Design of effective decision-making processes
Decisions affecting ecosystems and their services can be improved by changing the processes used to reach those decisions. The context of decision-making about ecosystems is changing rapidly. The new challenge to decision-making is to make effective use of information and tools in this changing context in order to improve the decisions. At the same time, some old challenges must still be addressed. The decision-making process and the actors involved influence the intervention chosen. Decision-making processes vary across jurisdictions, institutions, and cultures. Yet the MA has identified the following elements of decision-making processes related to ecosystems and their services that tend to improve the decisions reached and their outcomes for ecosystems and human well-being (R18ES):
- Use the best available information, including considerations of the value of both marketed and nonmarketed ecosystem services.
- Ensure transparency and the effective and informed participation of important stakeholders.
- Recognize that not all values at stake can be quantified, and thus quantification can provide a false objectivity in decision processes that have significant subjective elements.
- Strive for efficiency, but not at the expense of effectiveness.
- Consider equity and vulnerability in terms of the distribution of costs and benefits.
- Ensure accountability and provide for regular monitoring and evaluation.
- Consider cumulative and cross-scale effects and, in particular, assess trade-offs across different ecosystem services.
Awide range of deliberative tools (which facilitate transparency and stakeholder participation), information-gathering tools (which are primarily focused on collecting data and opinions), and planning tools (which are typically used to evaluate potential policy options) can assist decision-making concerning ecosystems and their services (R3 Tables 3.6 to 3.8). Deliberative tools include neighborhood forums, citizens’ juries, community issues groups, consensus conferences, electronic democracy, focus groups, issue forums, and ecosystem service user forums. Examples of information-gathering tools include citizens’ research panels, deliberative opinion polls, environmental impact assessments, participatory rural appraisal, and rapid rural appraisal. Some common planning tools are consensus participation, cost-benefit analysis, multicriteria analysis, participatory learning and action, stakeholder decision analysis, trade-off analysis, and visioning exercises. The use of decision-making methods that adopt a pluralistic perspective is particularly pertinent, since these techniques do not give undue weight to any particular viewpoint. These tools can be used at a variety of scales, including global, sub-global, and local.
A variety of frameworks and methods can be used to make better decisions in the face of uncertainties in data, prediction, context, and scale (R4.5). Commonly used methods include cost-benefit or multicriteria analyses, risk assessment, the precautionary principle, and vulnerability analysis. (See Table 8.1.) All these methods have been able to support optimization exercises, but few of them have much to say about equity. Cost-benefit analysis can, for example, be modified to weight the interests of some people more than others. The discount rate can be viewed, in long-term analyses, as a means of weighing the welfare of future generations; and the precautionary principle can be expressed in terms of reducing the exposure of certain populations or systems whose preferential status may be the result of equity considerations. Only multicriteria analysis was designed primarily to accommodate optimization across multiple objectives with complex interactions, but this can also be adapted to consider equity and threshold issues at national and sub-national scales. Finally, the existence and significance of various thresholds for change can be explored by several tools, but only the precautionary principle was designed explicitly to address such issues.
Scenarios provide one way to cope with many aspects of uncertainty, but our limited understanding of ecological and human response processes shrouds any individual scenario in it own characteristic uncertainty (R4ES). Scenarios can be used to highlight the implications of alternative assumptions about critical uncertainties related to the behavior of human and ecological systems. In this way, they provide one means to cope with many aspects of uncertainty in assessing responses. The relevance, significance, and influence of scenarios ultimately depend on who is involved in their development (SG9.ES).
At the same time, though, there are a number of reasons to be cautious in the use of scenarios. First, individual scenarios represent conditional projections based on these specific assumptions. Thus, to the extent that our understanding and representation of the ecological and human systems represented in the scenarios is limited, specific scenarios are characterized by their own uncertainty. Second, there is uncertainty in translating the lessons derived from scenarios developed at one scale—say, global—to the assessment of responses at other scales—say, sub-national. Third, scenarios often have hidden and hard-to-articulate assumptions. Fourth, environmental scenarios have tended to more effectively incorporate state-of-the-art natural science modeling than social science modeling.
Historically, most responses addressing ecosystem services have concentrated on the short-term benefits from increasing the productivity of provisioning services (RWG). Far less emphasis has been placed on managing regulating, cultural, and supporting ecosystem services; on management goals related to poverty alleviation and equitable distribution of benefits from ecosystem services; and on the long-term consequences of ecosystem change on the provision of services. As a result, the current management regime falls far short of the potential for meeting human needs and conserving ecosystems.
Effective management of ecosystems requires coordinated responses at multiple scales (SG9; R17.ES). Responses that are successful at a small scale are often less successful at higher levels due to constraints in legal frameworks and government institutions that prevent their success. In addition, there appear to be limits to scaling up, not only because of these higher-level constraints, but also because interventions at a local level often address only direct drivers of change rather than indirect or underlying ones. For example, a local project to improve livelihoods of communities surrounding a protected area in order to reduce pressure on it, if successful, may increase migration into buffer zones, thereby adding to pressures. Cross-scale responses may be more effective at addressing the higher-level constraints and leakage problems and simultaneously tackling regional and national as well as local-level drivers of change. Examples of successful cross-scale responses include some co-management approaches to natural resource management in fisheries and forestry and multistakeholder policy processes (R15-ES).
Active adaptive management can be a particularly valuable tool for reducing uncertainty about ecosystem management decisions (R17.4.5). The term “active” adaptive management is used here to emphasize the key characteristic of the original concept (which is frequently and inappropriately used to mean “learning by doing”): the design of management programs to test hypotheses about how components of an ecosystem function and interact and to thereby reduce uncertainty about the system more rapidly than would otherwise occur. Under an adaptive management approach, for example, a fisheries manager might intentionally set harvest levels either lower or higher than the “best estimate” in order to gain information more rapidly about the shape of the yield curve for the fishery. Given the high levels of uncertainty surrounding coupled socioecological systems, the use of active adaptive management is often warranted.