Rural Appraisal (PRA) approaches began to evolve in the search for practical ways to support decentralised planning and democratic decision-making, value social diversity, work towards sustainability and enhance community participation and empowerment. Again this change can more easily be seen to have begun in developing countries. Rapid Rural Appraisal techniques are still used within PRA, but importantly it involves the researcher planning changes to the farming system 'with' the farmer. This approach recognises that the problems facing farmers are not solely biological or technical, and acknowledges the value of local experience and knowledge. It advocates that the best way to incorporate this is through the active involvement of local people in the research process.
In this context, PRA can be described as 'a growing family of approaches and methods to enable local people to share, enhance and analyse their knowledge of life and conditions, and to plan, act, monitor and evaluate' (Chambers & Guijt 1995). The key to their success is that the probability of commitment to and adoption of changed practices is likely to be higher because the stakeholders have helped design the solutions, and understand how to make them work.
A number of terms exist to describe these systems of learning and action. Farmer First, Farming Systems Research & Extension (FSRE), agroecosystem analysis and Farmer Participatory Research are all approaches with strong methodological similarities used within developing country agriculture. In Australasia 'landcare' is the name given to the many voluntary and predominantly rural groups who work together to address land degradation issues. The 1990s were promoted by the Australian Government as the 'Decade of Landcare' and by 1994 there were already over 2000 such groups, involving about one-third of Australian farming families (Campbell 1995 p.127). Other examples of successful practical applications can now be seen in a range of other areas including health, nutrition, poverty and livelihood development programmes.
Implicit within these approaches is a realisation that new sources of 'expert' knowledge and data bases are needed to identify persistent and socially acceptable resource management practices more clearly. In many cases the knowledge required about the past and present states of our natural resources, and about the relationships between social and environmental systems, is held within local communities and other interested groups. Accordingly, it follows that the task of organising information to understand better the links between natural resource management and ecological dynamics should be a co-operative venture between research scientists, local communities and policy makers. In this sense collaborative approaches to natural resource R&D are, in the first instance, about learning (debate and reflection) and negotiation, rather than the provision of reports and technologies.
Where these participatory initiatives have worked it is because individual communities and groups have shown the benefits of working collaboratively, of developing a collective vision and learning and adapting their management practices together. However, despite the increasing numbers of participatory initiatives in different parts of the world, it is clear that most of these are still only 'islands of success' (El Swaify et al. 1999 p. 37). As Pretty (1998) emphasises, true participatory projects are those that empower people by building skills, interests and capacities that continue even after the project ends. This implies the institutionalisation of such initiatives and the corresponding capacity for activities to spread beyond the immediate project in both space and time. Also much of what is billed as participation is so in name only (Allen 1997 p. 630), lacking genuine engagement with stakeholders. Moreover, in many of these participatory initiatives science has appeared to be bypassed.
The whole RRA/PRA movement came originally from scientists and professionals seeking a greater awareness of people's needs by asking the right questions in a local-friendly way. The mantle of the inviolability of science was being raised ever so slightly. In contrast, the farmer-first movement swung the whole emphasis to meeting exactly those locally-articulated needs, whatever they may be and through whatever lens of prejudice they may have passed. The formal scientific contribution was demoted; interest groups other than the local community were downgraded; corruption and local political power-play were ignored; and the beneficial possibilities of external interventions were diminished -- all in the name of participation. Just as scientists are often prejudiced and simply wrong, a totally bottom-up approach is unlikely to promote the ideals of a sustainable planet (El Swaify et al. 1999 pp. 38-39).
Science has an important role to play in helping the different actors in the natural resource system (such as a watershed or disease environment) see how events and processes in their own enterprise or area are affected by, and contribute to, the larger-scale system dynamic (Jiggins 1993 p.189). As Loevinsohn et al. (1999) point out, key processes -- natural, social or economic -- are often poorly visible, some occurring on very large or small temporal or spatial scales, others just difficult to make out. In these situations an aid of some sort is required to help people see more clearly. Making things visible, often through the development of computer models, is not only a valuable mechanism for systematising knowledge, information and experience -- a key justification for many research initiatives. It is also 'an important means for initiating participation leading to the higher level of organisation and collaborative learning necessary for the management of larger-scale systems' (Jiggins 1993 p.189).
However, in the main, application of contemporary approaches to improve participation still fails to grasp the nature of the rapidly evolving social forces that are driving natural resource management systems today. For example, there are very few references in the agricultural R&D literature to participatory projects other than those which involve farmers and scientists dealing with agricultural management issues (Allen 1997 p. 634). Yet as communities and agriculture change, the juxtaposition of farming and other rural activities has become a battleground over property rights, water and related nutrient management issues, as well as other community impacts of changing land use (Abdalla & Kelsey 1996 p. 462). In these situations human interactions, behaviour and organisational relationships can be seen to be the driving forces.
More recently attention has shifted towards the use of action learning and research to more explicitly address the human dimension of agricultural and other natural resource management problems (Bawden et al. 1984; Scoones & Thompson 1994). These approaches explicitly recognise that natural resource management in the age of sustainability is not characterised so much by problems for which an answer must be found, but rather issues that need to be resolved and will inevitably require one or more of the parties to change their views (Bawden et al. 1984). They are an approach to deal with 'soft systems', 'in which objectives are hard to define, decision-taking is uncertain, measures of performance are at best qualitative and human behaviour is irrational' (Checkland 1981b p.288).
In response to these issues we are beginning to see increased interest in the application of more 'collaborative' or multi-stakeholder processes that facilitate the wide involvement of individuals, groups and organisations in problem solving and decision making with respect to issues and plans that involve or affect them. These processes also provide an acknowledgement that decisions related to sound land use will be dependent on the co-ordinated actions of many land managers and agencies, who in turn must act within the confines of a wider regulatory framework imposed by the community at large.
Despite the important role which science can play within natural resource management, researchers need to be aware that ecological information is only one factor affecting the way in which decisions on natural resource management are made -- and it is not always the most significant. 'Integration of ecological knowledge with critical socio-economic issues leads to the conclusion that other structural and institutional factors are more limiting to good management than ecological knowledge' (Stafford Smith et al. 1997). Other factors in this regard include political judgement, legal or financial necessity, personal or group bias, and commercial or international pressures. 'In most cases, the scientific argument for ... sustainable use of natural resources is abundantly clear: what remains is to raise awareness of this understanding over competing interests, reinforcing the need for information to emerge from within the decision making environment' (Reynolds & Busby 1996 p. 14).
Ecologists need to emphasis the very real contribution that ecological understanding can provide to the policy debate (over rangeland management), but must also be humble in recognising that this contribution is a small part of an integrated whole. ... But if ecologists continue to imagine that solutions to the problems of rangeland management are to be found through ecology alone, they will not only be wrong, but they risk becoming even more marginalised from the policy process than they currently are. ... The message is plain: we need to be honest, modest and strategically aware about our place in the spectrum of decision-making on natural resources, but simultaneously insistent that without this input, the value to society of the natural world will continue to decline. However, there is no point in bewailing the Philistines; it is ecologists who have the major short-term vested interest in seeing ecology used in decision making, and so it is ecologists who must go the extra mile to enable this input to be heard (Stafford Smith et al. 1997).
What has become increasingly obvious is that the major obstacles to improved use of information in decision making are social and organisational, not technological in nature, meaning that investments in ecological research and its supporting information technology alone will not provide a solution (Reynolds & Busby 1996 p.13). These authors suggest that one of the main reasons why environmental information systems fail to be integrated into mainstream decision making processes is that they are often developed apart from management and policy making processes -- rather than emerging from within. For information to be appreciated and used, those who are expected to use it must be aware of how and why it has been produced.
It naturally follows that as directions for natural resource management emerge from such collaborative processes, it will still be necessary to utilise more traditional science approaches to help achieve them. These learning-based approaches to problem solving acknowledge a continuum of approaches to address both 'soft' and 'hard' issues as well as more 'basic' research questions, contingent on the nature of the problem (Figure 2.2). And now, more than ever, there is room for all these different approaches. Accordingly, the basic nature of work undertaken by individual scientists will not change, the only difference being that the starting point for scientific endeavours is firmly embedded in the wider community.
Figure 2.2 Continuum of approaches to problem solving and situation improvement (adapted from Bawden 1991).
This more inclusive approach to natural resource R&D recognises that environmental management is at least as much about managing human activities as it is about managing lands and waters. As Christensen et al. (1996) point out, ecosystem management is inextricably linked with current trends related to population growth, poverty and human perceptions about energy and natural resources. 'Concerns such as the rights of private property owners and local loss of jobs is unlikely to diminish, and ecosystem management must include strategies that deal positively with those concerns' (Christensen et al. 1996). There is now a recognition that constructive change can only happen and be sustained if the people involved are included and empowered to make decisions. People's participation, the integration of the efforts of institutions and improved flows of information are indispensable to the building of real and lasting capacity for sustainable human development (Capacity 21 Programme 1996).
Empowerment in this sense differs from common usage of the term. It does not mean power-balancing or redistribution, but rather, increasing the skills of individuals, groups and communities to make better decisions for themselves. This idea of empowerment means 'the restoration to individuals of a sense of their own value and strength and their own capacity to handle life's problems' (Bush & Folger 1994 p. 2 quoted in Burgess & Burgess 1997). This capacity is relevant to environmental decision-making, as these authors further explain in a subsequent publication that though empowerment groups gain 'greater clarity about their goals, resources, options and preferences' and that they use this information to make their own 'clear and deliberate decisions' (Folger & Bush 1996 p. 264 quoted in Burgess & Burgess 1997).
In a similar vein, Page and Czuba (1999) suggest that:
... empowerment is a multi-dimensional social process that helps people gain control over their own lives. It is a process that fosters power (that is, the capacity to implement) in people, for use in their own lives, their communities, and in their society, by acting on issues that they define as important.
One crucial implication of this definition of empowerment for those concerned with bringing about change in the way we manage our natural resources is that it acknowledges that the individual and the community are fundamentally connected.
This does not mean that we can point the finger at those with less access to power, telling them that they must change to become more like 'us' in order to be powerful/successful. Rather individual change becomes a bridge to community connectedness and social change (Wilson 1996). To create change we must change individually to enable us to become partners in solving the complex issues facing us. In collaborations based on mutual respect, diverse perspectives, and a developing vision, people work towards creative and realistic solutions. This synthesis of individual and collective change is our understanding of an empowerment process (Page & Czuba 1999).
In response to these acknowledgements and challenges, many contemporary research efforts are concentrating on creating new approaches to more closely link science, management and policy at an ecosystem level. As Jiggins (1993 p.189) points out, these efforts represent a search for a R&D model and practice that combine the features of: i) management-based experimentation and innovation; ii) natural resource system management on scales larger than individual enterprises and communities; iii) methods for bringing about capacity for action among multiple agencies and actors (with typically divergent, not to say antagonistic points of view and interests); and iv) facilitation of the social processes and organisational capacity to accomplish these.
One promising initiative is in the area of adaptive management (AM), or adaptive environmental assessment and management (AEAM), which is emerging through the integration of ecological and participatory research approaches (Lee 1993; Gunderson et al. 1995; Bosch et al. 1996a; Dovers and Mobbs 1997; Christensen et al. 1996; Allen et al. 1998b). Adaptive management in this sense refers 'to a structured process of "learning by doing" that involves much more than simply better ecological monitoring and response to unexpected management impacts' (Walters 1997). The major direction initially taken in AM was quantitative modelling workshops wherein teams of scientists and resource managers collaborated in developing and evaluating alternative options in reasonably discrete management contexts such as smaller catchments, forest areas, or where the range of management issues was bounded (Walters 1986; Grayson et al.1994). More recently, as Dovers and Mobbs (1997) point out, there have been important developments in the linking of two areas which were previously largely unrelated. These are applying the adaptive concept in more complex, regional or large-scale contexts, and combining the ecological insights of 'traditional' AM with social learning and institutional perspectives.
This emerging form of adaptive management has some important features suiting it to the demands required by contemporary R&D models stated earlier. 'Information is central, the focus is on integrating natural system and institutional social dimensions, and it is absolutely and inevitably multi-disciplinary. Crucially, it is the only approach to policy and management where ecology has played and is playing a core role' (Dovers & Mobbs 1997). AM thus 'satisfies a widely perceived need to give more prominence to ecological imperatives, at a time when economics provides the dominant model for the design of the future' (Jiggins and Röling 1999). Moreover, in its emerging form, AM recognises the limitations of an 'expertise' model of science -- particularly in complex decision contexts with multiple interests, values and property regimes (e.g. Lee 1993; Dovers and Mobbs 1997). As a number of reviewers argue, the integration of research insights at the ecosystem scale can only be accomplished within a democratic, collective decision-making process, the combination of both science and politics being a prerequisite for effective learning (e.g. Lee 1993; Funtowicz & Ravetz 1994; Jiggins & Röling 1999).
However, despite the logic and appeal of AM as an approach to help decision making in complex, regional or large-scale ecosystem contexts, its success in practice has been rather less than spectacular (e.g. McLain & Lee 1996; Walters 1997). There is emerging concern that the long-term effectiveness of such approaches is limited by a number of barriers, most of which can be classed as social and institutional rather than technical (e.g. Campbell 1995; McLain and Lee 1996; Yaffee 1997; Pretty 1998; Allen et al. 2000). These include the continued reliance on a linear transfer of technology (TOT) model of R&D, fragmented information and knowledge systems, a tendency to discount non-scientific forms of knowledge, institutional cultures within research and policy making that work against genuinely participatory approaches, and a failure to provide appropriate processes to promote the development of shared understandings among diverse stakeholders.
It is these social and institutional issues, and how to overcome them, that are the subject of this thesis inquiry. Through the case studies outlined here the primary action research learning group (myself, Ockie Bosch and Margaret Kilvington) have sought to identify insights and approaches which can help agency staff, iwi, science programme leaders, and other interested groups to constructively change people's relationship to their environment, and encourage them to make more use of underpinning science as they go about their decision making. This research has used an action research approach (see Chapter 3) to find improved ways of managing collaborative or multi-stakeholder approaches to environmental management, and to establish the development of an integrated information framework to underpin subsequent decision making.