The following is the established format for referencing this article:Stahl, A. T., and A. K. Fremier. 2023. Translatability of water governance experiments across settings and scales. Ecology and Society 28(1):42.
Adaptive governance requires institutional capacity to coordinate responses to environmental problems at appropriate scales and utilizes networks for information sharing. This implies a capability to translate successful governance experiments from one social-ecological setting to another. Yet, translating lessons learned from case studies in adaptive water governance to other settings is all but straightforward. Watershed condition is a cumulative result of upstream ecological factors as well as land use decision-making processes, which may involve diverse stakeholders and multiple, nested levels of government. The relationships between site-specific land management decisions and water-related ecosystem services not only vary by location, but are further complicated by biogeochemical flows, ecological interactions, and social-ecological trade-offs. We view this governance challenge from a biophysical science perspective, highlighting the need to focus on translatability of governance approaches such that land use decision-making processes can better fit the dynamic, multidimensional, spatially continuous nature of riverine networks. To learn from a previous attempt to translate a successful water governance experiment across social-ecological settings, we investigated a case study of riverside area management in Washington State, northwestern USA. As participants in an agency-led workshop, we observed particular challenges in coordinating riverside management recommendations across a spatially variable social-ecological landscape. To clarify potential steps for translating riverine policy experiments, we intersected ecological understanding with adaptive governance scholarship. Using the case study as an example of the challenges of translating a policy experiment, we reviewed the ecological, management, and adaptive governance literatures to identify four elements of translatability: (1) a cross-sectoral, multiscale understanding of the shared goals or future desired state of the system; (2) quantified functional relationships between measurable site-scale features and ecosystem functions related to the shared goals; (3) definition frameworks to relate ecological concepts to the levels of potentially networked governance; (4) mapping strategies to visualize emerging networked governance in spatial context. We reviewed definitions pertaining to riverside areas and arranged them along a concept-application spectrum to provide a framework to relate ecological knowledge to the levels of potentially networked riverine governance. We mapped the spatial footprints of related policies nested within areas of similar ecological landscape characteristics to show spatial patterns that could inform translation of governance experiments in empirical context. We then discussed the role of translatability in adaptive water governance. We conclude with recommendations for considering the translatability of adaptive water-governance experiments and identifying potential opportunities to leverage existing ecological and institutional relationships to improve cross-scale fit with ecosystems across heterogeneous landscapes.
Individual implementations of environmental governance are experiments. These experiments are ubiquitous and involve multiple levels of both informal and formal institutions (Lebel et al. 2006, Young et al. 2007, Farrelly and Brown 2011). Some are considered successes, others failures, and for many, it is too early to know. Learning from the outcomes of these governance experiments is vital (Bos and Brown 2012, Suskevics et al. 2018, Pahl-Wostl 2019) and perhaps well described case by case. However, translation of successful experiments to other landscapes is far less well documented. We define translation as the intentional sharing and application of lessons learned from governance experiments to a different social-ecological context. Considering the processes of translation, and being intentional about it, can improve the probability of success and positive returns from experimentation (Bos and Brown 2012, Chaffin et al. 2016b). Successful experiments can be translated (i.e., adapted and applied) across settings or scales and likely involve communication across and among institutions (i.e., networked governance; Carlsson and Sandström 2007, Newig et al. 2010). Shifts toward more networked institutional structures and processes spanning nested levels within a social-ecological system (SES) offer potential to enhance spatiotemporal fit with ecosystems for more effective adaptive water governance.
Adaptive governance includes the social processes that translate lessons learned from successful experiments from one setting to another, which is a form of information-sharing that supports social learning (Pahl-Wostl et al. 2007, Decaro et al. 2017). We refer to translatability as this subset of adaptive governance concepts (e.g., Folke et al. 2005, Chaffin et al. 2016b), which are commonly discussed in the literature but are not often the central focus. As ecologists, we view translatability as the capacity to intentionally adapt and apply successful experiments to foster coordinated actions at the levels or scales most relevant to biophysical systems underpinning the shared desired state of the SES. From this perspective, clarifying the relationships between the spatiotemporal scales of biophysical systems and levels of society (actors or institutions) in empirical settings could help to identify opportunities to enhance social-ecological fit (e.g., Folke et al. 2007, Olsson et al. 2007, Brondizio et al. 2009). In concept, networked governance of the commons can lead to more scale-responsive environmental management (Carlsson and Sandström 2007) through institutionalized relationships that are stable, enabling trust and cooperation, yet still capable of change (Newig et al. 2010).
We developed the concept of “translatability” within a network governance framework to highlight existing institutional capacity to facilitate learning across social-ecological contexts to improve spatiotemporal fit in water governance. We acknowledge that each SES is unique and that no governance approach is universally applicable; yet, we posit that there are broadly applicable steps to systematically learn from and translate successful governance experiments for applicability elsewhere. Empirical studies have examined evidence of shifts toward adaptive water governance, typically describing water problems in a specific watershed or basin and providing broader recommendations (e.g., Olsson et al. 2006, Gunderson and Light 2007, Chaffin et al. 2016a). Lessons learned from theoretical and empirical studies have been applied to other settings or generalized for broader use (e.g., Green et al. 2012). However, there are few empirical studies of intentional translation in which successful approaches are systematically adapted to suit different social-ecological settings and thus improve institutional fit.
Among the hindrances to achieving the ideal networked governance at biophysically relevant levels or scales is the complexity of coordinating diverse actions across a heterogeneous social-ecological landscape. In many cases of water governance, more spatial coordination and knowledge-sharing among stakeholder groups would likely increase the odds of advancing toward the desired state of the system, but the legal and social barriers to coordination are often considerable (Cosens and Gunderson 2018). Bridging organizations exist, but each has limitations, for example, in their spatial area of influence. Formal governments often rely on top-down regulatory authority, which may not always be socially preferred or well suited for implementation on private lands (Cosens et al. 2017, Craig et al. 2017). Where agencies directly administer environmental policies, each operates within a specified jurisdiction, according to its mandate and the source of its authority. The administrative “footprints” of multiple organizations may overlap in space but are not necessarily congruent or coordinated in practice (e.g., Leong et al. 2011, Stahl et al. 2020). Nongovernmental groups such as conservation organizations can be limited in the scope of their projects for practical reasons such as funding availability and landowners’ willingness to participate. For example, groups working for salmon recovery in the western USA commonly focus on piecemeal actions, such as reach-level stream restoration projects, even though anadromous fish require continuous habitat from headwater streams to the sea to complete their life cycle and persist (Rieman et al. 2015, Reeves et al. 2018). Translatability thus includes consideration of multiple forms of landscape fragmentation involving social, legal, and ecological factors that vary at nested levels within an SES.
The importance of translatability in adaptive water governance may be most evident in the context of riverine landscapes. Policies or programs with targets related to improved water quality or likelihood of species’ persistence cannot succeed without coordinated actions that span the multi-scale, multi-level social-ecological settings of a river basin (Fig. 1). Figure 1a illustrates the multi-scalar biophysical processes influencing ecosystem services in riverine systems, while Figure 1b overlays the nested levels of formal governance structures for riverine systems in the USA. The figure illustrates the complexity of governing organisms and ecological processes that span or flow across social-ecological boundaries. Land use and management decisions affecting riverine ecosystem functions, such as pollutant removal or reducing stream temperature, are typically made on a parcel basis. Yet, outcomes such as improved water quality depend upon cumulative practices at watershed to major river basin extents, requiring more coordinated actions (Vreudenhil et al. 2010, Cole et al. 2020). More scale-responsive water governance arrangements (often involving community-based initiatives or cross-watershed groups) are emerging to provide multi-scale, multi-level coordination in response to a place-based water problem (e.g., Chaffin et al. 2016a, Keeley et al. 2022). These experiments are nascent in the contemporary context and are typically localized but have implications for broader applicability within a networked riverine governance framework. Identifying the key elements of translatability will enable empirical study of emerging networked riverine governance with capacity to promote more multi-scale, multi-level coordination in shifts toward more adaptive water governance.
We combined ecological knowledge from the riverine scientific and management literature with adaptive governance scholarship and our observations from a case study to identify an initial set of elements of translatability. The case study involved an attempt to translate lessons learned from a successful governance experiment across social-ecological settings to aim for ecological recovery at the extent of the Columbia River Basin, in northwestern USA. To clarify what knowledge would be needed to move toward more coordinated multi-level governance in this case, we reviewed the literature to relate the array of scientific, management, and policy definitions to the ranges of spatiotemporal scales at which networked water governance would potentially operate. We then mapped nested ecological and policy attributes to the landscape to indicate spatial opportunities and challenges for translating experiments across settings. We discussed the ways in which each of the four elements can influence the translatability of successful experiments as an essential component of shifts toward more networked, scale-responsive water governance. While we focus on governing cross-scale connectivity in riverine systems, the concepts apply more broadly to water governance and other areas of environmental governance involving dynamic flows across landscapes, including large landscape conservation initiatives.
Conceptual basis for translatability of adaptive water governance experiments
Terrestrial-based water problems pose multi-level governance challenges as water flows across heterogeneous social-ecological landscapes (Cosens and Gunderson 2018). From an ecological perspective, governance to conserve riverine ecosystem services would address the nested, interconnected, and dynamic nature of river systems (Fremier et al. 2013). Across a river basin, the ecology can vary substantially in space and time depending upon factors such as climate and geology. Within a watershed, riverine ecosystems are continuously connected longitudinally, laterally, and vertically to adjacent lands and subsurfaces, as well as through various levels of time (Ward 1989). Superimposed on this complexity, human land use, ownership, management, and perspectives on the value of riverine ecosystem services vary with location at multiple levels or scales (i.e., from parcel to watershed) (Brondizio et al. 2009, Mitchell et al. 2015, Steffen et al. 2015, Stahl et al. 2020). Because of this, riverine landscapes are highly divided by boundaries of land ownership, management, and social values. Governance of riverine landscapes thus contends with spatial heterogeneity in ecological characteristics and conditions as well as in social values, policy or funding mechanisms, and land management practices.
We view these challenges as problems of institutional misfit (Cumming et al. 2006) with riverine ecosystems that could be addressed in part by enhancing the translatability of governance experiments across settings at nested levels within a river basin. We summarize several focal points from the literature that relate to key considerations for framing a more intentional, systematic translation process (Bos and Brown 2012, Chaffin et al. 2016b). These include ideas for improving institutional fit with ecosystems, harnessing existing polycentric units of governance, and sharing of information (learned from experimentation) through social networks.
Institutional fit with ecosystems
Successful governance experiments are actively disseminated through networks of individuals and institutions, both formally and informally. We posit that focus on the intentional translation of experiments would help to improve the fit between institutions and ecological components, structures, and processes that underpin a desired state of the social-ecological system (Folke et al. 2007, Galaz et al. 2008, Moss 2012). Improving fit, albeit a conceptual remedy, recognizes that governmental policy or regulatory mechanisms cannot readily manage all relevant spatial and temporal scales to conserve ecosystem elements that provide ecosystem services, critical to human health and being, among other elements of biodiversity (Lemos and Agrawal 2006, Fremier et al. 2013, Falk et al. 2018). By recognizing potential spatiotemporal mismatches between existing forms of governance and ecosystem processes, problems and solutions might be clarified (Cumming et al. 2006).
Coordination of actions at scales more relevant to ecological processes to address environmental problems will inevitably require the participation of institutions and actors outside of formal government. Restricted timber harvest, for example, along headwater forested streams has fallen short of achieving water quality goals for salmon recovery in the northwestern USA, largely because of downstream conditions controlled by private land use practices (Reeves et al. 2018). More collaborative governance approaches would be necessary to coordinate private land practices in various local social-ecological settings to improve water quality at the river basin extent.
Improved fit with riverine ecosystems in theory requires coordination among multiple nested centers of formal and informal governance to balance competing interests across landscapes, levels, and scales (Cosens et al. 2014). Polycentricity recognizes the multiple centers of power in existing hierarchical governance systems composed of formal and informal actors. A network of connected polycentric units could in theory respond to environmental problems as they arise by matching the spatial scale of the problem (referred to by governance scholars as modularity) (Dietz et al. 2003, Folke et al. 2005, Cosens et al. 2017). Understanding the polycentric relationships in existing governance systems may reveal opportunities to facilitate translation through information-sharing and coordinated actions at appropriate levels and scales (Huitema et al. 2009, Biggs et al. 2012). For example, the Upper Columbia Salmon Recovery Board provides capacity to coordinate multi-watershed efforts that are beneficial for broader salmon recovery, because recovery depends upon the cumulative condition and connectivity of sites across the upper Columbia River Basin and Puget Sound. Governance for salmon recovery is designed to be adaptable across a heterogeneous landscape by adjusting rules to address site characteristics and economic costs (i.e., for individual restoration projects or recommended management practices) and simultaneously coordinating a diversity of actions among watersheds within the river basin (Craig et al. 2017, 2020).
Translation through networks
The information needed to govern ecosystem services over heterogeneous landscapes is at the intersection of scientific understanding and the social values determining policy goals (Wilhere and Quinn 2018, Chapman et al. 2020). Translation of lessons learned from one setting to another within a river basin requires networks among institutions and individuals for information-sharing (Pahl-Wostl et al. 2007, Newig et al. 2010). Information-sharing in riverine governance involves clear articulation of socially desirable outcomes (i.e., ecosystem services) and the ecological factors that relate to those outcomes (i.e., the production of natural capital) (e.g., Biggs et al. 2012). To leverage existing networks for information-sharing, current ecological understanding would ideally help inform evolving decision-making processes across levels, scales, and settings (Vreudenhil et al. 2010, Stahl et al. 2020). For example, Figure 1 illustrates the levels and spatiotemporal scales at which existing instructions operate (Fig. 1b), which can be related to natural processes operating at similar scales (Fig. 1a).
APPROACH AND METHODS
Case study context
Washington state spans a heterogeneous social-ecological landscape. On the humid western side of the state and in parts of northeastern and southeastern Washington, climates support forested plant communities and commercial forestry with a large percentage of the land area in protected status. In the center of the state, the semi-arid to arid Columbia Plateau Ecoregion (CPE) supports shrub-steppe and grasslands; agriculture is the predominant land use (orchards, row crops, or grazing); and most of the land area is privately owned (Figs. 2 and 3). Differences in ownership, land use, and land cover types pose political and practical challenges to state agencies’ efforts to effect environmental policy updates statewide.
In Washington, three conservation plans restrict riparian (riverside) timber harvest to improve freshwater habitats on forested lands under federal, state, or private ownership, respectively: The Northwest Forest Plan (1994); State Trust Lands Habitat Conservation Plan (HCP) (1997); and the Forest Practices HCP (2006) (referred to as the Forests and Fish Rules) (Fig. 2) (Wilhere and Quinn 2018). Each plan was negotiated on the basis of the same science, i.e., there was little or no disagreement among stakeholders about what constituted the best available science, and each plan resulted in increased protections of riparian forests (Wilhere and Quinn 2018 for a discussion of the three plans). These plans balance timber harvest with aquatic habitat conservation (namely salmon and clean water); each plan restricts riparian timber harvest to different degrees. The data-driven, but conceptual, model for all three plans was a set of graphical relationships representing the riparian ecological functions that most impact aquatic ecosystems. These are known colloquially as “the FEMAT curves” (FEMAT 1993; Fig. 7-7 and 7-8 in Reeves et al. 2018).
The FEMAT curves represent tree-based ecosystem functions including streambank stability, wood inputs to the stream, detrital nutrients, shade, and pollutant removal. The independent variable is distance from a stream channel expressed as site-potential tree height. The delivery of wood, detrital nutrients, and shade from riparian areas to stream channels are predictably related to tree height with schematic curves. With this relationship, each proposed riparian management zone width has been used to estimate costs (i.e., loss of timber harvest revenue) in policy negotiations (Wilhere and Quinn 2018). The FEMAT curves provided a practical and systematic representation of relevant biophysical factors to inform policy discussions for timber management on forested lands across social settings.
Recognizing that the basin-level conservation goals (water quality improvement and salmon recovery) could not be achieved without addressing riparian practices in the agricultural areas (e.g., Reeves et al. 2018), the state began investigating the potential to translate successful elements of the forest-based strategy to the dryland agricultural CPE (The William D. Ruckelshaus Center 2010, Windrope et al. 2020). The translation from forest-dominated to shrub-steppe (across ecological settings), from forestry lands to agricultural lands (differing land use), and from moist to arid (climatic contrast) revealed several challenges (Wilhere 2020). The state convened a technical advisory group in 2017 to provide a set of relationships analogous to the FEMAT curves for riverine management recommendations to maintain or enhance ecosystem condition in the CPE drylands.
Observations and research questions
In 2017, Washington Department of Fish and Wildlife (WDFW) assembled a panel of experts to synthesize the best available science to inform policy guidance for local governments regarding riparian management in the CPE drylands. The experts were academics (including the authors), state and federal agency scientists and managers from within and outside the state. Their primary interests ranged from vegetation to aquatic species to hydrology. We were asked to work collectively over 1.5 days to synthesize our knowledge in a way that could inform riparian management zone delineation throughout the CPE. Our assigned tasks were to (1) produce a concise scientific definition of dryland riparian ecosystem and (2) develop a set of FEMAT-like curves for CPE riparian areas. After two days, the group generated numerous ideas and suggestions but were unable to converge upon either a single static definition or set of FEMAT-like relationships that applied across the CPE drylands.
The authors of this study participated in the meeting and post-meeting communications. We did not conduct formal interviews but had multiple discussions about the workshop and context with the WDFW officials. We considered the workshop as an attempt to adapt an element of translatability from the FEMAT experiment (i.e., a set of functional relationships that was successfully applied across social settings in forested areas) to fit the drier grassland areas of the state. Our observations highlighted three key social-ecological differences between the CPE drylands and forested areas that complicated the translation effort.
(1) More diverse and variable characteristics. There is a perception that within the CPE there is a wider range of spatiotemporal variability in ecological, geomorphic, and hydrologic structures and processes than in forested areas (Wilhere 2020). Topics that repeatedly arose as contrasts to the forested areas included the dependence of CPE ecosystems on the seasonality of moisture, the uniqueness of riparian vegetation on the landscape, and a legacy of extensive hydrologic modification. The experts generated various possible definitions during the workshop, reflecting the diversity of their disciplinary backgrounds and individual experiences working at certain spatiotemporal scales or in particular dryland settings.
Site characteristics related to economic factors can be more variable in the CPE than in forested areas (where timber harvest is the primary source of income). The CPE agricultural land uses (including orchards, row crops, and grazing) are diverse and heterogeneous, leading to an array of possible cost scenarios associated with the loss of working land to restore riparian areas (Cole et al. 2020). This level of detail is difficult to quantify in a way that could be used to consistently represent the parcel-level cost, for instance, the economic cost to a farmer who removes a certain riparian buffer width from production.
(2) More diverse conservation actions. The targeted ecosystem functions for CPE riparian areas (improved sediment/pollutant removal via filtration or alluvial storage) depends on seasonal effects, complex subsurface flow patterns, and chemical exchange rates that have not been adequately quantified in semi-arid agricultural settings (Wilhere 2020). The relevant ecological factors do not have direct relationships with site-potential tree height; in fact, they can be enhanced in the absence of trees (Buchanan et al. 2020, Walton et al. 2020). The downstream effects of riparian practices on each parcel may not be as apparent with respect to filtration or storage functions as they might be for salmon habitat.
(3) Legacy of pervasive human impacts. Conversion to agriculture, combined with a legacy of highly altered hydrology in the CPE, has left many riparian areas in a highly degraded state. Many stream channels are incised, resulting in lower water tables, disconnected floodplains, shifts in species composition, reduced root mass and bank stability, and increased erosion (Wilhere 2020). In most areas, historical reference conditions are largely unknown and likely unachievable by protection alone, i.e., achieving them would likely require significant restoration (Wilhere 2020).
After observing the attempted translation of the FEMAT experiment from forested areas to grasslands, we inferred that steps could be outlined toward more intentional translation of localized water governance experiments to improve basin-level outcomes. We posited that ecological knowledge, if clearly communicated with the necessary degree of complexity, can help to determine or recognize elements of translatability, i.e., building blocks for facilitating the multi-level coordination and information-sharing that are essential for improving institutional fit with riverine ecosystems. From an ecological perspective, we asked how riverside areas are defined and how do the terms and definitions relate to the levels at which networked governance would potentially operate. Where are ecological conditions, land use, and policies similar or different among watershed management units in the study area, and how might these spatial patterns relate to networked governance for translatability across watersheds within the Columbia River Basin? To address these questions, we took a deeper dive into the challenges and opportunities for translatability revealed by the case of Washington state’s approaches to riverside area governance.
Literature review to define elements of translatability
We posited that an idealized set of institutional relationships could facilitate information-sharing through a networked governance structure spanning sub-reach to river-basin extents. The institutional network would ideally operate dynamically at appropriate levels and spatiotemporal scales to not only respond to water problems but also to proactively share lessons learned from governance experiments throughout a river basin. We intersected our case study observations with literature on adaptive governance, water governance, and the ecology, hydrology, and geomorphology of riverine systems to conceptualize elements of translatability that could be studied empirically.
Review of definitions related to riverside areas
Terminology used in scientific versus policy language is often overlapping but different in purpose or scope, which can cause confusion when using science to inform coordinated actions (Chapman et al. 2020). For instance, policy definitions for guiding actions on the ground are often context-specific, which makes them difficult to translate to sites in other settings. Ecological definitions of riparian areas (e.g., to advance understanding of flows and interactions) tend to be more conceptual and thus more generalizable to an array of contexts. Clear and consistent use of both types of definitions in concert “across the concept-application spectrum” (Knight et al. 2006) could in theory help to facilitate spatially coordinated actions.
In a snowball-style review of the scientific and management literature, we selected dominant definitions and important shifts in perception to evaluate patterns in the language used to refer to riverside areas. We collected and analyzed 52 definitions including biological, ecological, policy/management, and traditional ecological knowledge (TEK) perspectives. To incorporate multidisciplinary perspectives, we included definitions referring to riparian areas, ecotones, ecosystems, zones, habitat, vegetation, communities, or zones of influence; aquatic-terrestrial transition zones, interfaces, or interactions; floodplains or hyporheic flows or exchange; riverine areas, corridors, ecosystems or systems. We organized the definitions by timing of publication as well as attributes from the language used in each definition source, including the area or concept being defined, the purpose of defining it, criteria provided to identify an area, and the spatial and temporal dimensions represented by those criteria (Table A1.1).
Based on the language in each article or report, we coded each definition with a set of qualitative coordinates to represent its position along the concept-application spectrum (modified from Knight et al. 2006). We used two axes: purpose, ranging from delineation of management zones (1) to advancing conceptual scientific understanding (10); and spatial extent, ranging from site-specific (1) to widely applicable (10). There is no inherent value associated with the numeric coding in this scheme. To code the purpose of each definition, we reviewed the language in the source article or report. In most sources, the purpose was explicitly stated; where implied, we summarized the implied purpose; if not mentioned, we inferred the purpose of the definition. Definitions intended to advance scientific understanding were coded with a 10; those intended to inform management zone delineation were coded with a 1. Where spatial dimensions were specified, definitions based solely on site characteristics were coded with a 1; definitions that could be applied to a riparian area in any location were coded with a 10. Definitions intended to incorporate broader-scale ecological factors into management zone delineation or to bring conceptual understanding of riverine ecosystems closer to an on-the-ground definition were coded with intermediate values, representing the degree to which those factors were integrated in the defining criteria. Definitions that would apply only within particular areas (e.g., applicable within a given ecoregion or land use type) were also coded with intermediate values, representing the degree of spatial specificity in the language as it would fall along that spectrum. All coded values are provided in Table A1.1.
To organize the definitions along the spectrum from concept to application, we created a scatter plot with axes x = Purpose, y = Extent. We divided the plot area into categories, such that paired values >7 are labeled as concept-focused, paired values <4 are labeled as application-focused, and the space in the center (referred to by Knight et al. 2006 as the “Knowledge-Action” space) where both values are intermediate (4–7) are labeled as bridging definitions. We then plotted each definition to illustrate its category in this scheme.
Characterization of the policy landscape
To examine spatial patterns in ecological and governance attributes with respect to translatability, we grouped ecological, land use, and applicable policy mechanisms into mappable landscape areas (i.e., discrete map units to inform conservation policy and planning; Brost and Beier 2012, Anderson et al. 2015, Jennings et al. 2020). Our first step was to list the “desired” outcomes related to riverside areas in Washington state, which we inferred from the laws or programs that apply to the study area (Table 1). To select appropriate scales for mapping, we considered the biophysical spatial scales and properties relevant to the identified ecosystem function or service (deduced from ecological literature) as well as the administrative levels of associated laws or programs. Most goals associated with these laws or programs are related to ecological processes spanning microhabitat to watershed or drainage basin scales. Most levels of administration include nested state and local units of government; some also involve federal- or tribal-level administration, and each involves different mechanisms or rules on private lands. We viewed the multiple levels of administration for the multiple desired outcomes as potential units of emergent networked governance.
We focused on mapping at three nested levels to intersect the spatial variability in ecological and land use characteristics with that of existing units of governance affecting riverside areas:
State, ecoregion, and watershed administrative units (Fig. A2.1). We selected the state as the upper level because many policies pertinent to riverine management on private lands in Washington either originate at the state level (e.g., Growth Management Act) or are federal laws administered by state agencies (e.g., Clean Water Act). The middle level was the focal ecoregion (CPE drylands), which has distinct social-ecological characteristics from the other ecoregions in the state as described above. The lower level was composed of Water Resource Inventory Areas (WRIAs; WA Ecology and DNR 2011), which are management units delineated by natural watershed boundaries (Washington State Water Resources Act of 1997). Together, the three levels comprise a simple model of a hierarchical system for examining environmental problems (Cosens and Gunderson 2018).
We first grouped the WRIAs into three ecological regions based on climate and forest cover (WDFW 2015). WRIAs with more than 20 percent forest cover were divided into east and west forested regions, because forests west of the Cascade Crest are more humid than those to the east, and Forest Practices Rules apply differently in the two areas (Section 222-16-010 of the Washington Administrative Code). WRIAs with less than 20 percent forest cover were categorized as drylands. We disregarded large urban areas because they are not directly relevant to the case study.
We next mapped the spatial footprints of five policies that influence riverside land use decisions on privately-owned lands with each targeting at least one ecosystem function or service (Table 2). The Voluntary Stewardship Program (VSP) under the Washington State Growth Management Act aims to maintain or enhance riparian ecosystem functions from a baseline of 2011 through voluntary actions by agricultural landowners (The William D. Ruckelshaus Center 2010, SCC 2020). Best Management Practices to mitigate nonpoint source pollution aim to improve the quality of impaired waters with Total Maximum Daily Loads listed under the Clean Water Act (1972). Forest Practices Rules apply to private forest landowners under Washington’s Forest Practices Habitat Conservation Plan (2006), which balances timber harvest with clean water and salmon recovery (Wilhere and Quinn 2018). Salmon recovery measures under the Endangered Species Act operate in part by identifying the ranges of listed species and their designated critical habitat. New or updated watershed plans are required for certain WRIAs by 2019 or 2021 under State Bill ESSB 6091, an update to the 1997 (State) Water Resources Act, aiming to ensure clean water availability for new development.
To map the footprints of the five policies, we acquired or created five map layers in ArcMap 10.7 (with attributed polygons). We then converted each polygon into a raster (30 x 30 m), such that every cell of a WRIA was assigned a value of 1 if the policy applies, or a value of 0 if it does not apply (Table 2). We then categorized WRIAs into areas by ecological region, number of applicable policies, and combination of policies to represent watersheds with certain sets of social-ecological characteristics (Fig. A2.1).
We identified four elements of translatability from the intersection of our observations of the case study and our review of the literature (Table 3): (1) multi-scale understanding of biophysical systems and multi-level institutional structures and processes involved in achieving shared goals (e.g., Fig. 1); (2) quantified functional relationships linking measurable site-scale features to the shared basin-level goals for the range of ecological and land use settings (e.g., FEMAT curves); (3) definition frameworks to relate ecological knowledge to the levels of potentially networked governance (e.g., Fig. 4); (4) mapping strategies to visualize emerging networked governance in spatial context (e.g., Rocha et al. 2020; Fig. 5).
Literature review to define elements of translatability
Review of definitions related to riverside areas
Of the 52 definitions, 16 plotted in the concept-focused space (8–10 on both axes) and 18 plotted in the application-focused space (1–3 on both axes) (Fig. 4). The remaining 18 definitions plotted in the space between concept and application. We categorized these 18 definitions as attempts to play a bridging role (Toomey et al. 2017, Kadykalo et al. 2021) by conveying ecological evidence to inform a governance system that coordinates actions to fit ecological scales. Definitions from articles that were intended to advance or convey ecological understanding of riverine systems tended to be highly conceptual, involving criteria that spanned spatial scales from millimeters to kilometers and temporal scales from minutes to millennia. Definitions written to inform policy or management implementation were typically specific to an ecosystem function, involving criteria that were more discrete in space and time. Both concept- and application-focused definitions were repeatedly addressed and refined in the research and management literature from 1953 to present; we found no consistent directional trends in the types of definitions being discussed in the literature through time.
Characterization of the policy landscape
Our simple GIS analysis of policy mechanisms organized patterns in ecosystem functions into three different types of social-ecological areas for the CPE. Each watershed has a certain combination of policy mechanisms that apply (Fig. 5; Fig. A2.1 for details and full mapping extent). Area Type I (three watersheds) shared policies focusing on riparian ecosystem functions and salmon recovery. Area Type II (two watersheds) shared policies focusing on clean water and either riparian ecosystem functions in general or salmon recovery in particular. Area Type III (ten watershed units) shared policies focusing on riparian ecosystem functions, clean water, and salmon recovery. This map coarsely shows which ecological functions may be most important to relate to site-scale biophysical characteristics within each watershed unit.
We identified four conceptual elements of translatability to add clarity to the literature in adaptive water governance, drawing from existing literature and our case study. Synthesizing current knowledge into cross-sectoral, multi-scale understanding of biophysical systems and multi-level institutional arrangements involved in achieving shared basin-level goals (e.g., Fig. 1) can be used to identify the most relevant scales, levels, structures, and processes to address a water governance challenge. Establishing functional relationships between measurable site-scale features and the shared basin-scale goals (Fig. A2.1, Background) requires consideration of both institutional and ecological structures and processes, including how each varies spatially within the river basin (e.g., Figs. 2 and 3). Arranging relevant scientific and management terminology (definitions) along a concept-application spectrum (Fig. 4) provides a definition framework to relate ecological knowledge to the levels of potentially networked governance, clarifying how each type of knowledge can be applied to connect actions along river networks. Intersecting ecological landscape characteristics with existing institutional relationships in mapping strategies (e.g., Fig. 5) highlights potential spatial opportunities and challenges for translating governance experiments across settings and scales. These elements of translatability can be examined empirically to gauge the capacity of current water governance systems (specifically bridging organizations; Olsson et al. 2007) to coordinate governance across heterogeneous landscapes, improve fit with riverine ecosystems, and thus increase the likelihood of achieving shared basin-level goals.
The Washington state case study involved a set of functional relationships that were successfully translated across settings with similar land uses, ecological characteristics, and conservation strategies (forested areas with timber operations and riparian harvest restrictions) but have been challenging to translate to areas with different and more diverse characteristics (dryland areas, highly modified for various agricultural uses, and diverse riparian conservation strategies). The state agency leading the translation effort recognized the value of functional relationships as a basis for synthesizing scientific knowledge and applying it in various decision-making contexts to provide geographic continuity of protections that are necessary to achieve shared basin-level goals (Wilhere and Quinn 2018). A translatable set of relationships would ideally be adaptable to span the range of biophysical settings, land uses, conservation strategies, and desired outcomes in the river basin while being specific enough to inform decision-making processes in each setting. We suggest that a more complex array of structure to function relationships could be generated to support translatability across the social-ecological settings of the CPE drylands but developing these relationships would require motivation to fund many scientific studies (Fig. A2.1).
Clearly relating definitions across perspectives and purposes can help to determine how current knowledge could contribute to translatability (as network governance emerges) or make it clear where knowledge gaps inhibit translation. To outline a framework for relating ecological knowledge to the levels of potentially networked governance in the study area, we plotted riverside-related definitions from the scientific and management literature in concept-application space (Fig. 4). Concept-focused ecological definitions, for example, can indicate the key spatiotemporal scales at which actions should be coordinated to achieve basin-level goals. Bridging definitions may help to identify areas where social-ecological settings are similar (i.e., governance experiments may be translatable between them) or different (i.e., significant changes to the governance approach would likely be needed to achieve shared goals.) Bridging definitions can also highlight key intermediate levels for coordinated actions (such as watershed or cross-watershed initiatives) or highlight gaps that could be filled by bridging organizations (Sayles 2018). Bridging definitions may also help track ecosystem health at the mesoscale (e.g., to inform and assess watershed-scale initiatives; Stahl et al. 2021). Application-focused definitions can be synthesized to link measurable site characteristics to the ecological factors most relevant for advancing toward shared broader-scale goals (as did the FEMAT curves in forested areas).
We suggest that each type of ecological definition (i.e., conceptual, applied, and bridging) plays an important ongoing role in science and governance. Consistent with this idea, we found no directional temporal trends in the types of riverine area definitions appearing in publications. Current knowledge gaps include bridging ecological definitions that can systematically relate watershed-scale conditions and decision-making processes to the desired state, spanning the knowledge-action space described by Knight et al. (2006). Regardless of the type of ecological definition, we underline the importance of clearly and consistently selecting terminology to communicate effectively with policymakers, practitioners, or community members (Cvitanovic et al. 2016, Dufour et al. 2019, Norström et al. 2020). Beyond this study, examining the terminology related to a water problem can clarify the potential role of each type of information in a governance framework that supports translatability.
Understanding the spatial arrangement of social-ecological settings and cross-scale or cross-level interactions is crucial when considering the translatability of governance experiments at the river basin level. We took a first step (albeit simple) toward landscape characterization through the lens of translatability in the case study of riverside governance in the drylands of eastern Washington state. To show where nested sets of intersected “eco-policy” spatial relationships apply (or where different sets of relationships are needed) required landscape categorization and policy classifications that are similarly nested. (Fig. 1, Table 1, Fig. A2.1). We selected the levels and scales at which water governance institutions and riverine ecosystems show signs of spatial fit (to some degree): Washington state, which spans coastal to inland and forested to dryland ecosystems within the Columbia River Basin; the drylands of the CPE, which has distinct ecological and land use characteristics from the rest of the state and spans multiple watersheds; and watershed management units (WRIAs) within the CPE, each of which is managed with consideration of a different set of stakeholder interests and where different policies may apply. Within each group of similar watersheds, the best available science could be applied (or solicited) by bridging organizations to establish relationships between site-scale biophysical characteristics and desirable ecosystem functions. Displaying this synthesis of existing knowledge on the landscape enabled us to simplify some of the complexity and highlight key factors for translatability in an empirical setting. Spatial visualization of social-ecological systems rather than ecosystems alone might lead to more transferable outcomes by incorporating real-world factors (Rocha et al. 2020) that affect decision-making and ecological responses related to water quality, quantity, and connectivity throughout river networks.
Mapping in empirical context offers an opportunity to explore spatial patterns that emerge with different approaches to categorization. In our classification (Fig. A2.1), for example: What are the policy mechanisms that may affect water quality in dryland watersheds, and what role might these play in salmon recovery (by impacting aquatic habitat at the basin scale) if further coordinated by bridging institutions (such as the Upper Columbia Salmon Recovery Board, a boundary-spanning NGO) in an emerging networked water governance system? Many other landscape factors can be mapped to incorporate into spatial categorization, guided by the water governance issue and setting. A more complete representation of the social-ecological landscape could include more detailed (finer resolution) land use data, hydrogeomorphic models (derived via GIS analysis from streamflow data or models; e.g., Thoms et al. 2018).
This study is one example of an infinite number of possible approaches to inform the translation of experiments in adaptive water governance to other settings and across scales. The elements of translatability that we identified are generalizable to other areas but likely incomplete; empirical studies in other water governance contexts may reveal different or alternative elements to be most important. Our review of definitions in the literature was limited to those pertaining to riparian areas, thus covering only a small fraction of the hydrologic, geomorphic, and biological systems that affect water governance institutional processes and outcomes. Our mapping exercise was no doubt an oversimplification of the social-ecological system and the governance structure affecting riverside areas in Washington. However, we view this as a first step toward informing more intentional institutional networking to broaden the applicability of innovative water governance approaches (Biggs et al. 2012, Chaffin et al. 2016b, Pahl-Wostl 2019).
If more realistic spatial models of the social-ecological landscape can be constructed for a given SES, existing relationships among polycentric units of governance may become more transparently related to gaps in spatial coordination that are critical for achieving shared basin-level goals. For example, in the case study, the diverse entities affecting riparian practices compose a complex, interconnected hierarchy, including the Forest Practices Board, the Commissioner of Public Lands, Washington’s state legislature, the governor, federal and state agencies, Tribes or First Nations, two dominant political parties, local governments, nonregulatory local government agencies, individual landowners, and an array of nongovernmental organizations with various interests, approaches, and levels or scales of influence. We view the FEMAT-based governance experiments as an element of translatability that has emerged from that complex, interconnected hierarchy. They illustrate an approach to maintaining a tighter coupling between science and policy, while allowing for contextualization (i.e., local tailoring of practices, the inclusion of local knowledge and local stakeholder interests) to be applicable and socially acceptable across settings. Tailoring policy to every describable social-ecological system is infeasible (Craig et al. 2017), but supporting the emergence of networked water governance to address water problems and balance interests with legitimacy across levels and scales may be much more feasible (Cosens 2013). The concept of translatability provides a way for current ecological knowledge to support such shifts toward more adaptive water governance.
SUMMARY AND CLOSING THOUGHTS
Translatability in adaptive water governance represents a SES’ capability to disseminate knowledge in a way that improves spatial fit between institutional and ecological structures and processes in other contexts. We found that the translation of successful water governance experiments to new settings requires an understanding of the changing variables across heterogeneous social-ecological landscapes and frameworks for information-sharing. Current knowledge can inform intentional steps to set up governance experiments to be translatable to other settings, noting that contextual differences might not allow successful translation in all cases. Our case study illustrates one approach to evaluating relevant terminology and social-ecological system characteristics to consider challenges and opportunities for translatability. This information might be well known by individuals in the management community but has not been articulated and mapped systematically. Without effective synthesis and communication between scientists and policy groups, this knowledge would only be available on a piecemeal basis and might vary unknowingly among managers. We provide a simple, empirical approach to social-ecological-systems thinking to identify the building blocks for improving biophysical fit in an existing polycentric governance system. We believe that framing water problems with concept-focused, application-focused, and bridging ecological definitions can help link existing polycentric units of governance using scientifically sound principles and evidence. Mapping key social-ecological landscape characteristics that affect translatability in the study area helped to identify areas with shared or contrasting settings that may indicate where governance experiments may or may not be easily shared as well. While the details may differ, similarly complex, intertwined governance systems influence land use decision-making in many countries. Recognizing the emergence of opportunities to contribute cross-scale scientific knowledge to the scaffolding of environmental policies may trigger innovations to refine the adaptive governance of ecosystem services.
To further develop the capacity to translate lessons learned from governance experiments to other social-ecological settings and scales, we suggest several avenues for future research and application. The first is to pursue empirical studies that reveal patterns in the translatability of policies or informal governance approaches across social-ecological settings. Empirical data from attempted translations enables us to recognize existing elements of modularity and the ability to adjust to heterogeneous social-ecological landscapes. Comparing examples of successes versus failures in a governance experiment can contribute to learning about some of the variables that can advance or preclude shifts toward adaptive water governance. The second is to develop strategies for clearly communicating the current state of biophysical understanding in forms that are compatible with existing policy mechanisms at multiple levels and spatial extents. Without this knowledge in a useful format, we may fail to recognize existing examples of improved biophysical fit, bridging organizations that could play key roles, or windows of opportunity for transformation (Olsson et al. 2007, Chaffin et al. 2016b). The third is to empirically evaluate the effectiveness of existing elements of environmental governance that were intended to improve institutional fit with biophysical systems, e.g., WRIAs, Landscape Conservation Cooperatives in the USA (Merritts 2016), European Water Framework Directive (Moss 2012, Voulvoulis et al. 2017). Finally, empirical work at the community level can recognize and draw attention to opportunities to facilitate more inclusive, bottom-up governance (e.g., the Voluntary Stewardship Program in Washington state) alongside a biophysical emphasis on the importance of incorporating local knowledge and conditions in policy processes. We suggest that this type of transdisciplinary work can contribute to the “best available science” that informs policy to be adaptable and translatable as adaptive water-governance approaches continue to emerge.
RESPONSES TO THIS ARTICLE
Responses to this article are invited. If accepted for publication, your response will be hyperlinked to the article. To submit a response, follow this link. To read responses already accepted, follow this link.
We acknowledge the support of our institution for this work. This research was funded in part by the discretionary funds of A.K.F. A.T.S. received additional support from the Robert Lane Fellowship in Environmental Sciences, the Boeing Environmental Endowed Graduate Fellowship, the E. H. Steffen Fellowship and the Francis Rush Bradley Excellence Fund at Washington State University. Special thanks to George Wilhere and Timothy Quinn at the Washington Department of Fish and Wildlife, and Barbara Cosens for their invaluable contributions and insights during the writing and rewriting of this manuscript. We also thank the patient and insightful reviewers whose comments greatly improved the manuscript.
Data/code sharing is not applicable to this article because no new data/code were analyzed in this study. Map layers were generated from publicly available documents.
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Table 1. Ecosystem functions targeted by riparian conservation measures in the study area, ecological spatial scales of the underpinning biophysical systems, and levels of governance for existing laws or programs (Dufour et al. 2019, Riis et al. 2020, Wilhere 2020).
|Targeted ecosystem function or service
(Dufour et al. 2019, Riis et al. 2020)
|Example laws or programs that apply to the study area||Biophysical spatial scale(s) and properties relevant to ecosystem service provision & delivery||Administrative levels of existing laws or programs (collectively)|
|Streambank stability / erosion hazard mitigation (Montgomery 1997, Sweeney et al. 2004)||US National Forest Management Act requires management planning on national forest lands; Washington State Forests Habitat Conservation Plan and State Forest Practices Act (and Forests and Fish Agreement) regulate commercial timber harvest||Microhabitat to reach-scale;
affected by surface and subsurface storage and flows
|Federal or state level; determined by ownership on public lands, different rules apply on private lands|
|Flood attenuation / hazard mitigation (Tockner and Stanford 2002)||Washington State Water Resources Act requires the preparation of watershed management plans||Microhabitat to watershed-scale;
accumulative, requires floodplain connectivity, includes surface and subsurface storage and flows
|Nested state and watershed levels|
|Water supply / alluvial storage or groundwater recharge (Tockner and Stanford 2002)||Washington State Growth Management Act requires local governments to prepare comprehensive plans that meet certain criteria including plans to maintain or enhance Critical Areas (the Voluntary Stewardship Program offers an alternative option to agricultural counties)||Microhabitat to watershed-scale;
accumulative, requires floodplain connectivity, includes surface and subsurface storage and flows
|Nested state and local government levels; site-based actions can be evaluated at local-government extent to satisfy requirements|
|Clean water / pollutant removal
(Sweeney et al. 2004, Naiman et al. 2005)
|US Clean Water Act (Total Maximum Daily Load) indicates Best Management Practices to mitigate nonpoint source pollution||Microhabitat to drainage basin scale; species-dependent, land-use-dependent, geographically continuous, accumulative, requires floodplain connectivity, affected by surface and subsurface storage and flows||Nested federal and state levels;
determined by watershed, varies with ecological condition, land use, ownership
|Species conservation / biodiversity
(Hilty et al. 2006, Naiman et al. 2012)
|US Endangered Species Act protects Critical Habitat for listed species, e.g., salmonids||Microhabitat to drainage basin scale; species-dependent, land-use-dependent, geographically continuous, accumulative, requires floodplain connectivity, affected by surface and subsurface storage and flows||Nested federal and state or tribal levels; determined by ecological requirements of species or population, varies with land use, ownership|
|Shading by canopy / water temperature regulation (Naiman et al. 2012, Sweeney and Newbold 2014)||US Endangered Species Act protects Critical Habitat for listed species, e.g., salmonids||Reach to drainage basin scale; species-dependent, geographically continuous, accumulative, may require floodplain connectivity,
affected by surface and subsurface storage/flows
|Nested federal and state or tribal levels; determined by ecological requirements of species or population, varies with land use, ownership|
Table 2. Cell values assigned to rasters generated to spatially stack applicable policies.
|Policy or Program||Targeted ecosystem function or service||Value of 1||Value of 0||Source|
|Voluntary Stewardship Program (State Growth Management Act)||Streambank stability, alluvial or groundwater recharge, pollutant removal, species conservation, shading||WRIAs with ≥20% land in agricultural use, in participating counties||WRIAs with <20% agricultural land or not overlapping with participating counties||WDFW (2015), SCC (2020)|
|US Clean Water Act||Pollutant removal||WRIAs with at least one TMDL||WRIAs with no TMDLs||WA Ecology and DNR (2011)|
|State Forest Practices Habitat Conservation Plan||Species conservation, pollutant removal, shading||WRIAs with >20% forest cover||WRIAs with ≤20% forest cover||WDFW (2015)|
|US Endangered Species Act||Species conservation, pollutant removal, shading||WRIAs overlapping at least one mapped Evolutionary Significant Unit of a listed salmonid population (NOAA 2005)||WRIAs with no Evolutionary Significant Units mapped||NOAA (2005)|
|State Water Resources Act||Flood hazard mitigation, water supply conservation||WRIAs where updated watershed planning is required||WRIAs with no new watershed planning requirements||ESSB 6091 †|
|† Washington State Senate Bill 6091 - 2017–18, available from https://app.leg.wa.gov/billsummary/?BillNumber=6091&Year=2017.|
Table 3. Four elements of translatability identified in the literature review and guided by observations.
|Element of translatability||References||Examples|
|Multi-scale understanding of biophysical systems and multi-level institutional structures and processes involved in achieving shared goals||Cumming et al. 2006, Lemos and Agrawal 2006, Moss 2012, Fremier et al. 2013, Falk et al. 2018||Description of the geologic and ecological processes and services related to shared goals of improved water quality or salmon recovery in the Columbia River Basin (Fig. 1)|
|Quantified functional relationships linking measurable site-scale features to the shared goals or desired state for the range of ecological and land use settings spanned by the system (e.g., large river basin)||FEMAT 1993, Craig et al. 2017, Wilhere and Quinn 2018||Relationships based on tree heights developed by the FEMAT team to inform decision-making about riparian timber harvest in Washington State (Background); maps showing ecological setting and land use variability across the state (Fig. 2; Dufour 2019)|
|Definition frameworks to relate ecological knowledge to the levels of potentially networked governance||Crowder et al. 2006, Ekstrom and Young 2009, Keeley et al. 2022||Categorization of scientific/management definitions pertaining to riparian areas by extent and purpose (Fig. 4)|
|Mapping strategies to visualize emerging networked governance in spatial context||Ecological-management landscape units: Brost and Beier 2012, Anderson et al. 2015, Jennings et al. 2020
Social-ecological landscape units: Alessa et al. 2008, Martín-López et al. 2017, Rocha et al. 2020
|Spatial categorization of water resource management units based on ecological setting and groups of applicable policies related to different components of the shared desired state of the system (Fig. 5)|