Research

INTRODUCTION

Contemporary polycentric water governance networks appear incapable of effectively addressing present water issues (Bahadur and Tanner 2014, Bodin et al. 2016, Enqvist and Ziervogel 2019, Nohrstedt and Bodin 2020). We know today that power issues substantially affect polycentric governance networks (Armitage et al. 2009, Plummer et al. 2014, Schultz et al. 2018, Morrison et al. 2019), especially collaborative and social learning processes (Ansell and Gash 2007, Armitage et al. 2007, Reed 2008, Brisbois et al. 2019, Johannessen et al. 2019). Despite this awareness, we lack a detailed understanding on how collaboration and social learning in polycentric governance networks are impacted by power. For the purpose of this study, power or power dynamics denote the broad spectrum of visible, hidden, and invisible dynamics that directly or indirectly shape governance processes and outcomes (adapted from Lukes 2005). Given the global water crises, there is an urgent need to improve knowledge about how power dynamics affect polycentric governance (Biggs et al. 2012, Karpouzoglou et al. 2016, Morrison et al. 2019), particularly collaborative and social learning, which are advocated to improve governance and achieve more effective outcomes (Bahadur and Tanner 2014).

Polycentricity describes governance networks that consist of multiple decision-making bodies that share responsibilities for the resource in question. Governance is thought to become more effective and efficient through vertical and horizontal coordination of different decision-making bodies (Pahl-Wostl and Knieper 2023). However, polycentricity often exists as hybrid form, entangled and in co-existence with mono-centric governance structures (Galaz et al. 2012, Cumming et al. 2017, Lubell et al. 2017, Morrison et al. 2019). Research supports the claim that polycentric characteristics enable greater flexibility, innovative potential, and adaptive capacity in governance networks (Morrison et al. 2019), which in turn foster collaboration and social learning among stakeholder groups (Ostrom 2005, Blomquist 2009, Pahl-Wostl 2009, Carlisle and Gruby 2019). However, polycentric characteristics can also create disadvantages for resources governance, when, for example, overlapping responsibility causes inefficiency or inaction.

Collaboration and social learning are crucial deliberative processes in water governance and beyond because they can enable collective decision making and conflict resolution by promoting equity, fairness, inclusion, and trust building (Dietz et al. 2003, Keen and Mahanty 2006, Reed 2008, Emerson et al. 2011, Brisbois and de Loë 2016). Collaboration between stakeholders supports multiway interactions (Ross et al. 2002, Innes and Booher 2004, Rowe and Frewer 2005) that are situated in a diverse stakeholder network where power and authority are fragmented and decision making takes formal as well as informal avenues (Innes and Booher 2004, Morrison et al. 2023). Collaboration in polycentric governance networks means that a range of stakeholders work together in all phases of the decision-making process, from the development of collective goals and solutions to action planning and prioritization as well as monitoring and revaluation (Koontz 2006). The process is often motivated by a shared vision or a conflict that requires resolution (Koontz 2006, Levesque et al. 2017) and theoretically features shared responsibilities and power (Huitema et al. 2009). In practice, the success and effectiveness of collaboration is influenced by underlying power dynamics that underpin the process and its ability to promote equity, fairness, inclusion, and trust building (Dietz et al. 2003, Emerson et al. 2011, Brisbois and de Loë 2016). This can leave stakeholders in polycentric systems unable to resolve conflict and/or build consensus on appropriate management solutions and consequently, impacts upon the quality of governance solutions (Bodin et al. 2016, Bodin 2017).

Social learning is the other deliberative process that is fostered by polycentric governance networks and ought to improve decision making in the water sector (Mostert et al. 2007). Social learning encourages interaction and relationship building between stakeholders and consequently helps to unlock social capital (Borgatti et al. 2009, Pfefferbaum et al. 2017, Crow and Albright 2019), which is the foundation for a well-connected and functioning multi-stakeholder governance network (Brondizio et al. 2009). We define social learning as an interaction-based group learning process that results in a changing comprehension of the topic or problem of interest (Milbrath 1989, McAllister and Makkai 1992, Reed et al. 2010). Hence, learning plays a significant role in governance that seeks transformative change and enhances social-ecological resilience. Sharing experiences and creating space for experiments and diverse knowledge frames are critical elements of social learning as they allow the strengthening of adaptive capacity in water governance (Folke et al. 2005, Pahl-Wostl 2009, Biggs et al. 2012, Bodin, 2017, Gober 2018, Webb et al. 2018, Pahl-Wostl 2020). Despite the benefits that social learning offers to water governance, there is also evidence about destructive social learning (Moghimi Benhangi et al. 2020). If the learning process is based upon unsustainable values or policies, it is likely to produce undesirable water outcomes (e.g., water overuse; Moghimi Benhangi et al. 2020, Wyborn et al. 2023). Research also shows that, for example, knowledge and language use, political and institutional context, ground rules or resource access all influence and potentially impede social learning processes and their outcomes (Keen and Mahanty 2006, Mostert et al. 2007). Social learning processes are therefore subject to dynamics (hereafter referred to as power dynamics) that impact their effectiveness and outcomes. Identifying the nature of these power dynamics is key to improving water governance processes and enabling more reliable achievement of desired outcomes, like enhanced social-ecological resilience.

We set out to address the power gap by analyzing how multi-dimensional power dynamics influence collaboration and social learning in catchment-scale water governance, and how that affects governance outcomes. In this context we consider process-related outcomes such as the relationship between stakeholders, trust, conflict, or its resolution as well as stakeholder support for the approach taken. Following the social-ecological systems theory on collaboration and social learning as processes that strengthen social-ecological resilience, we refer here to outcomes as collaboration and social learning outcomes, such as stakeholder relationships, social capital, trust, and adaptive capacity (Lewicki and Brinsfield 2009, Biggs et al. 2012, Chaffin et al. 2014, Pahl-Wostl and Knieper 2014, Galan et al. 2023). We follow Brisbois and de Loë (2016) and Brisbois et al. (2019) who applied Lukes’ (2005) three-dimensional power theory to study the power dynamics that underpin collaborative governance approaches. Our research focused on the Lockyer catchment planning (LCAP) process in Queensland, Australia. This article is part of a larger research project that used a multi-method approach to power analysis by combining discourse analysis (McIlwain et al. 2022), social network analysis (McIlwain et al. 2023), and thematic analysis of interview data. In this article we present the results from the interview analysis, which allowed deep insight into the instrumental, structural, and the discursive dimensions of power that have shaped collaboration and social learning in an exemplar polycentric governance process.

THEORETICAL BACKGROUND

Tangible, hidden, or invisible, power dynamics underpin every decision made. Power dynamics are pervasive and play a critical role in water governance as they influence the decision making in complex and multi-dimensional fashion. In this study, we understand power dynamics broadly as all “forces” that affect the decision making in water governance processes. We describe power as multi-dimensional because we differentiate between the instrumental dimension of power, the structural dimension of power, and the discursive dimension of power (Lukes 2021).

Instrumental power

Instrumental power is an agent-based concept that stems from pluralist philosophy (Dahl 1957, Merelman 1968). Here, power is exercised by individuals or groups using certain strategies or instruments that could be labelled “tangible.” The agent might employ strategies such as misinformation, manipulation, or coercion, which are indicative for power dynamics (Brisbois and de Loë 2016). The instrumental power dynamics that were relevant in this study are discussed below (see also Table 1 for reference). Human resources can be considered instrumental power as knowledgeable staff or time capacities allow a stakeholder group to engage in collaboration, voice concerns and views, and learn from others. Responsibility and accountability can also indicate instrumental power because responsibility is the control over a certain thing or the duty of care that one or multiple stakeholders have in regard to the resource in question. Closely linked this factor is accountability. This means that a specific stakeholder organization is liable if, for example, certain actions are not performed, or water-related issues intensify. Official (mandated) responsibility and accountability (when in place) is therefore a powerful tool to drive stakeholder action and project implementation. Stakeholder groups are represented by human agents, which means that their relationships are laden with feelings, like trust or distrust. Creating trust is a strategy to convince the other of ideas or plans and makes agreement more likely as suspicion is lowered. However, distrust can provoke the opposite, leading to competitive strategies instead (e.g., competition around leadership or financial resources).

Structural power

The structural dimension of power looks at the ways in which agents attempt to navigate and avoid conflict and therefore is relatively “hidden.” Lukes’s model builds here on Bachrach and Baratz’s concept “the two faces of power” (1962). The focus is on inaction and non-decision making that is structurally manifested by, for example, inclusion or exclusion of stakeholder groups, agenda setting, or knowledge use and production (Brisbois and de Loë 2016). In the following we theoretically ground the structural power dynamics that were relevant to this study (see also Table 1). The control over certain stages of the governance process provides stakeholders with structural power as inaction and non-decision making can be easily exercised by, for example, controlling agenda setting, goal setting, knowledge use, and knowledge production. Stakeholder inclusion and exclusion is another effective strategy to navigate conflict because groups with opposing views could be excluded or their participation could be made difficult.

This strategy is often reserved for individuals or groups who instigated collaboration or conduct process facilitation, placing them in positions with increased structural power. Other strategies to influence the governance process is by leveraging the transparency and plurality around knowledge and knowledge use as well as enabling or disabling face-to-face deliberation. More obvious signs of structural power are mandate and legal authority or decision-making power (that is not mandated). Politics also incorporates structural power dynamics as a long-established political course or voter concerns can direct the decision-making of politicians. Closely linked to that is also the bias toward capitalism, which underpins the economic system and with that directs governance decision toward low-cost options and profitability.

Discursive power

The discursive dimension of power is not based on an agent-based power understanding; instead, it understands power as the ability to shape people’s thinking and influence their desires to avoid conflicts entirely. Following Marx (as cited in Lukes 2021) and Foucault (1980), this power concept is focused on the context that individuals are socialized in and the knowledge and beliefs that prevail within those spaces. The socio-historical context and its dominant knowledge(s) are considered to shape people’s behavior (Lukes 2005, Haugaard 2008), deeming this dimension of power as “invisible.” Discursive power dynamics are, for example, dominant themes or values, efforts to control discourse, or groups being favored (or not) by the dominant discourse (Brisbois and de Loë 2016). Indicators that reveal discursive power dynamics and were relevant to this study are developed below (also see Table 1). Problem definition and framing are based on the narratives and beliefs that individuals (and organizations) hold, which deems them a useful indicator for discursive power. Dominant and hegemonic themes and values give insight into the context that individuals are socialized in and, with that, reveals the knowledge and beliefs that characteristically exist in this context. Dominant narratives serve the interests of some individuals or groups and do not support the interests of other individuals or groups. Hence, understanding who is or is not favored by the dominant discourse provides an indication of the operations of discursive power. Last, efforts to control the discourse (an indicator that could also be attributed to the structural dimension of power because control involves structural agent power) are a way to suppress narratives that do not serve one’s purpose. Simultaneously, controlling the discourse also allows some individuals or groups to tailor the dominant narrative to support their own intentions and goals.

The instrumental, structural, and discursive power dimensions are also intertwined, as dynamics of one dimension may influence the dynamics of another dimension. This adds great complexity to the way in which power dynamics affect decision making in governance processes. Hence, decisions result from the complex interplay between multi-dimensional power dynamics. Consequently, understanding power dynamics that underpin governance processes, such as collaboration and social learning, is a pre-requisite to explaining governance outcomes.

METHODOLOGY

To comprehensively investigate the power dynamics that have shaped the collaboration and learning among stakeholder groups requires a theoretical frame that captures multiple dimensions of power. For this reason, we applied the three-dimensional power model of Lukes (2005), which differentiates between instrumental power, structural power, and discursive power as detailed in the introduction. The suitability of Lukes’ (2005) power theory for the investigation of collaboration in water governance has been demonstrated by Brisbois and de Loë (2016) and Brisbois et al. (2019), who compiled an indicator set for each power dimension (2016) and applied it to examine the influence of the natural resource industry to collaborative governance processes (2019). We build on their work by expanding the indicator suite for collaboration after review of the relevant literature and empirical based indicator development (Table 1). Furthermore, we extend the focus from collaboration only, to add social learning, aiming to further elucidate their power-related interrelationships (Table 1).

Case study

For the investigation of power dynamics that underpin collaboration and social learning, we focused on catchment-scale water governance in Queensland, Australia, because it is subject to a polycentric system. To exemplify a case in which coordination and cooperation across geopolitical scales is required, we selected a catchment that stretches across multiple local government areas. Additionally, a suitable case had to illustrate shared management responsibilities between diverse stakeholders, so collaboration becomes requisite to safeguard catchment health. We identified the Lockyer Valley in South East Queensland (SEQ) as a suitable catchment and focused on the governance process that developed the Lockyer Valley Catchment Action Plan (LCAP) 2016 as part of the regional Resilient Rivers Initiative (RRI; SEQ Council of Mayors 2015). The initiative emerged from the destructive floods in 2011 and 2013, which showcased climate change impacts on the region’s water security. The RRI listed four regional goals that provided direction for the individual catchment plans. In short, these goals were to (1) reduce erosion; (2) protect water security; (3) strengthen climate resilience; and (4) encourage partnerships and leadership for coordinated catchment management (SEQ Council of Mayors 2015).

The collaborating stakeholder groups for the LCAP included local and state governments, (water) industry and natural resource management (NRM) groups. A key initiating group was the Council of Mayors, comprising the mayors of the 11 local governments in South East Queensland. Four of these local governments were involved in the development of the LCAP: Lockyer Valley Regional Council (jurisdiction over largest share of catchment), Ipswich City Council, Somerset Regional Council, and Brisbane City Council. The participating state authorities were the Department of Natural Resources and Mines^[1] (DNRM) and the Department of Environment and Heritage Protection^[1] (DEHP). The water sector was represented by Seqwater as the regional bulk water authority, and Unitywater and Queensland Urban Utilities as water suppliers. SEQ Catchments and Healthy Waterways were the Natural Resource Management (NRM) groups that amalgamated in 2016 to become Healthy Land and Water. The LCAP states that it was developed in a “collaborative process,” which highlights its suitability for this investigation.

Data collection

Case-specific data for the thematic analysis was collected through 25 semi-structured interviews (~45 minutes long). We interviewed key informants from stakeholder groups that were (1) directly involved in the LCAP process; (2) marginally involved; or (3) not involved at all. As directly involved we denote groups that have been identified as collaborators in the LCAP document. The coordinating group provided a list with names and contacts of individuals that had been directly involved in the process and for most organizations at least two people were involved (executive level and project level). We aimed to interview one representative for each group and in four instances we interviewed two representatives of the same group following the recommendations of other interviewees. In total, 15 representatives (n = 15) of 11 directly involved organizations (Council of Mayors, Lockyer Valley Regional Council, Somerset Regional Council, Ipswich Regional Council, Seqwater, DRNM, DEHP, Queensland Urban Utilities, Unitywater, Healthy Waterways, SEQ Catchments) engaged in our project. Additionally, we conducted 10 interviews (n = 10) with representatives of marginally/non-involved groups. Marginally involved refers to one representative (n = 1) of the water users group that had been invited to the public engagement workshops that were part of the participation process. The contact originated from a previous research project and connected us with other individuals from the water users and farming community. Non-involved refers to local farmers (n = 4), citizen groups (n = 2; e.g., local natural resource management groups), one catchment officer (n = 1), one hydrologist (n = 1), and one wetlands specialist from the DEHP (n = 1) who all had not participated in the LCAP process nor the public engagement workshops. Citizen groups were identified through an online search. The catchment officer, hydrologist, and wetland specialist were individuals who were recommended by other interviewees. Consequently, catchment experts were among the directly involved group and the marginally/non-involved group. Engaging with Elders of the Yuggera and Ugarapul peoples as Traditional Owners of the Lockyer area remained unsuccessful and hence, their views are not represented in this project. All interviews with the directly involved group and with two catchment experts were held via Zoom and video recorded. Interviews with the marginally/non-involved group and with one catchment expert were held in person and audio recorded.

To tailor the questions to the interviewee’s level of involvement, we worked with two distinct interview guides. For the officially involved groups, we inquired about the relationship to the area and the LCAP process more specifically. For example, we asked about the initiation process, motivation to engage, key concerns, topics of conflict, potentially missing groups or topics, and the suitability of plan to address key goals. For marginally/non-involved groups, we asked about their relationship to the catchment, their perception about the LCAP (process), general catchment issues of concern, and views and concerns specific to climate change, contentious topics in catchment planning and the relationship to other stakeholder groups. The interview guides are provided in Appendix 1. The listed questions in Appendix 1 show that we refrained from asking direct questions on power. Power dynamics are a very sensitive field of inquiry and given this sensitivity, direct questions have a higher risk of producing non-authentic responses, especially in a work-related context. This is why we used subtle questions, to ensure greater authenticity and reliability of participant responses. Subtle means we embedded power indicators like control over agenda setting and problem definition into the questions to inquire about power dynamics. For example, question 4 asked: Who set the agenda and what were the most pressing problems identified? Given the depth of the resulting data, our subtle questioning approach satisfied its purpose. Furthermore, the interview content was so rich that additional (non-specifically asked indicators) could be identified in the analytical phase.

Methods

In this paper, we present only a sub-set of the 89 power indicators that were used to study power dynamics in the scope of this whole project. A list of all 89 power indicators and their coding frequencies is attached in Appendix 2). The sub-set allows for an in-depth illustration of the ways in which certain power dynamics affect collaboration and social learning. The indicators for this sub-set were selected based on high coding frequencies, but also their influence on collaboration and social learning (e.g., racism was perceived by very few of the interviewees and hence, coded very few times. Yet, this perceived racism led to the decision to exclude Traditional Owners and had therefore, a strong impact on the stakeholder diversity.) The 10 most often coded indicators are presented in Table 2.

We used NVivo software to thematically analyze the interview data and worked with a descriptive coding strategy that combined deductive and inductive codes (Saldaña 2014). Deductive codes were derived from existing literature as presented in Table 1 in the theoretical background section. This was complemented by an inductive coding process in which we allowed new codes to emerge from the interview data (Saldaña 2014). Table 3 shows the inductively generated indicators, provides a description for each indicator, and shows whether indicators were relevant to collaboration and/or social learning. The coding process was undertaken by a single coder, which bears greater risk for interpretation bias.

The new indicators are explained below and their relation to the three dimensions of power (Lukes 2021) is explained. Instrumental power became apparent through agent characteristics. Personality traits were influential in group discussions and decision making because individuals with charisma, for example, can use it as a tool to convince others. Linked to that is self-perception (the beliefs that someone has about themselves), which determines individual behavior and relation to others. Individuals with high self-esteem can present their viewpoints and goals with more confidence compared to individuals that are unable to stand their ground because of low self-esteem. Respect can also be used as a tool to influence the other. By treating the other with respect despite differences, benevolence and trust can be instilled. The opposite of that is to sabotage an instrument that generates benefits through weakening the contender, a strategy that likely entrenches conflict. Involving independent experts is a strategy to base the decision making on expert advice. Simultaneously, the act of influencing such independence is a strategy to tailor outcomes to one’s advantage. Agent’s interests can determine their willingness and openness to engage with others.

The structural power indicators that emerged from the data are, for example, inaction and non-decision making, especially silencing groups by ignoring their feedback or silencing certain topics. These are powerful ways to justify inaction and prevent or delay decision making on certain issues. Other indicators for structural power dynamics were control over priority setting and control over solution setting. As elaborated in the section on deductive codes, control over certain process phases gives structural power to the controlling group. Along with that was also the need for groups to maintain their autonomy over financial resources they invest. Balancing science with political interests is also an indication of structural power as political interests are prioritized over scientific facts and advice leading to biased decision making.

The discursive power indicators that were inductively generated were confirmation bias, momentum, and racism. Confirmation bias is a feature of discursive power because it describes subconscious tendencies to absorb information that confirms the beliefs and values that an individual or group already holds. The momentum that a project generates is an example of discursive power dynamics because it is often linked to discourses that dominate at a particular time and space (e.g., flood related destruction in 2013 demanded political action, which created the resilient rivers initiative and momentum for its specific funding model). Racism was also identified as a new indicator for discursive power because racism builds on a belief and value system that regards people as unequal based upon their ethnicity. Evidence for the following three indicators emerged solely from the context and interrelated interview content and hence, was not directly coded in the transcripts: (1) dominant and hegemonic themes and values, (2) efforts to control discourse, and (3) who is or is not favored by dominant discourse. After the coding process was completed, we recorded all information that indicated barriers to collaboration and social learning and grouped them thematically in a mind map.

RESULTS

Four main themes emerged from the mind mapping exercise, namely facilitation, leadership, finance, and politics. The leadership and finance themes had underlying trust issues in common, which is why these were combined. As result, we arrived at three main power themes: (1) power of facilitation, (2) power of trust, and (3) power of politics. Because these three themes appeared to be central to collaboration and social learning and key power indicators revolved around them, we call these themes power hubs. Power hub is a new term that describes a central theme that links to and encompasses a certain subset of power dynamics. Power hubs are themselves shaped by a multitude of instrumental, structural, and discursive power dynamics (Tables 1 and 3) that are interlinked and mutually influencing as we elaborate below.

Power of facilitation

The facilitation of the LCAP encompassed the coordination of the decision-making process that led to the plan, and therefore, involves the initiation on the executive level, the management of project group (activities) and related expert committees, as well as the engagement process of the public. In the Lockyer example, the public engagement process was facilitated by the local government, and the LCAP development process was mainly coordinated by the Council of Mayors. We found a large variety of power elements that shaped the collaboration and social learning related to the facilitation of the governance process (Fig. 1).

The interviews revealed that control over goal setting and agenda setting largely dictated the direction that individual catchment action plans were supposed to take. Goals were pre-determined by the initiating groups, representing their key interests and perspectives on catchment needs.

I think by the time we got in, the goals ... for all the Catchment Action Plans had been set in stone in a process prior to us being involved. ... We knew that in targeting the nutrients, we were also going to target sediment. ... [So we] still ticked their box but their focus was more land use management, like changing farming techniques and site management, where our focus was in stream bank erosion. (Participant 1, directly involved group)

The pre-determination of goals foreclosed an open discussion (face-to-face deliberation) on catchment issues and related goals based on the plurality of stakeholder knowledge(s). Additionally, we found that early goal setting can lead to (premature) solution setting, i.e., when goals already indicate the cause of any given issue. For example, the RRI identified “Keep soil on our land and out of our waterways to support agricultural productivity and improve water quality” (SEQ Council of Mayors 2015:5), indicating that topsoil erosion is a key erosion source. However, the discussions and the engagement with scientific reports around erosion in the Lockyer Valley revealed that large amounts of sediments are released through riverbank and in-stream erosion (Croke et al. 2013, Olley et al. 2013, Thompson and Croke 2013, Thompson et al. 2013, Coates-Marnane et al. 2016). The pre-determined goal to address topsoil erosion created frustrations with some stakeholders because they felt that decisions were not made based on all available data, hence, potentially discounting root causes and producing weak solutions. The interviews indicate that this has been one strong point of contention between the initiating groups (directly involved group) and the NRM groups (directly involved group), which was not resolved within the scope of the governance process.

In terms of instrumental power, we found evidence that limited human resources influenced the independence of the collaborative process. For example, the technical advisory committee consisted of representatives who also participated at the executive and/or project level. This lack of expert independence in combination with existing mistrust between certain stakeholders led largely to the omission of respective expert advice. Inviting expert advice affords the opportunity of learning from the expertise of others, an opportunity that was missed by decision makers. The interviews revealed that decision makers considered the scientific advice too narrowly focused on catchment health. Here we observed how different stakeholder values affected the learning process.

Next to the instrumental and structural power dynamics, we also identified discursive power influencing the process facilitation. Our data shows efforts by the instigating groups to control the discourse around erosion sources by, for example, pre-determining the goal and the root cause of erosion in the initiating phase, before all stakeholder groups were involved (as detailed earlier). Thus, we observed how the values (e.g., agricultural/ economic productivity) and knowledge (e.g., knowledge around topsoil erosion) of the groups involved in process initiation and facilitation strongly influenced the dominant themes, problem definitions, and representations (e.g., topsoil erosion reduces water quality). Simultaneously, this shows how dominating values and knowledge in a governance process suppress other values (e.g., ecosystem health) and alternative knowledge (e.g., knowledge around in-stream erosion) if inclusion and diversity are not actively facilitated in the collaboration and social learning processes. This also links to confirmation bias, which is the tendency to believe information that aligns with one’s existing values and world views. Confirmation bias prevents the openness to alternative values, views, and ideas and hence, we would describe it as a common barrier to learning in collaborative processes.

Power of trust

For the purpose of this study, trust refers to the strong belief that another group is reliable, truthful, and will not deliberately cause harm to the trusting organization nor obstruct the joint collaboration. The analysis identified a range of instrumental, structural, and discursive power dynamics that have shaped the learning and collaborative processes related to trust (Fig. 2).

In the Lockyer case, trust issues appear to be largely linked to competition around leadership. The learning and collaborative processes were strongly influenced by trust issues between government organizations and NRM bodies. These trust issues appear to have had multiple reasons. First, until the start of the RRI, catchment management was considered the responsibility of NRM bodies (though without formal mandate or authority). The political urgency to address river sedimentation and water security issues after the destructive floods of 2011 and 2013 led local governments to take charge by establishing a new governance model (i.e., the RRI). In interviews, local government representatives explained the need at the time to set up a coordinated approach to catchment actions and investments because of the scale of the issues and their social-ecological complexity. This change in leadership affronted the NRM bodies, who previously held this responsibility and purpose, instilling distrust.

We also found that non-involved landowners distrust the local governments’ management plans and capacity to address wide-spread catchment issues effectively. Farmers were mostly concerned about the siltation of the watercourses, whereas conservationist landholders mentioned the weed management in the riparian zone as an urgent issue.

Second, mistrust also stemmed from financial issues. At the time, NRM bodies were perceived by government organizations to be financially incapable to realize the needed scope of actions. With the amalgamation of the two NRM bodies into a company limited by guarantee in 2016, this perception changed. The new business structure of the main NRM body in the region evoked distrust from local governments, fearing this NRM body could be biased by business interests, which could compromise their judgement for priority works.

[It] muddies the water where the independence can be questioned given that there’s a party or business that relies on getting funding out of these programs. Whereas the [councilors are] not compromised on that. They are independent because it’s ... their ratepayers’ money. And that continues to be a challenge today. (Participant 2, directly involved group)

Local governments indicated they would like to hand over the responsibility of the RRI and its catchment plans to another body. However, a key concern is the accountability for spending public funds. One councilor noted that this concern could be resolved if the NRM body (limited by guarantee) was to restructure into a statutory authority.

Organizational independence, questions of accountability, and bias of capitalism (Brisbois and de Loë 2016) suggest strong instrumental and structural power dynamics that characterize the disagreement and fuel the distrust between two major stakeholders. These power dynamics undermine the collaborative processes through the resulting lack of trust.

The data shows that such distrust also negatively affects the learning processes. For example, the NRM bodies indicated they perceived their input and expertise was not seriously considered or included. Additionally, NRM bodies criticized the lack of transparency around planning progress and details (i.e., a long time between progress reports and limited opportunities to provide feedback) as well as limited openness to consider different schools of thought to collectively discuss problem definitions. These instrumental, discursive, and structural dynamics negatively impacted the learning processes because discussions did not build on plurality of types of knowledge; problem definitions were not collectively developed, and expertise and experiences were excluded. This also affected the collaboration because certain groups felt hampered to authentically contribute and influence decision making, leading to skepticism about their involvement and further growing distrust toward leading groups and facilitators. Dissatisfaction about the process might also trigger reduced anticipation for the planning process to succeed (e.g., encouraging acts of sabotage) and prevents the feeling of ownership over the joint plan.

In addition, individuals from the marginally/non-involved group also expressed frustration and distrust toward the local and state government and its management capability.

It’s just meeting after meeting and we don’t get an outcome. [...] There’s always something that pulls us up short or funding gets cut or people lose interest. Things don’t happen quick enough for us. (Participant 9, marginally/non-involved group)

Participant 10 from the same group stated direct impact on his property due to the installation of unsuitable creek crossings. Queensland Main Roads, a state level agency, is responsible for the respective road. (Note, that this organization was not involved in the LCAP process.) “We had crops in there, and that’s all gone [...] due to the mismanagement [...] of the crossings.” (Participant 10, marginally/non-involved group)

In collaborative processes, respect has also been highlighted as an instrumental power dynamic that shapes collaborative success between stakeholders. Respecting the organizational needs without attempting to change them is a prerequisite for harmonious collaboration. This ties in with organizations’ endeavor for autonomy over their financial investments.

You can’t tell an organization what it spends its own budget on. [...] They won’t accept that if you do. They’d be cranky about it. [...] Either you got to find a new bucket [of money] or help [...] them to spend their money where they want to spend it. (Participant 4, directly involved group)

This highlights the importance of face-to-face deliberation about needs, goals, and intentions to learn about individual collaborators and meet their goals and motivations with respect.

Power of politics

Politics refers here to activities and circumstances relevant to stakeholders’ positioning and strength to assert their interests in the scope of the governance process relating to the LCAP. The analysis identified a large array of instrumental, structural, and discursive power dynamics that can be linked to politics and have influenced learning and collaboration during the plan development process (Fig. 3).

When considering the instrumental dimension of power that influenced the process, we found that personality traits were strong power elements that shaped the collaborative and learning processes. Personality traits play a major role in deciding who wins arguments or whose opinion is heard (as per the earlier example about the conflicting opinions about the erosion source). The representatives of organizations are humans with individual personality traits, some might be loud, extroverted, and intimidating and others might have shy and introverted natures with lesser degree of self-confidence, yet others might be rhetorically gifted and charismatic. Interviewees raised concerns about balanced input into discussions and the need for the facilitator to manage individual involvement to enable inclusive and equitable deliberation practice. The results also suggest that stakeholders’ interests play an important role in their willingness to collaborate and their openness to learn from others’ expertise, experience, and perspectives.

The structural power of mandate and legal authority and decision-making power held by local governments allowed these groups to enforce their interests in the “collaborative” process, in contrast with groups that lack official authority. Additionally, interview data confirmed that local government bodies perceived the need to “balance” scientific knowledge with the need to accommodate political interests.

[...] it’s a balance of scientific work and politics, and political views of things. And that was an interesting and important part of Resilient Rivers, it wasn’t just all about the science. [...] if it was all about the science, there would have been one part of Lockyer Creek that everything [all the funds] went into and everyone focused on that. But that wouldn’t have solved all the problems we need to solve, and that wouldn’t have washed over politically. We needed to spread the love a little bit, to be fair. (Participant 2, directly involved group)

For example, by defining topsoil erosion as root cause of watercourse sedimentation, the focus shifted to the farming community and the need to protect their agriculturally productive soils and subsequently the local agricultural economy. This dominant discourse marginalized other (scientific) types of knowledge that pointed to in-stream erosion as a key contributor to waterway sedimentation and hence, shifted the management focus away from riparian zones. The strong bias toward hillslopes and surface soil erosion was also described by one of the catchment experts.

Now the immediate issue that we ran into was that the farmers and landowners were particularly concerned about erosion of their topsoil, the hillslope erosion, so the surface erosion. That’s what they could see. [...] And the [research] that we’d done previously told us, well, that’s probably not the main source of the material that’s moving out of the catchment. So we did a number of studies that actually showed that it was channel bank and gully erosion that was the dominant source of sediment. [...] Erosion of the channel banks was a nuisance to them. But it wasn’t what was damaging their productivity on the farms. (Participant 7, marginally/non-involved group)

This also illustrates that business concerns drive the bias toward a specific problem definition and explains why it was in the political interest to define the erosion problem in a way that favored community values, and with that, we assume it followed public expectations. The catchment expert also highlighted the persistence of the dominant problem definition around erosion.

[...] it didn’t matter how many presentations we gave or how convincing the science was. It always swung back, because there was a social bias if you like from what they were observing on their own properties. They didn’t look so much at the rivers, they looked more at what was going on the farms and the properties. (Participant 7, marginally/ non-involved group)

This also exemplifies how fixed problem definitions also affect the willingness to reconsider assumptions and prevent the consideration of novel perspectives and management approaches to a given social-ecological issue. Consequently, fixed problem definitions and the dominant discourse are strong discursive power dynamics that influence the learning process by foreclosing open discussion and consensus building based on diverse evidence. Subsequently, this data shows that problem definitions highly influence the suite of solutions that might be deliberated and implemented. Additionally, the lack of open deliberation and consensus building around the problem definition excludes stakeholders with differing problem definitions (and linked solutions) from the process, affecting the inclusiveness of the collaborative process.

And I definitely got the feeling that they would have been happy to run with it without the input from [NRM bodies]. And that we were more there from an engagement point of view, that we could be said to have been included. (Participant 6, directly involved group)

This indicates that although inclusion is crucial to encourage collaboration, mere inclusion of groups in a governance process does not guarantee the inclusion of their input. Furthermore, dominant (political) discourses at a time may lead to silencing groups or issues. For example, climate change had been identified by multiple study participants as a taboo topic.

If I had gone to council and uttered the words “climate change,” honestly I don’t know, just the howls of the region would have been unbelievable. I mean, I don’t think there was a single councilor in our Council Chamber that accepted climate change and most certainly not the Mayor at that time. (Participant 6, directly involved group)

This silencing of controversial issues, like climate change, is also evident within NRM groups. Excluding discussions around climate change and its impacts on the catchment appears a diplomatic decision to avoid loss of memberships.

You just don’t discuss climate change with people other than those you know are on the same page as you. You can’t discuss it. We don’t go where we know we’ll alienate some members. [...] But we don’t make it a topic for the workshops or discussions because we don’t want to lose members. (Participant 8, marginally/non-involved group)

There is also evidence about the exclusion of groups because of fear that inclusion would hold up the process. Interview data revealed that a conscious decision was made to exclude Traditional Owners and other community groups from the engagement process to avoid process delays or loss of momentum. In regard to the participation of traditional owner groups, perceived institutional racism was named as a reason to side-step their inclusion.

It was never said out loud, I got a strong sense that if we had started talking about Aboriginal groups within the Valley and their input ... I don’t think that would have washed very well with the council [at the time]. ... I mean, there’s a residual level of racism in places like this. (Participant 8, directly involved group)

Latent racism and the fear thereof led to the exclusion of traditional knowledge, which directly impacts the social learning process as diverse perspectives are not welcomed, involved, nor valued. Although a comprehensive community engagement process was conducted, representatives of the water users’ group and conservationists did not hold a permanent seat at the LCAP meetings and discussions. Consequently, the knowledge diversity in the meetings did not represent the community adequately.

These findings suggest that instrumental, structural, and discursive power dynamics are interlinked, and in their complexity, have decisively shaped collaboration and social learning in this multi-stakeholder water governance process. Power dynamics that influenced the LCAP process were tangible, hidden, as well as invisible. The process did not lead to collective action, nor did it resolve tensions between two key stakeholder groups. Although the output was an ambitious plan, its implementation has been slow because of resource limitations, and its monitoring and revision appeared neglected.

DISCUSSION

The power dynamics that shaped collaboration and social learning during the LCAP, a water governance process, were diverse, interlinked, and multi-dimensional in nature. The most power dynamics became apparent in relation to the LCAP process and played out between the directly involved stakeholder groups. Excluded from direct involvement in the process were mainly three types of groups, industry (farmers/water users), Traditional Owners, and local NRM groups. Simultaneously, the findings indicate a greater disinterest among farmers (water users) to engage in catchment planning processes, which appears to be linked to distrust in the local government’s ability to address catchment issues. Catchment experts provided an external (to the LCAP process) perspective on the catchment specifics, which helped to better understand management challenges. Below we discuss the key points that emerged from our findings, with an emphasis on theoretical advancements of collaboration, social learning, and polycentric governance systems.

First, we found that many of the power indicators were equally suited to signify influence on collaboration as well as social learning. Even though derived from distinct literatures, most power indicators are indicative for collaboration and social learning at the same time, highlighting the strong interconnectedness of both processes. Although the linkages between collaboration and social learning are recognized in the social-ecological scholarship (Berkes 2009, Biggs et al. 2012, Plummer et al. 2017), we argue that there is need to revise existing theoretical frameworks to mark collaboration and social learning as intrinsically linked concepts, which affect each other through feedback-loops. When power dynamics affect collaboration, we simultaneously have seen an impact on social learning, and vice versa. For example, if a stakeholder group is excluded from collaboration, their knowledge is excluded from the discussion, affecting the social learning process. Likewise, if a group’s knowledge or input is not heard or used, the group becomes intellectually excluded from the collaborative process and/or feels excluded. These findings suggest the need for the conceptual development of collaboration and social learning into a concept that acknowledges their interplay.

Additionally, based on the results of our power analysis, we suggest that the substances that tie collaboration and social learning are “knowledge” and “trust.” This study shows that knowledge is used as a very effective structural gateway to influence collaboration and social learning processes in multi-stakeholder settings. The operation of power through knowledge has also been demonstrated by other water governance studies. For example, Wyborn and colleagues exemplify how “logics of administrative and techno-rationalism both produce and are re-produced by the power of federal and state governments” (2023) in Australian water reform. This means that formal authority underpins the knowledge that is applied to institutional processes while, simultaneously, reinstating the formal powers of federal and state governments. The strong link between power and knowledge is also reflected by our coding results. The indicators (1) control over knowledge use and production, and (2) transparency and plurality around knowledge use (includes who decides whose knowledge counts) were the two most frequently coded power indicators (Table 2). So, although we know that diverse knowledge greatly supports learning processes and its outcomes (Tengö et al. 2014), the ability to control knowledge use and production, and the level of transparency and plurality around knowledge use largely affect the quality of the social learning process and learning experience of individual stakeholders. However, not every stakeholder group has the same ability to control knowledge. The findings illustrate that the process facilitators are best positioned to influence knowledge use and production, transparency, and plurality to favor and develop a rationale that supports their interests. For example, this case study demonstrated how closely problem definitions and solution definitions are linked. The relationship between problem definition and solution definition has been highlighted by other scholars in the field (Bischoff-Mattson and Lynch 2016, Elrick-Barr and Smith 2021) and related disciplines, such as public policy (Marchildon 2016) and is a practice that largely influences outcomes from the onset. Another practice that decisively shapes outcomes is the manipulation of knowledge use and production by, for example, excluding specific input. An open, transparent, and inclusive social learning process can no longer take place. The negative consequences of manipulative behavior for authentic learning experiences and their implications for enhancing SE resilience have also been described by Thompson et al. (2013). Once affected groups notice that lack of transparency and plurality around knowledge use and realize that knowledge use and production have been manipulated, distrust arises, which likely affects their willingness to collaborate. With that we can pinpoint the control over knowledge use and production, and transparency and plurality around knowledge use as key structural power dynamics to have significant influence on the effectiveness of collaboration and social learning. Less effective collaboration and social learning processes have a reduced potential to grow social capital and adaptive capacity, key features for enhancing social-ecological resilience as desired outcome. Consequently, the power dynamics do not only influence the collaborative and social learning processes, but they also affect the outcomes by hampering the effectiveness of water governance outcomes.

Next to the manipulation of knowledge use, this study also found that competition over leadership and financial resources were critical sources of distrust, and negatively impacted collaboration and social learning. Trust is the human emotion that allows us to believe that the other has “good” intentions toward us (Stern and Coleman 2015), inviting openness, advice sharing (Gino and Schweitzer 2008), and a bond between groups through shared core interests (Levesque et al. 2017). These are all features that support social learning processes and can intensify collaboration (Muro and Jeffrey 2008, Levesque et al. 2017, Bartels and Furman 2023). In the Lockyer case, competition over leadership led to silencing competitor input on the one side, and reduced interest for the planning process to succeed on the other side. The competition over leadership of catchment-related water governance resulted from the severe impacts of the floods in 2011 and 2013, which directed attention to previous and seemingly ineffective catchment management. Next to the unsuccessful perceived catchment NRM management, we found that organizational independence, accountability issues, and bias of capitalism were reasons for distrust between local government and the main NRM body. Mistrust has multiple sources in this case and undermines the ability of these stakeholders to collaborate and learn with and from each other. Moreover, mistrust likely affects the entire process as other stakeholder groups have to navigate between the rivals. The negative impact of mistrust for collaboration and learning has been confirmed by others (Lachapelle and McCool 2012, Stern and Coleman 2015, Levesque et al. 2017). We know that trust strengthens stakeholder relationships and with that, helps to unlock social capital, a prerequisite for building resilience (Pahl-Wostl et al. 2007, Galan et al. 2023). Distrust reverses this causal chain, by weakening stakeholder relationships, eroding social capital (Lewicki and Brinsfield 2009), and decreasing the adaptive capacity, which consequently hinders flood related resilience building as aimed for in the Lockyer case. This shows how these subtle power dynamics produce undesired governance outcomes. At the same time, distrust also reinforces the resilience of the current system, which produces the outcomes that ought to be changed by the collaborative governance process (Allison and Hobbs 2004, Cumming 2018). Thus, fostering collaboration and social learning in multi-stakeholder settings requires strategies for trust building and simultaneously, mechanisms that help to break down distrust.

These insights have wider theoretical implications. They suggest a great need to discuss and clarify the role of each stakeholder group, and to clearly establish the responsibility and accountability that sits within each role. Huitema et al. describe collaborative management as “the sharing of rights, responsibilities, and power between different levels and sectors of government and civil society” (2009). Based on our findings, this definition requires adjustment as the “sharing” appears associated with great conflict potential and the term “power” is ambiguous. Instead, we suggest that collaboration in governance should be characterized by the clear allocation of roles, responsibilities, accountability, and joint decision-making power between different levels and sectors of government and civil society. Recent literature highlights the critical role of accountability, responsibilities, and joint decision making for collaborative governance in the water sector (Ulibarri et al. 2020, Söderberg et al. 2021, Goodwin 2022, Hale et al. 2022). Collaboration that is not situated in a space of joint decision making will fall short in including diverse types of knowledge and producing decisions that are supported or at least accepted by most of the collaborating groups.

Furthermore, these findings also have implications for the characterization of polycentric systems. When following Carlisle and Gruby, a polycentric governance system is composed of “(i) multiple, overlapping decision-making centers with some degree of autonomy [which] (ii) choos[e] to act in ways that take account of others through processes of cooperation, competition, conflict, and conflict resolution.” (2019:932). The “overlapping” is advocated because it is thought to spread responsibility, create redundancy, and, consequently, strengthen SE resilience (Carlisle and Gruby 2019, Morrison et al. 2019). However, according to the findings, the absence of clear responsibilities and accountability creates mistrust and weakens stakeholder relationships. Additionally, we found that the presence of competition that is described by Carlisle and Gruby (2019) as one process type in the polycentric system, is counterproductive for collaboration and social learning because it also creates mistrust. Based on these insights, contradictions between the concept of polycentricity on the one side, and the concepts of collaboration and social learning on the other side become apparent. Consequently, we present further evidence that (depending on its nature) polycentric governance systems do not necessarily support collaboration and social learning (Morrison et al. 2017, Heikkila et al. 2018, Wyborn et al. 2023).

Last, the structural dimension presents the largest and most various set of power dynamics. Because the structural dimension of power uses an agent-based power understanding, there is great potential to interrupt unproductive power structures. A key element here is to loosen the grip of government organizations on water governance processes and involve non-government actors in the decision making (Wyborn et al. 2023). Also important is the process facilitation, which is led by independent process professionals who do not have their own stake in the governance process, and hence, remain unbiased (Rowe and Frewer 2000, Mostert et al. 2007). Unbiased process facilitation involves skills that can accommodate and moderate stakeholder diversity, knowledge diversity, interest diversity, transparency, and openness as well as balancing different personalities to allow a fair and equitable discussion and learning process to unfold (Rowe and Frewer 2000, Innes and Booher 2004, Keen and Mahanty 2006, Mostert et al. 2007, Bartels and Furman 2023). That neutrally facilitated water governance forums hold benefits like heightened commitment, knowledge diversity, and improved dialogue has been, for example, demonstrated by Fowler and Shi (2016) or Prutzer and colleagues (2021). A helpful approach could therefore be the outsourcing the process facilitation to non-involved neutral agencies specialized in collaborative and learning process facilitation (Keen and Mahanty 2006, Newig et al. 2019, Bartels and Furman 2023). Consequently, there is need to design education programs (e.g., Bachelor degrees) that produce facilitators with expertise in conflict mediation (Reed et al. 2010), communication (Kansky and Maassarani 2022), stakeholder management, discrimination, and racism management (Carter and Hill 2007), as well as knowledge around social-ecological issues (e.g., environmental justice, climate change, water governance). This approach has great potential to support transparency and plurality around knowledge use and production as well as assist in dismantling distrust and building trust between the stakeholders (Lewicki and Brinsfield 2009). With that, professional facilitation could actively foster collaboration (e.g., inclusion from the onset, mediation in conflict situations) and social learning (e.g., moderating the input of extroverts and introverts, knowledge production and use).

CONCLUSION

The analysis of an Australian polycentric governance process has shown that collaboration and social learning were strongly influenced by diverse power dynamics from the instrumental, structural, as well as discursive power dimensions (after Lukes 2005). The most influential power dynamics across all three dimensions could be ascribed to three main power hubs (power centers that encompass a certain subset of power dynamics): the power of facilitation, the power of trust, and the power of politics. Power dynamics that operate in the structural dimension were most diverse and prevalent across all three power hubs. We interpret this finding as a promising entry point to address and leverage multiple structural power dynamics with only a few key actions.

Furthermore, our study demonstrates that most power dynamics across the instrumental, structural, and discursive dimensions affect collaboration and social learning simultaneously. We consider this a strong indication that collaboration and social learning are intrinsically linked. We regard knowledge and trust as the key “substances” that bound these two concepts. Our analysis provides evidence on how power dynamics shape collaboration and social learning processes, and how trust and knowledge produce feedback-loops between them. These insights into the interrelationships between collaboration and social learning have significant potential to advance social-ecological theory, particularly the SE resilience principles. Using a power lens as a “torch” to illuminate these interrelationships enables their identification. At the same time, it aids the integration of power theory into resilience conceptualizations, a continual blind spot in the field.

With a climate emergency taking place and severely impacting the water security of communities all around the world, we need to ensure our governance processes are as effective as they can possibly be. One promising avenue is to largely transform the way stakeholders interact by actively facilitating and managing collaboration and social learning processes. This will allow social capital to build and collective action to emerge, crucial building blocks for resilience.

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^[1] Department may have changed its official name. We use the name at the time of the collaboration.

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