Emerging Concepts in Adaptive Management

Social- ecological system features



Emphasizes that the two parts (human systems and environmental/biophysical systems) are only arbitrarily separable and equally important, and that they function as a coupled, interdependent, and co-evolutionary system (e.g., human actions affect biophysical systems, biophysical factors affect human well-being, and humans in turn respond to these factors) (Berkes 2011)

Recognizes the role of humans in shaping ecosystem processes and dynamics thus valuing their capacity to influence and be influenced by ecological outcomes (Dale et al. 2000, Waltner-Toews and Kay 2005)


Coupled systems exhibit nonlinear dynamics, thresholds, surprises, legacy effects and time lags (Liu et al. 2007)

Extent and nature of coupling varies spatially, temporally and organizationally (Liu et al. 2007)

Coupled systems have multiple drivers, an array of impacts, unpredictable ways in which drivers act, and multiple feedback interaction between human and biophysical systems (Nayak 2011)

Interconnections and cross-scale dynamics among the social-ecological attributes become important factors that define the nature and extent of system complexity

Nestedness and sub-systems

Complex systems have a structural architecture characterized by hierarchical organization and interactions that take place between these nested systems (Simon 1962, Levin 1999)

Focusing on sub-systems as distinct parts of the larger social-ecological system aids the development of understanding them, because they are valued as integral to each other, bound as a coupled system (Turner et al. 2003, Glaser 2006, Kotchen and Young 2007)


Observed dynamics and behavior of ecosystems and social-ecological systems are the result of the interplay of structures and processes that vary spatially and temporally (Levin 1999, Gunderson and Holling 2002, Cash et al. 2006)

Allows us to think about complex multi-scale processes within the social-ecological system and determine appropriate scales of intervention for adaptive management

Orienting adaptive management theory and practice around the main features of social-ecological systems has a number of implications, such as: (1) reinforcing the philosophical foundations of adaptive management which are to embrace uncertainty and complexity (Holling 1978, Berkes 2003); (2) appreciating the resource context as a complex adaptive system that involves multi-directional flows between people and their environments (Kates et al. 2001, Berkes 2003, 2011, Mahon et al. 2008, Levin and Clark 2010); (3) recognizing connections among adaptive management of natural resources and the livelihood, food security and social wellbeing concerns of people and communities (Chuenpagdee et al. 2005, MEA 2005, Weeratunge et al. 2014); and (4) illustrating that decision making arrangements must reflect how the social domain (e.g., distribution of power) intersects with the ecological through multiple feedback processes (Berkes 2010, Nayak and Berkes 2010).

A social-ecological perspective compels adaptive management practitioners and researchers to look beyond theoretical, methodological and disciplinary boundaries to offer an overarching framework—an inclusive lens—to study social-ecological systems. Finally, by bringing the social context into a conventionally resource-focused approach, a social-ecological system lens helps to highlight the conflicts and distributive justice challenges of adaptive management, along with impacts on livelihoods and potential for inequity and problems of participation in decision-making processes (Berkes et al. 2006, Liu et al. 2007, Nayak and Berkes 2014). We address several of these emergent challenges in subsequent sections below.

Situating Adaptive Management in a Governance Context

Management and governance are neither synonymous, nor mutually exclusive. Management typically involves the operational decisions taken to achieve specific outcomes (e.g., increases in yield of a desired resource stock). Governance often refers to the broader processes and institutions through which societies make decisions that affect the environment (see Oakerson 1992). Biermann et al. (2009) define governance as “the interrelated and increasingly integrated system of formal and informal rules, rule-making systems, and actor-networks at all levels of human society (from local to global) that are set up to steer societies toward preventing, mitigating, and adapting to global and local environmental change.” In this context, institutions are the formal and informal “working rules” and associated decisions (e.g., for monitoring and enforcement) that mediate interactions among people and their environments (Ostrom 1990). We use governance to refer to both an analytical lens to examine the broader set of rules and actor networks within which adaptive management actions and decisions take place, as well as specific arrangements for adaptive decision making about natural resources among government agencies, industry and resource user groups (see Armitage et al. 2012).

Gunderson and Light (2006) suggested that thinking in terms of adaptive governance can help “increase responsiveness and generate more diverse and versatile competencies that create options for the future and develop the adaptive capacity to improvise and adjust to recurring crises.” This makes good sense given the social-ecological complexities of most natural resource management settings. However, working towards such a goal inevitably requires managers and other actors in an adaptive management process to consider more thoroughly the social and institutional constraints within which they operate, reflect on levels of power and authority among the actors involved in adaptive management, bridge diverse knowledge systems, and build adaptive capacity to support more fundamental transformations in how societies interact with natural resources. As Gunderson and Light (2006) noted, “adaptive governance deals with the complex human interactions that have been obstacles to the implementation of adaptive management,” which include institutional constraints and contested and divergent values, goals, and objectives between actors.

Situating adaptive management in a governance context generates a number of useful insights for managers and resource users (Box 1). For example, government agencies with the mandate for adaptive management cannot be the only source of decision making, although they have a crucial role to play in that regard. As more actors (industry, user groups, civil society organizations) enter the adaptive management arena, different types and sources of knowledge will gain legitimacy. Indeed, our current understanding of social-ecological systems is incomplete and multiple types of knowledge are necessary to inform decisions (Brunner et al. 2005, Folke et al. 2005). A governance perspective (see Garmestani et al. 2009) helps managers to recognize the legitimacy of diverse and sometimes peripheral actors with new roles in resource and ecosystem management, and helps convey a “multi-objective reality when handling conflicts among diverse stakeholders” (Folke et al. 2005).

Box 1: Implications of a Governance Lens for Scientists and Managers

Consider emergent actors with new roles in resource and ecosystem management

State agencies are no longer the main actor or sole source of decision-making. Hybrid arrangements involving state and non-state actors have emerged, offering alternative and promising models, but have also created new challenges associated with accountability, legitimacy and scale.

Recognize that adaptive management occurs in contested and power-laden social contexts

Power underlies all adaptive management processes, and influences how trade-offs between multiple, competing objectives are made. Acknowledging and understanding the role of power encourages reflection on and recognition of the contested and divergent assumptions, values and goals amongst actors involved in decision-making.

Appreciate the need for engaging and bridging diverse knowledge systems for learning

Scientific knowledge of complex social-ecological systems is often incomplete, creating pitfalls when relying on it as the exclusive source of information for decision-making. Knowledge that is co-produced by bridging diverse sources and types is typically better suited for navigating complexity and uncertainty (Berkes 2009).

Embrace the challenge of adaptation

Adaptation to maintain or preserve existing features of social-ecological systems is necessary to address environmental change. Capacity to meet the challenge of adaptation is crucial, as is the need to recognize maladaptive practices and consider more fundamental system transformations. In light of ongoing processes of change in social-ecological systems, expectations of adaptive management need to be continually refined.

A governance lens may also encourage adaptive managers to reflect on the multiple domains (social, economic, ecological) in which their problems are nested (see Westley 2002, Garmestani et al. 2009). In other words, a governance perspective can facilitate an integrative or social-ecological view (as above), rather than a traditional regulatory or sectoral view. Similarly, a governance lens highlights the social structures and processes (i.e., networks) that link individuals, organizations, agencies, and institutions in a multi-level world (Olsson et al. 2004). Since actors interact vertically and horizontally within such networks, strong network arrangements are hypothesized to enhance the capacity for adaptive management by facilitating processes of learning and building legitimacy of decision outcomes (Armitage et al. 2012). However, such networked and/or multi-level arrangements also have disadvantages. They may require more time for decisions to be made, and exacerbate political, economic or livelihood conflict if not carefully facilitated. A governance lens thus highlights the need to strengthen capacity to manage adaptively across scales, but also to recognize that any management process is bounded by broader political, economic and institutional conditions that will ultimately define transitions towards sustainability .

Surfacing Power in Adaptive Management

The emergence of hybrid governance arrangements emphasizes a transition from the single state/agency actors in resolving management challenges, to network strategies involving combinations of actors from states, the private sector, and civil society (Lemos and Agrawal 2006). As the preceding discussion on governance highlights, adaptive managers are increasingly engaged with a broad array of actors outside formal (i.e., government) spheres that seek to influence the management of natural resources (Ansell and Gash 2008, Ali-Khan and Mulvihill 2008). Any decision regarding natural resources is inherently influenced by social relations of power (Bryant 1998, Brechin et al. 2003, Ansell and Gash 2008). Adaptive management processes are required to more effectively consider questions about actor inclusion (i.e., who participates in hypothesis generation, knowledge production, data analysis?), as well as questions about influence, the legitimacy of actor participation, and the distribution of power among actors (i.e., how effectively do different actors participate in various phases of adaptive management?).

We define power here as the application of action, knowledge and resources to resolve problems and further interests (Adger et al. 2005, Raik et al. 2008), and we identify four related arenas through which to consider power in adaptive management: (1) decision-making; (2) authority and control; (3) action; and (4) knowledge. These categories are not exclusive, and some social actors may span multiple categories (Table 13.2).

Table 13.2
Arenas of power in adaptive management

Arenas of power


Roles and responsibilities




The power to meaningfully influence decisions

Participant, negotiator, discussant, persuader, advisor, consultant, communicator

Engagement of actors (e.g., tourism, government, NGO, community etc.) via a multi-stakeholder Management Advisory Board in Bunaken National Park, Indonesia (Erdman et al. 2004)

Mannigel 2008, Ferse et al. 2010

Authority and control

The power to coerce or constrain human action

Rule maker, decision maker, enforcement

Devolution of Brazil’s water sector to local multi-stakeholder river basin councils generates varied levels of authority across states (Engle et al. 2011). Ongoing decentralization reforms across sub-Saharan Africa are transferring decision-making powers to local governments and organizations in the context of natural resource management (Ribot 2003)

Agrawal and Ribot 1999, Njaya et al. 2011, Campbell et al. 2013


The power to execute

Implementer, monitor, adjudicator

Local enforcers (kewang) and traditional local leaders play a vital role in the functioning of customary sasi marine management systems in eastern Indonesia (Harkes 1998, Satria and Adhuri 2010)

Mappatoba 2004


The power to gather, learn, possess, and exclude knowledge

Knowledge holder, knowledge broker, knowledge (co)producer

Multi-stakeholder riparian management in the Sprucedale National Forest, southwestern USA results in competing discourses where differential power amongst actors is used to select knowledge sources and influence decision making (Arnold et al. 2012)

Natcher 2005, Nadasdy 2007, McGregor 2012

In adaptive management, a failure to address or consider differences in power among actors can have far-reaching implications for the legitimacy of decisions about natural resources (Borrini-Feyerabend et al. 2007, Larson and Soto 2008, Biermann and Gupta 2011). The differences in power among actors may be linked to capacity limitations (e.g., financial, technical), which may contribute to uneven representation in terms of the issues addressed and the interests considered (e.g., Stringer et al. 2006, Kallis et al. 2009). However, structurally embedded constraints related to institutions (e.g., rights, rules) and the marginalization of certain groups are more likely to be a foundational reason for uneven distribution of power among participants in an adaptive management process. In either case, unequal distributions of power may lead to poor social, and ultimately ecological, outcomes (Lebel et al. 2005, Nadasdy 2007).

Explicit recognition of structural and agent-based dimensions of power and their interactions (see Raik et al. 2008) can prove crucial to successful adaptive management, particularly given the increasingly hybrid, networked and multi-level decision making arenas within which adaptive managers are situated. The sharing of authority and control among diverse actors is increasingly encouraged as an approach to management of a wide range of natural resources (Borrini-Feyerabend et al. 2007), and manifests in many ways, such as in the form of government-indigenous partnerships, community agreements on conservation, or collaborative management arrangements more generally (Press et al. 1995, Mappatoba 2004, Fox et al. 2008). In these contexts, the focus is less on active adaptive management, and more on the social process of learning by doing , monitoring and collaborative decision making in response to the uneven distribution of power among communities, conservation organizations and government agencies (Salafsky et al. 2001).

Knowledge Co-production in Principle and Practice

Knowledge systems are defined as interconnected symbols that create meaning about reality that humans co-construct and adapt over time (Dryzek 2005, Reid et al. 2006). Knowledge systems thus reflect a knowledge-practice-belief complex (Berkes 2012), where meaning emerges from actors co-constructing symbols, artifacts, competencies, and norms to enact ‘what we know’ and ‘how we know it’ (Midgley 2000). It is crucial for actors in adaptive management to recognize that knowledge is as much a social process (i.e., governance) as it is a set of outcomes (e.g., management plans).

Undertaking how to bridge knowledge systems in adaptive management is an area still in need of significant effort. Where efforts to bridge knowledge systems have been meaningfully attempted, they have often occurred in the context of collaborative and deliberative processes (Berkes and Davidson-Hunt 2008). Knowledge co-production can be defined as “the collaborative process of bringing a plurality of knowledge sources and types together to address a defined problem and build an integrated or systems-oriented understanding of that problem” (Armitage et al. 2011). Such processes encourage managers and other actors to: (1) examine different narratives of (or stories about) environmental change and uncertainty (Batterbury 1997, Dietz et al. 2003); (2) enhance their overall capacity to understand and accept uncertainty (Reidlinger and Berkes 2001); (3) allow actors to formulate shared visions to guide decision making (Peterson 2007); and (4) encourage a shift away from knowledge integration towards knowledge exchange (Fazey et al. 2013). A knowledge co-production approach seeks to maintain the integrity of participating knowledge systems and knowledge holders, while creating space for the development of novel and hybrid understandings needed to learn through uncertainty. This is a hallmark of adaptive management.

Evidence shows that bridging diverse knowledge systems improves the overall understanding of environmental phenomena among different groups (Reidlinger and Berkes 2001, Reid et al. 2006), and enhances the perceived salience, credibility and legitimacy of adaptive management (Cash et al. 2003, Mitchell et al. 2006, Reid et al. 2006). Knowledge of different types and from different sources (scientific, local, traditional) can improve the quality of decisions (Reid et al. 2006, Reed et al. 2013). For example, Laidler (2006) illustrates how Inuit and scientific knowledge holders use very different processes to understand and act upon changes in Arctic sea ice. Scientists use satellite imagery or local instruments to measure and verify changes with the aid of statistical modeling, whereas Inuit use their observations gained during hunting or other land-based practices and verify changes by sharing and discussing their experiences with other community members (Laidler 2006, Laidler et al. 2010

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