Research

INTRODUCTION

Riverine flooding is an increasingly damaging and complex phenomenon on a global scale (Jian et al. 2024) in which effective planning is essential to reduce impacts (Kreibich et al. 2022). Flood planning in a changing climate is a wicked problem (Rittel and Webber 1973) requiring attention to ecological, social, and political factors. The complex interplay of planning, flood characteristics, and hazard communication creates risk patterns that shift with the coinciding social characteristics, environmental concerns, and political climate (Lechowska 2018, Tyler et al. 2019). In this context, collaborative planning is increasingly recognized as a promising approach for addressing such complexity because it can help integrate diverse perspectives and knowledge systems. A key challenge is identifying how such approaches can be strengthened to more effectively address the interdependent nature of these challenges.

Extensive considerations are required within flood planning. Similar to other environmental challenges, flooding occurs in social-ecological systems (SES) characterized by dynamic interactions among social actors, between these actors and the environment, and across environmental components and processes. Addressing such system problems requires decision making that spans sectors, boundaries, and perspectives while incorporating adaptive management (Folke et al. 2005, DeFries and Nagendra 2017). As such, planning must engage with both the practical challenges of implementation but also with the structural conditions that shape broader processes of coordination, negotiation, and adaptation among diverse actors. Environmental governance literature repeatedly argues that effectiveness requires responsiveness to the full complexity of the SES (Berkes and Folke 1998, Levin 1999, Dietz et al. 2003, Folke et al. 2005, Armitage et al. 2012). Although consideration of every contextual factor and interdependency across scales and levels within a system poses an insurmountable challenge, developing a clearer understanding of how addressing different dimensions of complexity contributes to more effective planning outcomes.

In this study, we framed decision making in the system as flood planning, which inherently requires considering aspects of ecological connectivity and interrelated planning functions. These elements can influence effectiveness of planning outcomes. The challenge of aligning decision-making systems to these complex interactions has been dubbed “the problem of fit.” Addressing the problem of fit is of foremost importance because it enhances governance system performance and SES outcomes (Berkes and Folke 1998, Galaz et al. 2008, Cox 2012). The hypothesis is that governance systems reflecting critical connections among and between social actors and environmental components are better able to match the scales of essential processes and learn from the dynamics in both the social and ecological systems (Folke et al. 2007, Bodin and Tengö 2012, Sternlieb et al. 2013). This emphasis on the interconnectedness of social and ecological systems extends the problem of fit to “social-ecological (SE) fit.” For example, managing watersheds sustainably requires attention to both the ecological dynamics of water flow and the social dynamics of land and water use.

Indicators of fit and misfit have been measured in a variety of systems, including conservation (Guerrero et al. 2015, Gallo-Cajiao et al. 2024), wildfire risk (Hamilton et al. 2019), policy interdependence (Hedlund et al. 2021a), and climate change adaptation (Fried et al. 2022, Vantaggiato et al. 2023); however, assessments tend to focus on how a governance system aligns with either the ecological context of the challenge or the institutional or functional context of the challenge. Studies that focus on the ecological context usually compare the way natural resource management systems are organized to connectivity in the environment, such as how forests, watersheds, or species are connected (e.g., Sayles and Baggio 2017, Hamilton et al. 2019). Collective action problems occur when independent decisions create joint outcomes (Ostrom 2010), and the interdependences that underline them can also be distributed across policy domains or functional arenas. Studies that focus on this institutional or functional aspect tend to compare the communication patterns among actors to interdependencies between policies or collaborative tasks (Bodin and Nohrstedt 2016, Metz et al. 2020). Although multiple relevant interdependencies coexist within a single system (Vantaggiato et al. 2023), they have rarely been assessed together in relation to fit. It is currently unclear how different interdependencies interact to influence fit (Bodin 2017).

Although there is a solid conceptual basis, the empirical evidence connecting SE fit and outcomes in SES is limited. Only a handful of studies have measured indicators of fit alongside outcomes (Barnes et al. 2019, Pahl-Wostl et al. 2023, Huber et al. 2024), and these studies have found diverging benefits of fit. For example, SE fit corresponded with positive ecological conditions in a study of coral reef fishing communities in Kenya (Barnes et al. 2019) but was found to be associated with worse governance outcomes in wetland governance in Switzerland (Huber et al. 2024).

In this study, we investigated collaborative flood planning in the Wolastoq | Saint John River Basin. In response to the knowledge voids above we: (1) addressed the need for approaches to assess multiple dimensions of fit by developing and testing an approach to do so and (2) contributed empirical evidence connecting SE fit and outcomes by testing the relationship between SE fit and performance in a case study of flood planning. We used a multi-level network approach to examine how collaboration patterns among actors aligned with interdependencies between flood planning functions and hydrologic connectivity. We tested a series of hypotheses regarding how these alignments related to actor performance. This analysis is a useful step toward identifying how alignment to different aspects of a focal problem interact, as well as identifying the circumstances in which achieving alignment between collaboration patterns and problem characteristics yields the greatest benefits.

SOCIAL-ECOLOGICAL SYSTEMS AND THE PROBLEM OF ‘FIT’

Social-ecological fit and flood planning

Flooding presents a challenge for the planning system to match both the biophysical processes and the collective action problem, providing an exemplary case to investigate both these dimensions of SE fit. Flood planning naturally needs to account for the multifaceted nature of flood risk, which is driven by a variety of social-ecological factors. Climate change is altering flood exposure through likelihood of events, flood extents, and emerging compound natural hazards (Dottori et al. 2018, Steinhausen et al. 2022). Flood exposure is further influenced by land use choices. Vulnerability is impacted by infrastructure tolerance, social systems, and individual experiences. Risk to natural hazards is heavily influenced by human behavior (Adger et al. 2005, Hemmati et al. 2021), especially the evolution of competing interest across regions or sectors, and risk perceptions (Razavi et al. 2020). Furthermore, when assessing the planning system itself at a basin-level, assessments need to account for the levels of government and multiple types of organizations involved (McGlynn et al. 2024).

From an ecological perspective, effective flood planning requires attention to the whole watershed or river basin because there are often upstream and downstream trade-offs (Razavi et al. 2020). This is a key challenge because watersheds often cross multiple political jurisdictions, and actions within one region impact others. In the Wolastoq, spring snowmelt combined with rainfall increases water levels. Land management actions in the upper basin of the watershed, such as preserving wetlands, can increase buffering capacity for major rain events lowering the flow rate of water entering downstream sub-basins (Newton and Burrell 2016, McGlynn et al. 2023). Flood planning requires regionally specific actions while accounting for biophysical interdependencies because one region’s attempt to limit its exposure may increase risk for a different region. Focusing on hydrologic connectivity as an element of the broader ecological considerations provides a means to assess how actors work with regard to the physical landscape (Widmer et al. 2019, McGlynn et al. 2023).

From the perspective of the collective action problem, flooding also presents a series of connected sub-issues or sub-problems (Metz et al. 2020), which are addressed through different functions (McGlynn et al. 2025). These core functions have shared resources or common activities and so are interconnected. Authority or responsibilities for these functions are often distributed among organizations with specific mandates, necessitating a need for collaboration between different organizations. For example, emergency response can be divided into interdependent operational tasks, such as evacuation and public communication (Bodin and Nohrstedt 2016, Bodin et al. 2022), but all require effective execution for overall success. Flood planning requires data collection and modeling; risk, vulnerability, and natural asset assessments; establishing work goals, monitoring programs, and new bylaws; and updating and building both gray and green infrastructure. Flood planning in the Wolastoq River Basin demonstrates the multiple and varied interdependencies that can be considered when assessing SE fit because the current constellation of flood planning actors is located in different political jurisdictions, operate over different spatial areas, and have different focuses and mandates.

Collaboration provides one mechanism to align the informal flood planning system with the hydrological and functional connectivity. Collaboration can connect actors to match the biophysical processes within the watershed so that actors who work in different regions of the basin can coordinate land management actions that can benefit the whole basin. For example, identifying areas for wetland restoration upstream that reduce water flow downstream. Collaboration can also help match the interdependencies that arise from the operational division of responsibility (Feiock 2013). For example, collaboration between actors in different regions of the basin can facilitate the sharing of water course data and models for use in natural asset management and climate change adaptation plans. Multiple organizations with diverse interests, types of expertise, and jurisdictional authority are often responsible for or involved in acting on different flood planning functions, and some degree of coordination is often required between them.

Patterns of collaboration are an important consideration when assessing SE fit, and choices for collaboration are influenced by the possible gains and transaction costs. Transaction costs indicate “the comparative costs of planning, adapting and monitoring task completion under alternative governance structures” (Williamson 1985:142) and are influenced by the type of problem being solved, the actors involved, and the broader context, such as the existing institutions and location (Lubell et al. 2002, Feiock 2013). Transaction costs may differ for organization types (Lubell et al. 2014) and may be lower when working with others with immediate proximity or who have similar missions or face similar challenges (Hamilton et al. 2019, Jasny et al. 2019, Bixler et al. 2023). Transaction costs increase for issues that require specialized knowledge (Metz et al. 2020) and when deep governance silos separate the interdependencies (Hedlund et al. 2022). Flood planning requires specialized knowledge, involves multiple branches or levels of government, and covers broader geographic areas, all potentially increasing the transaction costs associated with collaborating. Difficulties in collaborating across organization types in flood planning may manifest as a lack of shared commitment or opposing values (McGlynn et al. 2023). Collaboration within flood planning may need to align with the hydrologic and functions interdependencies while actors navigate transaction costs.

Social-ecological (SE) fit and performance

The theoretical development of SE fit associates achieving fit to enhancing performance. An early conception of SE fit set out by the International Human Dimensions Program of Global Environmental Change in 1998 asserted the “effectiveness and robustness of social institutions are functions of the fit between the institutions themselves and the biophysical and social domains in which they operate” (Folke 2007:14). This early work presented achieving and maintaining fit as a prerequisite for performance. Cox (2012) suggested the theory of fit implies a normative outcome with alignment; consequently, fit indicates a relationship that produces a desirable outcome. Epstein et al. (2015) further specified that fit is tied to system attributes associated with sustainability, must be measured rather than assumed, and must be assessed within the broader context. Implicitly, when governance systems do not align with the interdependencies in the system, fragmentation leads to ineffective governance and poor outcomes (Ostrom 1990, Cumming et al. 2006, Bodin 2017). Social-ecological fit has been repeatedly associated conceptually with enhanced performance (Folke et al. 2007, Cox 2012, Epstein et al. 2015); however, research to build an empirical basis to disentangle this potential relationship has lagged.

There have been a few notable investigations into how fit relates to governance performance. Whittaker et al. (2021) identified instances of SE fit in lake organizations in the northern United States by exploring how different ecological, social, and institutional conditions contributed to different SES governance outcomes. Notably, different combinations of Ostrom’s institutional design principles (see Ostrom 1990) and context attributes led to the same outcomes, providing evidence there is no universal approach to enhancing fit, and context is critical to the outcomes in the system.

Pahl-Wostl et al. (2023) separated two forms of SE fit between governance systems and ecosystem-service usages and interdependencies. The first measure of fit considered formal frameworks and policies to support coordination, while the second measure considered the implemented coordination processes. Fit was calculated based on the alignment of social connections among actors compared to ecosystem service use and interactions. System effectiveness was assessed by how coordination led to changes in plans and strategies, and if said changes were implemented. Fit was higher for the coordination in practice than for formal policies, but coordination with a high degree of fit supported both water security and sustainability.

Others have used a network-based approach to assess SE fit and outcomes. Barnes et al. (2019) identified that communication between fishers who harvested the same species was related to improved ecological conditions, supporting the fit hypothesis. Huber et al. (2024) investigated Swiss wetland governance to test the co-occurrence of SE fit network structures and governance outcomes. Social-ecological fit was measured through the presence of small-scale network structures, and outcomes were measured as how well the goal of relevant ecosystem management activities was achieved. The authors found a negative relationship between SE fit patterns and good outcomes, not supporting the fit hypothesis. The authors suggested good outcomes may more likely occur for ecosystem management activities that have lower risk and as such require fewer collaborative relationships. In contrast, negative outcomes may have prompted the need for more collaborative relationships, which may hold the potential to change the outcomes of ecosystem management activities in the future. Because this study investigated averages across cases, further analysis is needed to link actors’ assessments of governance outcomes to their specific collaboration patterns. Bodin et al. (2022) assessed how patterns of collaboration and task engagement impacted task effectiveness at the individual level in two cases of wildfire response. Task effectiveness was impacted by different collaboration structures between the two cases. In one case, collaborating on the same task or working on interdependent tasks enhanced effectiveness. In the second case, effectiveness was only enhanced when both structures co-occurred. Management in the first case was more hierarchical, possibly contributing to increased effectiveness with less entanglement.

On balance, although the SE fit hypothesis is gaining traction, it remains an unresolved question requiring further investigation. In particular, there is a need to understand under what conditions SE fit is associated with positive outcomes. Our study addresses this research gap by considering how patterns of collaboration relate to effectiveness, while incorporating both hydrologic and functional interdependencies. We test the fit hypothesis by applying the autocorrelation network approach from Bodin et al. (2022) that connects patterns of collaboration to function complexity and performance. We extend this approach to also incorporate hydrologic connectivity.

Social-ecological (SE) fit and multi-level network motifs

With the premise based on systems and alignment, SE fit lends itself to a network perspective. A network is a series of nodes and relations, and network analysis provides a method to quantity relations and overall network structure (Borgatti et al. 2009). Network analysis, specifically the use of multi-level networks, has provided a route to examine how structures and relations within the governance systems reflect the broader complexity it is attempting to address (Janssen et al. 2006, Bodin et al. 2014, 2016, Guerrero et al. 2015, Widmer et al. 2019). Bodin and Tengo (2012) presented a framework to quantify interactions in SES through a multi-level network approach that distinguishes different patterns of interdependencies in SES. This multi-level network approach constructs a social-ecological network (see Sayles et al. 2019).

Within this multi-level network approach, a social network, representing interactions, communication, or collaboration between individuals or organizations, is connected to a second set of nodes reflecting a different component of the system (Fig. 1). The accompanying second network has been conceptualized and constructed with different nodes and relations. Researchers have built networks from patches of land connected through seed dispersal (Bodin et al. 2014), species connected through food webs (Barnes et al. 2019, 2022), watershed delineations connected by water flow (Sayles and Baggio 2017, Widmer et al. 2019), and shoreline connected by tidal dynamics of sea-level rise (Vantaggiato et al. 2023). There have been simultaneous efforts to create networks reflective of the collective action problem. Such networks have mapped interrelated climate change issues (Fried et al. 2022), policy networks (Hedlund et al. 2021a, 2022), and task interdependency networks (Bodin and Nohrstedt 2016). For this research, we have connected a social network representing collaboration among organizations in the planning system to two different networks as representations of system interdependencies: an aspect of the ecological dimension through connected watershed units and an aspect of the functional dimension through interconnected flood planning functions (Fig. 1). Because we have three layers representing the different dimensions of the system, we have illustrated a three-level network; however, current network methods are restricted to analyzing two-level networks.

From this multi-level construction, the networks can be analyzed through the presence, or lack thereof, of small-scaler internal network structures, known as motifs (Fig. 1). Social-ecological fit literature has applied SES governance theories to develop a suite of motifs to indicate the extent of fit or misfit within an empirical system.

Social-ecological (SE) fit challenges and network hypothesis

Social-ecological fit challenges arise from a misalignment or mismatch between the governance function and problem characteristics (Guerrero et al. 2015, Bergsten et al. 2019). Social-ecological fit literature has emphasized the inherent cooperation and collaboration within governance arrangements as a key attribute to developing SE fit. As such, fit challenges emphasize these critical connections among decision-making actors to match dynamics in the problem sphere. We focus specifically on two SE fit challenges.

The first fit challenge, shared management, demands coordination between two actors engaging with the same focal interest. In an ecological framing, this may be the management of a region of land or an extractive entity, and in a collective action problem framing, this may be a policy or task. Stemming from common pool resource literature, this challenge is associated with the risks of independent use of a shared resource because independent decision making can lead to ineffective management or over-exploitation (Ostrom 1990). The challenges applied to network motifs create a closed social-ecological triangle in which two coordinating actors are tied to the same resource (Bodin et al. 2014, Guerrero et al. 2015). Misfit to this challenge is two actors not connected but engaging with the same region or policy (see Guerrero et al. 2015 for visuals). Closed common pool resource triangles have been associated with enhanced management (Bodin et al. 2014) and positive ecological conditions (Barnes et al 2019).

The second fit challenge, management of interconnected issues, demands coordination between two actors engaging with interconnected focal interests. Again, the focal interest can reflect the ecological context or the functional context. Independent management of interconnected resources may perpetuate misuse because impacts on connected ecological components may not be recognized and subsequently not adjusted for, possibly leading to severe environmental change (Bodin et al. 2014, Bodin 2017). When connected, the actors can monitor changes in both components and will experience indirect feedback from use or management changes (Bodin et al. 2014, Kininmonth et al. 2015, Alexander et al. 2017). Fit to this challenge can be represented through a closed square motif and misfit through an open square in which the social nodes are not connected. Collaboration that aligns with ecological interdependencies has presented a challenge in a variety of systems (Guerrero et al. 2015, Widmer et al. 2019, McGlynn et al. 2023), as has collaboration that aligns with interconnected policies (Hedlund et al. 2021b). Although there may be benefits to closing these loops, not all gaps need to be addressed by all actors (Fried et al. 2022), and other institutional mechanisms besides collaboration, such as laws, can close the connection (Metz et al. 2020).

Fit challenges have often been operationalized with a focus on a single interdependency in the focal system. In developing our hypothesis, we started with the prominent challenges in SE fit and applied them to the functional challenge. We then overlaid hydrological connectivity to differentiate the role of collaboration when organizations work in the same region versus when they work in interconnected regions. The functional challenge is representant through a network of interconnected flood planning functions. Hydrological connectivity is represented through a watershed network where the sub-basins in the Wolastoq are connected by water flow. To begin to relate SE fit to performance, we investigated how patterns of collaboration that reflect alignment for both the flood planning functions and the watershed impact an organization’s performance at addressing a focal function through a series of hypotheses (Fig. 2).

Shared functions

H1: untargeted collaboration reduces performance

Although generic recommendations within environmental governance suggest greater collaboration, previous research has identified relationships that do not provide support on a focal wildfire task may hinder performance (Bodin et al. 2022). We will first assess how this finding applies to flood planning.

H2: collaborating on the same function enhances performance

Collaborating on a shared function represents a case of shared management. Actors frequently choose to coordinate actions with those with a shared interest (Barnes et al. 2019, Hedlund et al. 2021a, Fried et al. 2023). Network models of the impact of collaboration on a shared wildfire task have shown a positive correlation with task effectiveness in an emergency response environment (Bodin et al. 2022); however, the outcomes of collaboration are further influenced by context and institutional structures (Brummel et al. 2012, Guerrero et al. 2023). This study assesses the effect of collaboration on function performance in a non-acute planning context.

Management of interconnected functions

H3: collaborating on interconnected functions enhances performance

Flood planning functions are interconnected. Previous research identified collaboration between two actors working on interconnected wildfire tasks was correlated with positive outcomes at the network level (Bodin and Nohrstedt 2016), but less conclusive results at the task level (Bodin et al. 2022). This configuration is suggested to improve effectiveness because the collaborative relationship would facilitate coordination actions to improve performance on a shared function (Bodin et al. 2022).

H4: independently working on interconnected functions enhances performance

Management of interconnected functions can occur by a single actor. This can reflect a greater system understanding, thereby addressing problem complexity (Galaz et al. 2008, Bodin et al. 2014, Guerrero et al. 2015) and increase autonomy over the functions. An organization engaged in two interconnected wildfire tasks is well-positioned to advantageously manage the interdependency (Bodin et al. 2022). We tested if this applies in flood planning.

Shared management of a sub-basin

H5: collaboration among organizations in the same sub-basin enhances performance

Coordination that connects actors engaging with the same ecological resource, fulfilling the challenge of shared management, has been correlated with positive ecological conditions (Bodin et al. 2014, Barnes et al. 2019). In this system, actors tend to collaborate with those who work in the same region (McGlynn et al. 2023). We are testing if collaboration within the same sub-basin influences function performance.

Management of interconnected sub-basins

H6: collaboration among organizations in connected sub-basins enhances performance

Collaboration that connects actors engaging with interconnected ecological resources can contribute to improved systems understanding, such as what is occurring up or down river. Both enhancing knowledge and social learning are essential factors in environmental governance (Armitage et al. 2008, Carr Kelman et al. 2023) and increased access to information also increases individual-level performance (Sparrowe et al. 2001). We are testing if collaboration that creates management of interconnected sub-basins influences function performance.

METHODS

Case study

Flood planning provides an excellent case to explore the multiple facets of SE fit. The Wolastoq | Saint John River Basin is a transboundary river basin in Eastern North America covering over 55,000 kmI² (Kidd et al. 2011) and forms part of the border between Canada and the United States. The river basin falls within the Canadian provinces of Québec and New Brunswick, and the state of Maine in the United States. The river basin, although having traditionally experienced seasonal flooding, is experiencing increasingly severe spring flooding (Woodhall-Melnik and Grogan 2019, Currie et al. 2020). Flooding has caused extensive damage, and variable flooding patterns are impacting communities in New Brunswick (Government of New Brunswick 2020, Wright 2024).

Data collection

The research began with three semi-structured key informant interviews. Key informants were selected based on knowledge and participation in collaborative flood planning efforts in the basin. Interviews verified a roster of all possible organizations conducting flood planning in the Wolastoq Basin and supported generating a list of key functions within flood planning. We used a similar approach to Bodin and Nohrstedt (2016) who identified wildfire response tasks to understand essential functions for basin-wide flood planning. They were asked to identify flood planning functions “when thinking about the whole river basin” and subsequently rank the functions in order of priority. The list of functions from all informants was amalgamated and compared to the flood issues presented by Metz et al. (2020). The list was refined to include 22 functions, which were categorized under 5 themes.

Function interdependencies were established through a thematic coding of interview transcripts and identified when two functions were mentioned in the same narrative as sharing resources or common activities. The identified interdependencies included data requirements, standard adaptation planning processes, enforcement of regulation, and sequential responsibilities in regional emergency planning. Established interdependencies were validated by a key informant who approved all but one identified interdependency, provided contextual descriptions for the identified connections, and suggested no additional interdependencies.

Data were collected in August and September of 2020 and 2021 through an electronic survey. The initial round of data collection occurred in 2020 and is described in McGlynn et al. (2023). A second online survey was administered in September 2021 to increase the response rate and better define network boundaries. Organizations identified as collaborators by responding organizations from the initial survey responses were once again asked to participate and were provided with a copy of previous research outputs. Organizations that were not identified as collaborators were also contacted to confirm they did not engage in any flood planning activities. An additional 12 organizations responded to the survey and 4 organizations indicated they do not conduct flood planning. In total, complete responses were received from 65 organizations (51% response rate). All data collection were approved by the Brock University Research Ethics Board.

When responding to the survey, respondents were asked to respond on behalf of their organization. Respondents were asked to identify from a listed roster which organizations they collaborated with when conducting flood planning, considering all activities since 2018. Collaboration was defined as the regular professional sharing of human, financial and/or technical resources, engaging in joint activities, and organizing joint activities (McGlynn et al. 2023). Respondents were asked to identify in which sub-basins their organizations conducted flood planning. Respondents also identified the flood planning functions of their organizations and indicated how effective they thought they and their nearest collaborators, as in those they worked directly with, were in addressing the different functions. Responses were recorded on a four-point scale from “not at all effective” to “very effective,” or “I don’t know.”

Network construction

We constructed a hydrological network of the watershed based on river flow connecting smaller watershed units. There are 16 ecologically defined sub-sub basins within the Wolastoq sub-sub drainage areas (Government of Canada 2020) and hydrologic unit code 8s (USDA-NRCS 2020), and a tie was established between nodes based on connections through downstream flow. A social-ecological network connected responding organizations to the sub-sub basin(s) where the organization conducts flood planning, as indicated in the form survey responses.

The collaboration network links organizations based on reciprocal collaborative ties, defined as relationships mutually acknowledged by both organizations. Responses from both waves of data collection were amalgamated into one network. The collaboration network was restricted to responding organizations. Two variations of the collaboration network were created to reflect specific social-ecological fit challenges, management of a shared resource, and management of interconnected resources (Guerrero et al. 2015).

The “same location” network maintained all 65 nodes and only kept the ties from the collaboration network for when both organizations conducted flood planning in the same sub-sub basin. Many organizations work in multiple sub-sub basins (McGlynn et al. 2023), and a collaborative tie was kept such that both organizations worked in at least one of the same sub-sub basins. This collaboration network reflects the challenge of shared management. The “ecological neighbor” network similarly only kept ties when the organizations worked in connected sub-sub basins based on the hydrological network. This collaboration network reflects the SE fit challenge of management of interconnected issues.

The “function interdependency network” was constructed from the identified functions as the nodes with links indicating shared resources or common activities, as verified by the key informant. The “actor-function network” connected the responding organization to each function they identified in the survey. The responses were transformed from the indicated level of effectiveness to a corresponding value of 1 to 4, where 1 corresponded to “not at all effective” and 4 to “very effective.” Responses of “I don’t know” were transformed to 0, equating it to a non-response (Appendix 1, Table A1.2 for frequency of responses). The actor-function tie effectiveness is the dependent variable in the network autocorrelation model.

Data analysis

Network autocorrelation models provide an alternative to regression models for network data to explain a node-level attribute as a function of the network and a set of covariates (Doreian 1989). The network structure is incorporated to account for social influence (Leenders 2002) in which an actor adopts the beliefs or behaviors of others in the system. The network autocorrelation model was adapted for the multi-level data set following the procedure presented in Bodin et al. (2022).

In our adapted autocorrelation model, the dependent variable was actor-function tie effectiveness. The dependent variable was transformed into a vector of length N*F, where N is the number of actors and F is the number of functions. The network effect terms are the actor-task configurations and the influence of collaborators’ performance assessments.

The multi-level motifs (Fig. 3) were normalized by the number of times the actor could be in the structural configuration for the focal function. We controlled for social influence in our model, which in our case is the influence of collaborators’ performance for the focal function. This captures the idea that the focal actor’s performance in the shared function improves when collaborators perform well because their success promotes collective progress and enables learning through knowledge and skill transfer (Bodin et al. 2022). We also included average performance ratings to control for individual actors’ varying propensities to report high or low effectiveness and the function level effect to control for some functions being more difficult than others. Model parameters were estimated using maximum likelihood (ML) in the lnam function in the sna package (Butts 2020).

A range of models was tested on each of the three networks (all collaboration, same location collaboration, and ecological neighbor collaboration), sequentially including and removing terms to find the best-fitting model while minimizing term interactions. The full suite of terms used is presented in Appendix 1. Akaike information criterion (AIC) was used to select the best-fitting models.

RESULTS

Testing how shared management of a task influenced actor-function performance involved two hypotheses assessed across all three network models (H1, H2). For the full collaboration network and the same location network, collaborating with others not working on the focal function (H1) did not have a significant effect on performance (Fig. 4). However, throughout test models, the “collaboration” term was consistently negative, fluctuating around the 90% confidence interval (Appendix 1, Table A1.5). Importantly, in the ecological neighbor network, the collaboration term had a negative and significant impact on actor-function performance. These findings support H1, showing that untargeted collaboration reduces performance, particularly when collaborating across sub-basins.

For the best-fitting model, H2 and H3 were captured together in the diagonal square term, which combined two inverse triangle motifs (H2) and a square motif (H3). Collaborating on two shared and interconnected functions had a significant effect on actor-function performance only in the ecological neighbor network. The H2 and H3 terms were also tested separately, informing model interpretations. The square term without diagonals (H3), representing the management of interconnected functions, was not significant in any of the test models (Appendix 1, Table A1.5). Taken together, these results support H2 and H3, suggesting that collaboration enhances performance only when collaborating actors are both working on two interconnected functions and working across sub-basins.

When testing how the management of interconnected functions by a single actor influenced functions performance, we found that working on interconnected functions had a positive effect (H4). The functions triangle marginally increased actor-function performance in the full collaboration and the ecological neighbor network and was significant in the same location network. This result supports H4, showing that working on interconnected functions enhances performance.

Looking at the differences between models considers how the contexts of the two fit challenges impact actor-function performance. The model results from the same location network assessed how shared management of a sub-basin influenced actor-function performance. Neither the collaboration nor the diagonal square terms were significant, which does not support our hypothesis (H5) that collaboration among organizations working in the same sub-basin enhances performance. The full model results from the ecological neighbor network assessed how the management of interconnected sub-basins influences actor-function performance. Collaboration among organizations in neighboring locations did have a significant effect on function performance (H6). Specifically, collaborating with others not working on the focal function had a negative effect on actor-function performance, while the diagonal square term representing collaborating on two shared and interconnected functions enhanced performance.

In all three network autocorrelation models, the average performance of the organization had a positive and significant impact on function effectiveness, controlling for individual differences in perception. A dummy function variable was also included to control for some functions posing greater difficulties than other functions. The same three functions (developing natural asset management plans, developing bylaws and regulations, and installing green infrastructure solutions) were negative and significant in all three models (Appendix 1, Table A1.4). Collaborator effectiveness had a non-significant effect on function effectiveness across all models.

DISCUSSION

Our approach enabled the study of collaboration patterns that support actor-function performance in SES, considering an aspect of both the ecological and functional dimensions of the planning problem. By focusing on specific fit challenges, we used this approach to test the relationship between SE fit and planning outcomes, measured through flood planning function performance. We make several empirical observations that help advance SE fit theory, notably, that aligning collaboration to interdependent functions to enhance performance depends on the SE fit challenge.

Our results support the claim that untargeted collaboration to solve environmental problems may be detrimental to achieving outcomes (Bodin et al. 2022; H1). Our results provide further insights suggesting that this is particularly disadvantageous when working across regions. Maintaining collaborative relationships requires resources. Allocation of resources toward relationships that do not align with current critical interdependencies, while perhaps adaptive for future conditions (Bodin et al. 2019a, Vantaggiato et al. 2023), may reduce performance on activities that require immediate resources.

Our results also support previous studies showing that collaborating on shared responsibilities enhances performance (H2). Analysis of wildfire task performance identified collaborating on a shared task was correlated with improved performance (Bodin et al. 2022). Previous analysis in a flood planning context identified collaborating on shared functions correlated with higher performance at the organizational level (McGlynn et al. 2025). Our findings provide a more nuanced understanding by identifying that this enhancement might be limited to a subset of conditions

There is no evidence collaborating with others for shared management of a sub-basin enhances performance (H5). A tendency to collaborate with others within a shared ecological unit has frequently been found in SE fit literature (Widmer et al. 2019, Vantaggiato et al. 2023). Although this pattern of collaboration frequently occurs and can likely have benefits, our results suggest that it does not correlate with enhanced functional effectiveness.

The apparent lack of collaborative benefits may be explained through the drivers of collaborative relationships. Collaborative partner choice is heavily influenced by the relative cost of the relationship, with minimizing transaction costs being a more prominent influence than aligning with system interdependencies (Nohrstedt and Bodin 2019, Hedlund et al. 2021a). When transaction costs are lower, partner choice may be more influenced by problem interdependencies to maximize individual benefit (Nohrstedt 2018, Fried et al. 2023). Geographic proximity reduces transaction costs (Fischer and Jasny 2017, Hamilton et al. 2023), increasing the opportunity for actors to choose relationships that will provide the most benefits. When SE fit is occurring for a shared sub-basin and “is easy” because the two organizations are working in the same space, more collaboration may not be beneficial but is also not a hindrance. More of these relationships, which likely have lower transaction costs, are not hindering effectiveness and potentially could become “adaptive” as the problem evolves (Vantaggiato et al. 2023).

Transaction costs are also lower when similar types of actors work together. Similar actor types may be working on the same flood planning tasks because of their respective mandates or goals. Layering this tendency together with an increased inclination for collaboration to occur between organizations working in the same physical space or with the same resources, it may be sufficiently easy for organizations to maintain relationships without receiving immediate benefits.

When working across ecological units, collaboration needs to align with function interdependencies to enhance performance. When assessing how the management of interconnected sub-basins influences performance (H6), collaboration with those not working on the focal flood planning function hindered performance. Collaboration on two shared and interdependent functions greatly supported performance. Collaboration across sub-basins likely has higher transaction costs, reflected by the under-representation of collaboration across ecological interdependences throughout the literature (Bodin et al. 2019b). In flood planning, collaboration across connected sub-basins may have higher transaction costs due to the increased geographic distance. When SE fit “is difficult” and misfit is more prevalent, collaboration needs to align with function interdependence. Collaboration that aligns with these interdependences, such as the tightly entangled diagonal square, may support overall system understanding and maximize performance from learning and sharing resources (Leach et al. 2014). Organizations engaging in the same interdependent functions, for example gathering watercourse data, conducting vulnerability assessments, or developing adaptation plans, can learn from each other and generate positive outcomes for their respective work (Plummer et al. 2022). The added challenges and transaction costs of collaboration across regions require in-depth collaboration to generate performance benefits. Mere coordination in this setting does not provide benefits, but rather collaboration when both organizations work on independent functions is shown to garner performance benefits.

Actors will collaborate if the gains outweigh the costs (Bixler et al. 2023), prioritizing localized alignment over broader-scale alignment (Hamilton et al. 2019). Our results show significant performance benefits from highly intertwined collaborative structures that span hydrological boundaries; however, these collaborative dynamics may be difficult to initiate. Network brokers have the opportunity to reduce the transaction costs of initiating cross-basin relationships (Hamilton et al. 2021, Bixler et al. 2023, Vantaggiato et al. 2023, McGlynn et al. 2024). Organizations of similar types (NGOs, municipalities, etc.) may be working on the same suite of interconnected flood planning functions (floodplain mapping, vulnerability assessments, developing natural asset management plans, etc.) in multiple parts of the basin. Our results suggest collaboration among these organizations could support effective flood planning. Clear, goal-oriented relationships can enhance organizational performance (Nohrstedt 2018). The reoccurring recommendation is for regional governance arrangements to prioritize facilitating and catalyzing collaborative relationships among organizations with similar functions but working in distinct regions.

This work has provided empirical evidence linking SE fit and functional performance, opening several additional considerations. Our research provides support to the hypothesis that SE fit can enhance performance, yet suggests this relationship is stronger in certain situations. The critical extension is the identification of an interaction between different dimensions of the focal problem, namely hydrological connectivity and functional interdependence. Our findings suggest that when working in the same sub-basin, autonomy over interdependent functions is sufficient to enhance planning performance. Conversely, when working across sub-basins, collaboration on two interdependent functions is necessary. We recognize that this distinction might be unique to our flood planning case and may differ in other systems and/ or at different time points in collaborative development. Future studies should test our hypothesis of SE fit, interactions between dimensions of the focal problem, and performance in other contexts.

We should also consider other aspects of collaboration and performance. Collaboration is multi-faceted and occurs in various forms. For example, some relationships may be mandated, whereas others develop organically; some connect similar types of organizations, whereas others link dissimilar ones. Identifying the performance benefits of different common types of collaboration would be useful for purposefully adjusting governance systems. Lastly, what level of performance is sufficient? Performance cannot increase indefinitely. Exploring the extent of fit that provides a foundation for sufficient performance is a useful research direction.

CONCLUSION

This research investigated the relationship between fit and flood planning outcomes through the metric of actor-function performance in the Wolastoq | Saint John River Basin of eastern North America. In building upon conceptual suppositions about SE fit and performance, the work makes two important contributions. First, we measured the immediate connection between indicators of SE fit and performance, displaying how specific actor-function configurations are related to performance. Second, we have combined two often separated components of fit enabling us to deliver rare insights on when collaboration should be the most strategic to support both fit and performance.

We argue this is evidence supporting the overarching hypothesis that SE fit is a precursor for performance. Whereas empirical work linking indicators of fit to performance is limited, our findings contribute to this body of evidence and demonstrate how fit may differ for different dimensions of a focal problem. When transaction costs are higher, such as when working across sub-basins, collaboration that aligns with function interdependencies enhanced performance. In this situation, untargeted collaboration negatively impacts performance while collaborating on two shared and interdependent functions enhances performance.

Achieving indicators of SE fit alone does not guarantee performance, as displayed by the absence of performance benefits from collaboration in the same location network. This is not to suggest that there are no benefits from collaboration when working in the same sub-basin. Rather, less strategic collaboration appears neutral, and benefits may emerge at a different unit of analysis, potentially avoiding negative outcomes more than enhancing performance. In a complex system in which actors are facing overlapping challenges, strategic collaborations that reflect multiple forms of complexity can enhance performance.

Our approach has some limitations. Function performance is a “meso-level” perspective on collaborative effectiveness (Bodin et al. 2022). While this focus on function-level effectiveness is not reflective of positive outcomes at the basin level, if a degree of SE is a prerequisite for performance as suggested, we can reason SE fit will first contribute to improving intermediary outcomes. Although modeling function effectiveness, not all functions are created equal; we controlled for performance differences through the function variable included in the model, but we did not control for how some functions may require or benefit more from collaboration. Furthermore, we used cross-sectional data to understand task performance as a metric of outcomes. Although a useful indicator for early stages of collaborative endeavors, as always, longitudinal monitoring would be required and should be prioritized in future studies to begin to connect the co-evolution of SE fit with outcomes.

Our findings illustrate a degree of interaction between matching the ecological and functional complexities embedded in addressing flood planning as an example of an environmental challenge. Social-ecological fit promotes alignment between the decision-making system and the focal challenge; however, the complex systems nature of current environmental challenges dictates a perfect fit would be impossible to achieve and maintain in an ever-evolving system. It is then essential to understand the circumstances when fit, as operationalized by well-aligned collaborations, should be prioritized. Collaboration is influenced by transaction costs, which have been shown to change based on spatial and functional scales. Better understanding of the fit orientations that may enhance performance, while accounting for limitations imposed by the relative transaction costs, can support effective collaboration. Future research should further probe not only the relationship between fit and performance but also the relative performance gains from specific fit orientations, both at the organization and whole system levels.

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