Conventional environmental management planning approaches are decreasingly likely to meet their intended goals under conditions of rapid ecological or social change (Berkes et al. 2003, Kay 2008, Chapin et al. 2009, Kofinas 2009). Linked social-ecological systems (SESs; Berkes et al. 1998) are characterized by feedbacks and complex, unpredictable phenomena, often thwarting the effective use of linear projections based on current trends (Wollenberg et al. 2000, Carpenter 2002, Peterson et al. 2003a). Creative processes for anticipating change, such as scenario planning, have been proposed as useful alternatives to conventional planning approaches that fail when confronted with surprise (Wollenberg et al. 2000, Alcamo et al. 2005).
Scenarios can take many different forms, depending on the chosen approach (Wollenberg et al. 2000, Alcamo and Henrichs 2008). An important limitation to quantitative scenarios is that mathematical models can only capture a portion of the complex interactions of driving forces inherent in an SES (Alcamo et al. 2005, Alcamo 2008). Quantified scenarios based on mathematical models can be good for simulating well-understood systems over sufficiently short times. However, exclusively quantitative scenarios are typically a poor representation of complex SESs (Swart et al. 2004).
Participatory, qualitative approaches that involve local stakeholders can result in detailed, imaginative, and wide-ranging scenarios (Reed et al. 2013). Involving people to develop scenarios can bring forth more ideas of possible futures that come from outside of the decision-making or management framework (Schoemaker 1995). This helps to address the core problem with decision making of a narrow paradigmatic lens, aiding people to see decisions without the weight of habituated goals and pressures (Chermack 2004). The involvement of stakeholders in the creation of scenarios can improve decision making (Palomo et al. 2011), because decisions identified and developed by local stakeholders are more likely to be consistent with local priorities, norms, and institutions (Chapin et al. 2006, Walz et al. 2007, Reed et al. 2013).
The purpose of our research was to assess the efficacy and utility of scenario planning by using it to identify wildlife management goals in a rapidly changing social-ecological system. Scenario planning is promoted in the social-ecological systems literature as a planning and decision-making tool when dealing with uncertainty in dynamic SESs (Walker et al. 2002, 2004, Peterson et al. 2003a, Folke 2006, Peterson 2007). We add to the emerging SES literature that appraises the method in practice (e.g., Peterson et al. 2003b, Bohensky et al. 2006, González et al. 2008, Gibon et al. 2010, Palomo et al. 2011, Malinga et al. 2013, Palacios-Agundez et al. 2013, Reed et al. 2013). However, ours is the first study to use scenario planning for wildlife management goal development.
Our study area, the southwest Yukon Territory, Canada, offers ideal prospects for applying scenario planning within a systems-thinking framework. This region has a long history of profound social, economic, and ecological changes that continue (e.g., Slocombe 2001, Cruikshank 2005). Of greatest significance here is the appearance of newly introduced or reintroduced species on the landscape. Within the past 50 years, wood bison (Bison bison athabascae)were reintroduced and elk (Cervus canadensis) were introduced into the territory. Mule deer (Odocoileus hemionus) are increasingly moving northward from British Columbia. The southwest Yukon also has a history of well-established resource comanagement regimes, underpinned by settled Aboriginal land claims (Clark and Slocombe 2009). Further, local stakeholders clearly see the need for resource management institutions to have high adaptive capacity (Ogden and Innes 2009).
Scenario planning in environmental management
Scenario planning considers multiple plausible futures with uncontrollable variables and high uncertainties. It links past and present events with hypothetical courses that examine the relationships of driving forces. It has a goal of creating more robust planning for events that may be unpredictable (Peterson et al. 2003a, Ralston and Wilson 2006, Weeks et al. 2011). It shifts the analytical focus of estimating what is most likely to occur, which is common of predictions or forecasting, toward questions of what are the consequences and most appropriate responses under different circumstances (Duinker and Greig 2007). Scenarios can spur action in the face of uncertainty by using realistic narratives to bring alternative possibilities to life (Carpenter 2002).
The adaptation of scenario planning to conservation and management is fairly recent (Peterson et al. 2003a). It has gained traction as a tool to visualize future climate change and sustainable development implications. Climate scenarios, for example, represent possible future climates developed to determine the impacts of climate change (Beaumont et al. 2008). Many studies discuss possible species’ distributions under different climate scenarios based on global climate models (see Fuller et al. 2008, Jensen et al. 2008, Maiorano et al. 2011, Rose and Burton 2011). Other studies have been used to help engage local stakeholders to envision how climate change might impact their communities (see Sheppard et al. 2011). Several global environmental assessment exercises have included a scenario component to help visualize future environmental challenges (see IPCC 2000, UNEP 2007 and MEA 2005).
Effective scenarios should be developed within a systems thinking framework (Chermack et al. 2001) where interacting forces are examined and not just trends and uncertainties (Schoemaker 1995). The focus on the relationships of driving forces is significant because small, persistent forces can alter species interactions, destabilize communities, and drive major biome shifts (Parmesan and Yohe 2003). Once the interactions between forces are highlighted, participants can develop a broader understanding of the SES and how management might build resilience of the system. A scenario planning process can help decision makers visualize plausible future stability domains for a given SES and develop policies to direct the SES to a desired future scenario. By utilizing knowledge about the local SES function from stakeholders who live in the study area, scenarios can capture change in specific functions of the SES (Kok et al. 2004, Gibon et al. 2010). Conceptualizing different futures can help wildlife managers recognize changes, make decisions, and adjust policies to shift the system toward a future that accomplishes a range of management objectives (Peterson et al. 2003a, Weeks et al. 2011).
Originally the study was intended to focus exclusively on wood bison, and all members of the Yukon Wood Bison Technical Team were invited to the first workshop. During that workshop participants suggested and agreed to incorporate elk and mule deer into the study. Members of the Yukon Elk Management Planning Team were thus invited to participate in the subsequent workshops. There is no committee responsible for mule deer management. Those two planning teams comprise representatives from Environment Yukon, Environment Canada, affected First Nations, and affected Renewable Resources Councils. They also receive input and have representatives from interest groups such as the Yukon Agriculture Association, the Yukon Fish and Game Association, and the Yukon Outfitters Association. Demographic and professional characteristics of study participants are described in Table 1.
We followed the process described by Ralston and Wilson (2006) to guide scenario development, adapted to fit our particular context (Beach 2014). Scenario planning typically occurs over a series of workshops, which are common venues in northern North America for communicative and collaborative processes (Huntington et al. 2002). Ralston and Wilson (2006) recommend a project that has three workshops of 2-3 days each, with a scenario team of 8-12 participants, and spans 3-4 months (Ralston and Wilson 2006). Three workshops were conducted in Haines Junction, Yukon Territory over a 13-month period. Workshop 1 had nine participants and lasted one day in January 2012, focusing on identifying drivers of change. Workshop 2 lasted two days in April 2012 and nine participants attended, developing the scenario narratives. Two participants from the first workshop did not attend the second workshop, but two participants joined who were not present at the first workshop. Workshop 3 happened over a single day in February 2013 and had six participants, considering and examining possible management responses to the scenarios. Seven participants who had attended previous workshops failed to attend the third workshop. Two individuals who had attended no previous workshops attended the third workshop.
Workshops were facilitated by the second author, whose professional and research relationships in the region predated this study by 12 years. Flip charts were used to record main ideas of conversation threads and to facilitate specific steps of the scenario development process. Workshops were audio recorded to capture all participant input. We used these recordings to evaluate and include input when writing the scenarios. The recordings also helped us reattach context to participant input, such as the tone of voice. Audio was especially helpful for triangulating between workshop discussion, field notes, and flip charts.
Within the area of interest participants defined the specific study area as bounded by Haines Junction, Whitehorse, Carmacks, and Kluane Lake (Fig. 1). This area roughly coincides with the Aishihik Wood Bison Herd range as well as Champagne & Aishihik First Nations’ traditional territory. The study site is characterized as an interior dry forest dominated by white spruce with aspen and willow. It is within the Ruby Ranges ecoregion within the boreal cordillera ecozone (Smith et al. 2004). Participants selected 20 years (2032) as a temporal reference point because it is approximately a generation, and bison have been on the landscape for about that amount of time. Visually representing themes and local conditions enhances people’s ability to visualize different futures, allowing people to more readily think about the implications of a given scenario (Ralston and Wilson 2006, Vervoort et al. 2010, Sheppard et al. 2011). Consequently, we hired a Yukon-based graphic artist to create a set of four computer-generated images (one for each scenario), each representing main themes and important drivers (Fig. 2).
Two surveys were completed by participants, one after the second workshop and one after the third workshop. These surveys asked questions about perceptions of scenario planning as a tool to develop wildlife management goals. Because the number of completed surveys was small (n = 8 for survey 1 and n = 6 for survey 2), survey data was amalgamated, and coded and analyzed by hand. Researchers also kept field notes during workshops. These notes included important participant commentary, further research ideas, emerging themes, and tone of participant interactions. All methods used were approved by the University of Saskatchewan’s Behavioral Research Ethics Board, and this research was carried out under the authority of annually issued Yukon Scientists and Explorers Act Licenses.
The scenario team identified 46 drivers of change and then grouped these into three distinct axes of uncertainty (Table 2). Eighteen drivers were grouped into a “Changing Ecological-Social Interactions” axis. Twenty drivers were grouped into a “Land Use” axis. Eight drivers were grouped into “The Human Factor” axis. Once axes were selected, participants identified the logics for the axes: the two polar directions an axis could manifest in the future. The “Changing Ecological-Social Interactions” axis had logics of “unpredictable change” and “gradual change.” The “Land Use” axis had logics of “high cumulative impacts” and “low cumulative impacts.” Finally, the “The Human Factor” axis had logics of “Exploitative” and “Stewardship.”
Grouping the various axis logics together yielded eight possible scenario logics, though not all of the paired scenarios logics were plausible. For example, a scenario in which there are high cumulative impacts from land use, but human values reflecting a stewardship ethic seems contradictory. For this reason, participants deemed such contradictory combinations of scenario logics unlikely and so discarded them, leaving four viable scenarios.
The scenario team developed four alternate visions of the future southwest Yukon SES. Full scenario narratives are presented in Appendix 1. Scenario 1 (Doom and Gloom) features status quo management actions, resulting in low native ungulate populations and moderate new ungulate populations. Scenario 2 (Slow Boil) features high unintended consequences from managers being slow to react, resulting in low native ungulate populations and low new ungulate populations. Scenario 3 (A Confused State) features high unintended consequences from poorly planned management actions, resulting in low native ungulate populations but high new ungulate populations. Scenario 4 (Win-win) features carefully planned management actions, resulting in low-moderate native ungulate populations and moderate new ungulate populations.
Surveys revealed that scenario planning helped participants to think about how drivers interact, what uncertainty exists, and how to craft contextually appropriate management goals. All participants who completed survey 2 (n = 6) believed that they learned something from the scenario planning process that will be valuable to them as a manager, will be able to use outcomes from this process, and could see themselves using scenario planning in the future. These survey respondents agreed that scenario planning is a method that could help people with different perspectives collaborate and discuss issues. Survey 1 (n = 8) respondents agreed that the scenario planning process helped them understand other stakeholders’ points of view.
Participants described scenario planning as a method that enabled broad thinking and made sharing perspectives easier. They also suggested ways to improve the process and clarified the useful scope for scenario planning endeavors. We learned a number of practical lessons during this project, and we present these with the intent of informing future scenario planning efforts elsewhere. A concise summary of these lessons, especially for practitioners and managers, is presented in Box 1.
Participants described how the holistic, ecosystem approach that considered species, human needs and values, and development helped them to visualize the effects of nonecological components of the SES on wildlife. When the thinking was centered on how interactions between drivers form causal relationships, participants were able to visualize potential threats that had not been previously discussed in southwest Yukon wildlife management circles. For example, scenario 2 revealed a value shift due to loss of wildlife. People showed less respect for the land because they had less opportunity to access and connect with it through hunting. Of survey 2 respondents, 83% agreed that scenario planning helped them understand future uncertainty. One participant said it “reinforced how events may dramatically alter management goals.” Perhaps the most significant awareness that rose through the scenario planning process was potential unintended consequences of using management to “close the door” on one or more of the new species. Limiting the population growth of mule deer, for example, could induce cultural food insecurity in a future where other ungulate populations suffer. Systems thinking changes the goal from seeking knowledge of parts of the system to improving understanding of the dynamics of the whole system (Folke et al. 2005). Participants valued how the scenario planning process encouraged and required broad thinking, describing it as “different,” “integrative,” and “long-term.” All participants agreed that the long-term nature of thinking in scenario planning is valuable and something generally missing from conventional wildlife management planning.
The collaborative aspects of the process enhanced people’s ability to think broadly. Participants viewed collaborative discussion as helpful while identifying drivers of change, thinking about driver interaction, and during visualization of future scenarios. One participant said, “Brainstorming during planning allowed us to think about interactions.” By discussing these elements in groups after periods of independent thinking, scenario team members were able to draw from each other’s perspectives and experience. This sequenced discussion served to expand creativity while constraining implausible notions of the future. As one participant put it, “we got to sort it out together and come to a common understanding.” This reaffirms suggestions that scenario planning helps generate a shared vision of the future or a shared mental model (Peterson et al. 2003a, Chermack 2004, Palomo et al. 2011).
Having diverse and extensive experience related to the decision focus further helped the scenario team think broadly. Specifically, extensive experience and a wide range of participant ages apparently helped the group identify a wide range of drivers of change (Table 2). One participant said being a renewable resource manager and dealing with individual drivers of change on a daily basis helped identify drivers. Another mentioned that working with communities and environmental assessments helped identify drivers. Such comments show how participatory scenario planning can help local stakeholders collectively think holistically about an SES. The points of view and experience of others helped participants “to visualize decades of cumulative effects of population growth and resource projects.” This shows that participatory scenario planning can help stakeholders understand how drivers might interact to form causal relationships.
Giving voice to diverse perspectives is a goal of scenario planning (Peterson et al. 2003a). These might include economic, social, or cultural perspectives. Having more values or perspectives present could make consensus harder to reach at various points of the scenario planning process. Conversely, having a wide variety of values and perspectives can help to identify more possibilities of how the system might change in the future (Kok et al. 2007, Reed et al. 2013). In this study, having both First Nation and nonaboriginal cultural perspectives influenced the conversation about how to group drivers of change into axes of uncertainty. For example, one First Nation participant argued for the inclusion of several socially oriented drivers in what was a predominantly ecologically oriented axis of change. The participant explained this was necessary because humans are part of nature and some social drivers, such as “hunter patterns,” are intimately tied to natural drivers, such as “moose.” That one conversation helped other participants think holistically about the SES, enabling them to learn from each other and broaden their perspectives; a finding similar to Priess and Hauck (2014).
Overcoming cross-cultural misunderstanding is an enduring challenge for natural resource comanagement in the Yukon Territory (Nadasdy 2003, Natcher et al. 2005, Natcher and Davis 2007, Clark and Slocombe 2009). A scenario planning approach appears to be able to help First Nation and nonaboriginal resource managers generate shared understanding by improving both parties’ understanding of each other’s perspectives. In this study, all survey respondents agreed that scenario planning is a method that could help people with different perspectives collaborate and discuss issues. Similarly, 88% of survey respondents agreed that the scenario planning process helped to understand points of view of other stakeholders. These two findings indicate that scenario planning holds promise for clarifying and securing common ground between stakeholders with differing perspectives and values. For one participant, this was a “strength of the approach.”
Some authors argue that scenario planning has an outcome of identifying “robust” strategies that can be applied across a range of future conditions (Ralston and Wilson 2006, Carvalho et al. 2011, Caves et al. 2013). Robust, or “no regrets” strategies were identified in past Yukon forest management workshops looking at different climate futures in the region. They were considered robust strategies because they could work under multiple possible climate futures (Ogden and Innes 2009). We found that in a wildlife management context participants were reluctant to sort wildlife management goals in this manner. Participants were very clear that they preferred to keep goals fixed in the contexts of individual scenarios; the reason being that management needs would be different in those different futures.
To further illustrate this point, five of the seven identified goal clusters (Beach 2014) could be applied across multiple scenarios. However, different management recommendations were made to achieve the goals under the varying contexts of the scenarios. For example, it is a goal to keep new species at socially tolerable, harvestable levels in all four scenarios. However, the individual steps to maintain wood bison populations would be different in scenario 3, where disease is prevalent in the population, than in scenario 1 where the population is disease-free. The social tolerance for wood bison could be much lower in a scenario where the herd was diseased. As such, corresponding management needs would likely be different. Consequently, it appears important not to lose the aspects of a clustered goal that root it to the conditions of a specific scenario.
It is worth noting that in the southwest Yukon species-specific technical teams write the species management plans and a renewable resource council is mandated as the key institution of public government involved in environmental management within a corresponding First Nation traditional territory. Our goals were set at the regional level by participants representing the technical teams and renewable resource councils governing the wood bison and elk ranges.
Another point to highlight is the importance of context. The narrative format of the scenarios helps create a hypothetical situation that may remove participants’ personal investment compared with day-to-day situations. One participant said, “being part of the story makes it less provocative,” while another added that “I don’t feel like I’m being personally attacked.” Discussing issues through story could ease the tension surrounding familiar issues. For example, when participants discussed a potential coal power plant there was less weight attached because it was a hypothetical (though plausible) project. There were few or no past conversations, impact assessments, or heated debates surrounding it. This may contribute to why all participants felt that scenario planning could be a helpful method for stakeholders with diverse perspectives and values to discuss complex and/or contentious issues, a finding shared by Caves et al. (2013).
Despite the need to link goals explicitly with specific scenario contexts, study participants observed that within those contexts, scenarios could be relevant for managing resources beyond wildlife. Participants found scenario planning helpful to set priorities for wildlife management, raise awareness of potential threats, identify future monitoring and resource needs, examine long-term repercussions of management actions, stimulate the sharing of perspectives, and build capacity. Participants also felt that scenario planning could be particularly useful in generating a wildlife management plan, a species recovery document, a land-use plan, or when conducting risk or resilience assessments. It was mentioned, in retrospect, that the Yukon Wood Bison Management Plan (2012) could have benefitted from a scenario planning process.
Participants also saw potential value in applying the scenarios when considering management for other species and/or resources within the same system. This is an important finding. Scenario narratives describe several versions of the future system with a focus on a particular element. However, groups interested in focusing the scenarios on a different element, say wolves or coniferous forests rather than new ungulates, could use the “bones” of the scenarios because they were built considering the system holistically. The causal relationships considered during the original scenario development process will still apply. They would simply need to be refocused to address how the resulting events could affect the newly emphasized element.
Latency posed a problem. Significant time between workshops led participants to forget the meaning and context behind drivers of change. Participants also had difficulty remembering fine details of the scenarios by the time they were discussed. This could be avoided by keeping to the recommended timetable of 3-4 months (Ralston and Wilson 2006), with roughly 1 month between each workshop. This puts significant demands on the scenario narrative writer, but reinforces the scenario team members’ memory of workshop events and context.
As studies have noted elsewhere, it is important to ensure enough time is given for all scenario planning steps to unfold (Kok et al. 2007, Walz et al. 2007). In this process, participants felt that there needed to be more time to develop and discuss management goals. Furthermore, because the third workshop was only a single day there was no time left to develop indicators. As a result, this planning process was missing an aspect fundamental to operationalizing the resulting management goals.
Continuity of workshop participants was also a problem. Because this was a voluntary study, participants were not obligated to attend. Coordinating a time when all participants were available was challenging, and several participants did not attend all three workshops. Some apparently lost interest after the first workshop, whereas other new participants became interested as they heard about the project, so came to subsequent workshops. Participants who attended only the final workshop were missing context from the previous workshops and at times seemed to have trouble adjusting to the group’s thinking.
Ideally, participants will commit to all workshops if possible, ensuring continuity of the participants and the perspectives represented. More robust management goals may be possible from a scenario team that understands the context from the entire scenario development process. Workshops done within an institution with employees whose attendance was part of their regular work likely would not experience the same problem.
Throughout the scenario planning process, there were points where participants felt unsure of how the sum of the parts would add up to the whole, or what the whole even was. At those times clarification was required. This indicates the importance of explaining the full extent of the process to participants at the beginning, and being prepared to remind participants of it. It was evident that knowing how each step of the process worked toward the ultimate goal helped participants perform each step and stay engaged.
For example, the process of ranking drivers caused confusion. Multiple participants perceived issues with scale, feeling that some drivers could be nested within other drivers. Mining exploration and production, for example, both fit within the larger driver of natural resource demand. By ranking one as higher impact than the others, would they necessarily reduce the importance of the others that are related? Grouping similar drivers prior to ranking the drivers could reduce confusion of scale when ranking. Similarly, when asked to identify drivers of change, some participants wanted clarification about what the drivers were to be used for, or how general or specific the drivers should be. Seeing examples from other scenario planning workshops was helpful in those instances.
A related problem was that at times participants found themselves working with a different set of definitions. People’s interpretations of words differed, likely because of varying cultural or professional understandings. A particular issue was how to define the word “uncertainty” with reference to the drivers of change. Some participants took it to mean uncertainty of occurrence, while others thought it to mean uncertainty of impact. This may well have introduced variation in how participants ranked drivers.
Because this scenario process was rooted in SES theory, the researchers constantly referred to “the entire system.” What exactly was entailed in “the entire system” gave participants trouble. For some, thinking in this way was problematic. These participants had trouble combining aspects of the human economy and environmental interactions into the same thought. Others already had an operationalized understanding of what it means for an environment to also contain human social and economic interactions. This difference in understanding necessitated extended discussions about how to group drivers and discuss how drivers might interact into the future. This also reinforced the benefit from scenario planning of challenging people to understand each other’s perspectives and values.
The following insights were gained by the researchers outside of the scenario workshops, but from observations made during the workshops. Our results are consistent with the case many have made that scenario planning provides resource managers with a method to operationalize theories about managing dynamic social-ecological systems.
A process that generates knowledge and experience of ecosystem dynamics improves the social capacity of responding to environmental change (Folke et al. 2005). This becomes true when the generated learning is expressed in management practice (Folke et al. 2005). Keeping the above two points in mind, this study suggests that scenario planning is a process that fosters adaptive learning. In resource management, adaptive learning “provides the means for coping with uncertainty and change in a social-ecological environment” (Kofinas 2009:96). Kofinas (2009) claims that adaptive learning occurs when one or more groups does the following:
Engaged resource managers should be continually undertaking the first of these activities. Taking resource managers through the scenario planning process helped them to engage in the remaining three. Specifically, identifying drivers of change and axes of uncertainty parallels activity 2. Thinking about how drivers and axes interact to form future scenarios as well as examining threats and opportunities parallels the first part of activity 3 (evaluate emergent conditions). Discussing possible management options parallels the second part of activity 3 (evaluate options for action). Last, developing management goals, monitoring needs, and identifying signposts that indicate the need for management action lays essential groundwork for activity 4.
Scenario planning can likely further enhance the adaptiveness of a management regime by providing a forum for single-loop, double-loop, and triple-loop learning (Argyris and Schön 1974, 1978, Keen et al. 2005). Each of these learning mechanisms involves cyclical, experiential learning in which practitioners reflect on the results of past actions. Single-loop learning permits the organization to continue its present policies or achieve its present objectives (Argyris and Schön 1974). Importantly, individuals do not question the fundamental goals (double-loop) and design of the organization (triple-loop; Argyris and Schön 1974). In a resource management context, single-loop learning refers to adjusting actions to meet previously identified management goals (Kofinas 2009). For example, participants in this study engaged in single-loop learning by recommending opening bison hunting to subsistence harvesting. Managers looked at population levels being high and suggested increasing the harvest by adding wood bison to the list of subsistence species for First Nations. The goal of harvesting bison remained intact.
Double-loop learning involves the modification of an organization’s policies or objectives (Argyris and Schön 1978). Within natural resource management, practitioners reflect on consequences of past management actions before taking further actions (Kofinas 2009). The feature that distinguishes single-loop learning from double-loop learning is that double-loop learning calls into question basic assumptions and goals. Study participants engaged with double-loop learning when they reflected under each scenario whether or not to prioritize management of culturally sensitive species. They looked at shifting management goals to ensure new species remain at socially acceptable levels. Scenario planning helped participants think about whether existing management goals would be appropriate under different conditions.
Triple-loop, or transformative, learning, challenges the institutional assumptions upon which single-loop and double-loop learning are based (Keen et al. 2005). It involves a reevaluation of models and approaches as in double-loop learning, but adds a consideration of whether the alteration of norms or goals might require a paradigm shift in governance (Keen et al. 2005, Folke et al. 2009). It is the difference between changing a goal, such as prioritizing management of culturally sensitive species, and changing the process by which a goal is developed. Participants in this study engaged with triple-loop learning by questioning the efficacy of the current processes available to them for planning wildlife management goals. Through reflecting, participants saw value in a holistic, long-term approach to developing management goals. This spurred them to recommend that longer term planning approaches, such as scenario planning, be conducted prior to developing management goals. Implementing a parallel planning process would shift the current planning paradigm for wildlife management away from single-species foci and short-term time horizons toward longer term, holistic thinking.
Developing management goals through the scenario planning process simultaneously takes managers through iterations of an adaptive learning cycle. Within a scenario planning process managers can devise plans to adjust actions, or develop entirely new approaches to meet goals based on new assumptions. With the right decision focus, a scenario team can even investigate a change in governance paradigms.
Successful adaptive comanagement depends on social networks between individuals, groups, and organizations that allow for multidirectional information flows (Gadgil et al. 2003, Olsson et al. 2004, 2006, Folke et al. 2005, Armitage et al. 2007, Kofinas 2009). The success of such networks relies on the collaboration of a diverse set of stakeholders operating at a range of scales. Sharing of management power and responsibility may involve multiple institutional linkages between organizations (Folke et al. 2005).
Our findings suggest that scenario planning provides mechanisms to build, or to strengthen, institutional linkages. Of all survey respondents, 88% agreed that scenario planning helped them understand points of view of other stakeholders. All respondents to the second survey agreed that scenario planning could help people with different perspectives collaborate and discuss issues. By helping organizations to build trust and discuss shared mental models of plausible futures, scenario planning can further contribute to the success of adaptive comanagement (Peterson 2007). Our scenario planning process evidently facilitated multidirectional informational flows between all represented organizations, a finding shared by Stringer et al. (2006). However, we did not examine the potential impact of improving informational flows, which, to be conclusive, would have required longer term structured follow-up.
Scenario planning processes can empower local participants by communicating social-ecological change with high salience (Sheppard et al. 2011, Reed et al. 2013), encouraging the actual use of outputs that have been cogenerated (Kok et al. 2007, Walz et al. 2007), and encouraging flexible participation (Stringer et al. 2006). Our participants found it provided a forum where everyone in attendance could equally provide input and feedback. Such interaction can potentially empower groups that may believe their perspectives are underrepresented under current governance models.
Scenario planning processes can accept input from a wide range of knowledge systems, thereby enhancing linkages between organizations possessing different ways of knowing. Input from multiple, especially local knowledge, systems is an important way to deepen researcher understanding of system dynamics and add validity to localized scenarios (Walz et al. 2007). Modern science is a well-organized system for expanding the world’s knowledge. However, it lacks the wealth of detailed, context-specific observations of the dynamics of complex ecological systems that can be found in some local knowledge (Gadgil et al. 2003). In fact, many local resource users of the world possess, as parts of their knowledge systems, site-specific knowledge of how to respond to disturbance and build adaptive capacity to changes (Berkes and Folke 2002, Chapin et al. 2009). Local knowledge systems offer important insights, and is why environmental governance needs collaboration among diverse stakeholders (Plummer and Armitage 2010). Qualitative, participatory scenario planning workshops provide a forum to share these insights.
This application-oriented study has locally specific yet broadly relevant findings. We learned that scenario planning is a method that can successfully develop wildlife management goals. It helped local and regional resource managers better understand local SES dynamics and uncertainty. It prompted them to consider potential impacts of various wildlife management goals on SES dynamics, and vice versa. To improve the process, we offer some key findings from our experience. Scenario practitioners should insist on commitment from participants, because continuity improves understanding of process context. Time between workshops should be minimized and workshops should be given sufficient time to accomplish all steps of the scenario planning process. Following these recommendations should improve the robustness and usefulness of scenario outputs.
We also demonstrate that participatory scenario planning can be used as a foundational process toward SES-based management goals. Undertaking this thought process can help wildlife managers articulate goals with a deeper understanding of a goal’s implications to the rest of the SES. Identifying system drivers and future-oriented goals can lead to proactive management, rather than, as one participant put it, just reacting to a squeaky wheel that needs grease. Planning more holistically and improving interorganizational information flows and relationships were two observed outcomes seen by participants as likely to lead to more adaptive, effective wildlife management. For these reasons, participants felt that instilling a culture where these types of processes preceded conventional planning would be extremely useful in the Yukon. Such institutional challenges are hardly limited to wildlife management either, as participants noted. Our findings thus have broad relevance to professional practice in natural resource and environmental management, especially as the shortcomings of top-down expert-driven “scientific management” in the face of rapid change spur experimentation with new forms of adaptive governance for social-ecological systems (Brunner et al. 2005, Folke et al. 2005).
A series of people and institutions helped to make this article possible. Special thanks to the workshop participants for taking four grueling days from their busy lives to talk to us, and think hard. Specifically, we thank the Alsek Renewable Resource Council, Carmacks Renewable Resource Council, Champagne & Aishihik First Nations, Environment Canada, Parks Canada, Ta’an Kwäch’än Council, Yukon Territorial Government, Yukon Fish and Wildlife Management Board, and Yukon Fish and Game Association for sending members to one or more workshops. We thank Tanya Handley for producing the scenario graphics. This study was financially supported by the Social Science and Humanities Research Council of Canada and the University of Saskatchewan.
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