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Keywords:

  • Biodiversity;
  • comanagement;
  • cross-scale interactions;
  • human-environment systems;
  • Natura 2000;
  • public participation;
  • scale;
  • Scotland;
  • Special Area of Conservation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

There is general acceptance that biodiversity management should be adapted to ecological scale but only recently has the precise role of scale in participatory biodiversity governance begun to be explored. We investigated stakeholder perceptions in three case studies of biodiversity management planning to understand the effect of framing a management response according to the ecological and social scale of the problem on (i) participatory processes and (ii) their social and ecological outcomes. Perceptions of success were highest in the case study where stakeholder involvement reflected the perceived ecological scale of the problem. Other factors contributing to successful outcomes were identified, including effective boundary spanning and mutual recognition of conservation conflicts. Failure to take the latter into account, and to align management responses with socioecological scale, may jeopardize long-term sustainability of biodiversity.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

The current tenet underpinning the conservation of biodiversity in human–environment systems is scale-adapted governance (Newig & Fritsch 2009; Buizer et al. 2011; Kok & Veldkamp 2011). Stakeholder participation in decentralized management processes has been adopted by many policy jurisdictions due to the substantive and instrumental benefits it supposedly generates (Carlsson & Berkes 2005; Young et al. 2012). Participation also takes place at local or regional levels for practical reasons (Newig & Fritsch 2009) and brings together diverse stakeholders, potentially strengthening the quality and acceptance of decisions (Harrison & Burgess 2000; Parkins & Mitchell 2005). However, stakeholders have different and potentially conflicting definitions of problems that, if ignored, can lead to flawed processes and ineffective outcomes (Young et al. 2013). These conflicting definitions can often be traced to the ways in which individuals and groups frame the problem and the scale at which it occurs (Lebel et al. 2005; Cash et al. 2006). Framing is “the interpretation process through which people construct and express how they make sense of the world around them” (Gray 2003, p. 12). Scale framing is the way in which people represent an issue in terms of a particular scale, which may significantly influence participation (Richards et al. 2004; Rockloff & Moore 2006).

Biodiversity and other common resources are affected by problems that span multiple scales, including spatial, temporal, jurisdictional, institutional, management, network, and knowledge (Cash et al. 2006). Human–environment systems operate through complex and multiple interactions between and within these scales (Adger et al. 2005; Berkes 2006; Cash et al. 2006; Young 2006). Although the political geography literature has examined the “politics of scale” (Lebel et al. 2005), it has focused principally on social and political scaling processes and less on the characteristics of environmental processes (Padt & Westerink 2012). Recent studies adopting a social-ecological systems perspective have, however, examined the problem of fit and of scale mismatches between institutions and systems (Olsson et al. 2006; Ostrom 2009) when incorporating social and ecological considerations into conservation practice (Lee 1993; Cumming et al. 2006; Folke et al. 2007). Participation, comanagement, and transdisciplinarity are being advocated as solutions to challenges of social-ecological systems and scale (Cash et al. 2006; Rockloff & Moore 2006; Armitage et al. 2009; Apostolopoulou & Paloniemi 2012; Young & Marzano 2012). The way in which scale is framed in policy-making may, however, result in the misfit of management interventions (Cash et al. 2006), for example, in the implementation of the Water Framework Directive (Borowski et al. 2008). It is important therefore to understand the effects of scale framing in biodiversity management planning and implementation processes to achieve socially and ecologically sustainable outcomes. There is, however, scant empirical evidence on the complex relationship between scale framing and participatory approaches to biodiversity management.

This article contributes to an emerging literature on scale and governance (e.g., Newig & Fritsch 2009; Kok & Veldkamp 2011) and on scale framing (Termeer et al. 2010; van Lieshout et al. 2011) by presenting a novel interdisciplinary evaluation of stakeholder involvement in three case studies where biodiversity management was undertaken at different scales. We hypothesized that criteria relating to process, social, and biodiversity outcomes were more likely to be evaluated positively where the scale of the management response was framed according to the scale of the socio-ecological problem (Figure 1). We evaluated stakeholder involvement using an analytical framework derived from public participation evaluation theories, specifically Rowe and Frewer (2000) and Beierle and Konisky (2001), and adapted to reflect the specific aims of the European Union Natura 2000 network. The framework incorporates 13 criteria (see Annex A of the Supporting Information) that were used, drawing on both qualitative and quantitative data, to analyze the relationship between scale framing, stakeholder involvement processes, and the direct (criterion 13) and indirect (criteria 7–12) links in terms of biodiversity conservation (Young et al. 2013). We discuss the implications of this analysis for the management of biodiversity across multiple scales.

image

Figure 1. Conceptual model illustrating the potential relationship between scale framing and the process, social, and biodiversity outcomes of involving stakeholders in the development of management plans.

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Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Study system

Natura 2000 is a European ecological network of protected sites comprising Special Protection Areas (SPAs) and Special Areas of Conservation (SACs) established under the EU Birds and Habitats Directives, respectively. Active steps are taken to reconcile biodiversity conservation with “economic, social, and cultural requirements” (Article 2(3) of the Habitats Directive). Member States are required to establish conservation measures—e.g., management plans, statutory, administrative, or contractual measures—when sites are designated as SACs. The integration of local actors into the management plan process is seen as best practice (European Commission 2000).

A multiple-case design following theoretical replication logic was adopted for this study, with one case study at each spatial scale. Case studies were all SACs that (1) had a management plan that required the active involvement of a range of local stakeholders in its development and/or implementation; and (2) reflected different contexts of stakeholder involvement, namely, different scales. They comprised:

  1. One microscale case study: The River Bladnoch SAC Atlantic Salmon Catchment Management Plan. This is a single site (SAC) unit covering an area of 3 km2. The river Bladnoch and its tributaries were designated as an SAC in 2005 for their population of Atlantic salmon (Salmo salar), listed under Annex II of the Habitats Directive (JNCC 2009).
  2. One mesoscale case study: The Forth and Borders Moorland Management Scheme. This covers 12 sites totaling 280 km2. The scheme aims to maintain and improve moorland habitats and the species they harbor by helping landowners and managers promote good moorland management practices through individual management plans.
  3. One macroscale case study: The Moray Firth Seal Management Plan. This covers seven SACs totaling 5,230 km2. The Moray Firth was designated for its harbor seal (Phoca vitulina) and Atlantic salmon (Salmo salar) populations, listed under Annex II of the Habitats Directive. The Moray Firth Seal Management Plan was developed in 2005 to address the conflict between seal conservation and salmon fisheries (Butler et al. 2008). Only in this case study was the scale framing of the plan explicitly addressed.

Data collection and analysis

Our hypotheses were as follows:

  • -
    The process of stakeholder involvement is more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 1).
  • -
    Social outcomes are more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 2).
  • -
    Biodiversity outcomes are more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 3).

To test the hypotheses, 59 semistructured interviews were carried out from January to July 2009 (Table 1). The selection of initial interviewees followed a purposive sampling strategy designed to ensure that the views of each of the main types of stakeholder were included. Further contacts within the stakeholder network associated with each of these sites were extended through a process of “snowball” or chain referral sampling (Lewis-Beck et al. 2004). Semistructured interviews elicited interviewees’ experiences of developing the management plan and their perceptions of the social and biodiversity outcomes (see Annex B of the Supporting Information for a full interview guide). The interviews also included a scoring exercise, with stakeholders asked to score on a scale from 1 to 5 (five being the highest) the 13 evaluation criteria (Annex A of the Supporting Information). Half-point scores were allowed, which means that criteria were effectively scored on a nine-point scale. Three of the process characteristics (“transparency,” “early involvement,” and “cost-effectiveness”) and one social outcome characteristic (“implementation”) were excluded from the quantitative analysis due to large numbers of missing responses from interviewees in these categories (see Annex C in Table S1 of the Supporting Information for summary of responses). All interviews were transcribed verbatim and coded using NVivo qualitative data analysis software (QSR International 2010).

Table 1. Breakdown of interviewees in each case study: the first letter refers to the case study (B = Bladnoch; M = Moray Firth; F = Forth and Borders Moorlands); the middle letters refer to the stakeholder group: GA = government and government department representatives, i.e., local and regional stakeholders responsible for implementing or regulating biodiversity policy; SA = scientific and technical advisers, i.e., local or regional scientists external to governmental bodies (e.g., university, independent research organizations); BU = biodiversity users, i.e., local stakeholders who were affected by or involved directly in the management of the target species/habitats in the protected areas such as farmers, fishermen, fishery managers, foresters, and local businesses)
Interviewee backgroundBladnochMoray FirthForth and Borders MoorlandsTotal
Representatives of the Scottish government or government departmentsBGA1-BGA5MGA1-MGA4FGA1-FGA615
Scientific advisersBSA1-BSA2MSA1-MSA6FSA1-FSA412
Biodiversity usersBBU1-BBU12MBU1-MBU10FBU1-FBU1032
Total19202059

We analyzed the quantitative interview data to detect whether differences between case studies in terms of participants’ perceptions of process, social, and biodiversity outcomes existed. Specifically, we tested whether scored perceptions of process characteristics (Hypothesis 1), social outcomes (Hypothesis 2), and biodiversity outcome (Hypothesis 3) differed between case studies. We fitted statistical models to each of these nine variables, and, in each case, tested for an effect of “case study” upon score. We used ordinal regression models, which treat the data as categorical and exploit the ordered nature of the response variable when performing regression analyses (Christensen 2011). The ordinal regression approach provides a parsimonious way of evaluating differences between the three different case studies (it does this using just two parameters) without needing to make the potentially unrealistic assumption that the scores lie on a genuinely numeric scale. The ordinal regression approach assumes, for example, that a score of three is higher than a score of two, but does not assume that the difference between scores of two and three is necessarily the same as the difference between scores of one and two. Ordinal regression methods are widely used in analyzing questionnaire responses that are, as here, in the form of a Likert scale (Norusis 2011). The ordinal regression models were fitted using the “clm” function within the “ordinal” package in R ( R Development Core Team 2011), and are based on the cumulative logit. Full model structure details are in Annex C of the Supporting Information.

A categorical variable denoting social group (government advisors, scientists, and biodiversity users) was included in all models to structurally account for any systematic differences in scoring between different groups of participants, which had previously been found to be important (Young et al. 2013). For each of the nine variables, we tested for differences between case studies by using a likelihood ratio test (with a chi-squared reference distribution and two degrees of freedom) to compare a model that included both case study and social group as categorical explanatory variables against a model that only included social group. If the likelihood ratio test showed evidence for significant differences between case studies, at the 5% level, then we interpreted these differences by looking at the estimates, standard errors, and confidence intervals for the pairwise differences between the three case studies (see Annex C in Table S2 of the Supporting Information for full model results).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

The process of stakeholder involvement is more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 1)

The quantitative analysis showed that “influence” had a highly significant relationship with case study (Table 2). Participants in the macroscale case study rated “influence” significantly more highly than those at the microscale and mesoscale case studies, while differences between the meso- and microscale case studies were small and nonsignificant (Table 3). “Representativeness” and “independence” did not differ significantly between the case studies (Table 2).

Table 2. Overall assessment of whether perceived process, social outcomes, and biodiversity outcomes, differ between the three case studies. For each perceived process or outcome characteristic, statistical significance was assessed by using a likelihood ratio test to compare a model that contains case study and stakeholder group against a model that only contains stakeholder group. Asterisk denotes the significance at the 0.05 (*), 0.01 (**), and less than 0.001 (***) levels
HypothesisPerceived process or outcome characteristicLikelihood ratioP-value
The process of stakeholder involvement is more likely to beRepresentativeness5.370.068
evaluated positively in the case study where scale is framedIndependence4.790.091
explicitly (i.e., the macroscale case study) (Hypothesis 1)Influence12.350.0021**
Social outcomes are more likely to be evaluated positively in theLearning4.710.095
case study where scale is framed explicitly (i.e., the macroscaleValues1.030.60
case study) (Hypothesis 2)Trust6.830.033*
 Technical quality14.560.00069***
 Conflict resolution5.180.075
Biodiversity outcomes are more likely to be evaluated positively in the case study where scale is framed explicitly (i.e., the macroscale case study) (Hypothesis 3)Biodiversity outcome0.310.85
Table 3. Model estimates and test statistics to summarize differences between case studies in perceived process, social and biodiversity outcomes, based on models that contain “case study” and “stakeholder type” as explanatory variables. This table presents results for those perceived outcomes that show statistically significant differences between case studies. Estimates represent estimated pairwise differences between each pair of case studies, together with associated standard errors, 95% Wald confidence intervals, and P-values. Asterisk denotes the significance at the 0.05 (*), 0.01 (**), and less than 0.001 (***) levels
Perceived outcomePairwise comparisonEstimateStandard error95% Confidence intervalP-value
InfluenceMeso–Micro0.140.87−1.56, 1.850.87
 Macro–Micro2.781.000.83, 4.730.0053**
 Meso–Macro−2.460.89−4.21, −0.720.0057**
TrustMeso–Micro1.150.87−0.55, 2.850.18
 Macro–Micro2.220.890.48, 3.960.012*
 Meso–Macro−1.240.81−2.83, 0.350.13
Technical qualityMeso–Micro−1.160.91−2.95, 0.620.20
 Macro–Micro2.961.320.38, 5.540.024*
 Meso–Macro−4.011.35−6.65, −1.360.0030**

The qualitative analysis showed that the process in the macroscale case study of framing the management plan around the conflict between seal conservation and salmon fisheries allowed the identification of all key actors. This was mainly achieved by one key individual who ensured adequate representativeness and inclusion of all relevant actors, acting as “an informed and trusted honest broker” [MGA2] who could “cross scales […] in terms of knowledge systems and also spatial scales” [MSA1]. The involvement of decision-makers (i.e., the Scottish Government) ensured that the scope of the plan had clear boundaries in terms of what stakeholders could and could not do, leading to a situation where “you had to stick to the rules—that was made quite clear and there was no grumbling about it” [MBU10]. Within these constraints, stakeholders were broadly able to voice their views and concerns, but no false expectations were raised. Despite the limits placed on it, the process was perceived as independent and driven by the grassroots, which was reflected in the level of influence stakeholders felt they had in the process.

This was in marked contrast with the micro- and mesoscale case studies. In the former, many affected landowners of the catchment, notably the private forest owners but also other significant stakeholders, were not involved, despite the local focus of the process. This was due to unclear goals of the plan, the execution of the process, and the perceived top–down nature of the plan. Similarly, in the mesoscale case study, one landowner remarked that during “the development stage of the scheme there was no input at all from our side, none whatsoever” [FBBU4]. Indeed, unless biodiversity users already had good relationships with government department representatives, opportunities for influence were perceived as poor.

Social outcomes are more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 2)

The quantitative analysis showed a highly significant difference between case studies in the scores given to the proposition that the process had improved the “technical quality” of decisions (Table 2). This variable was scored significantly more positively in the macroscale case study than in the micro- and mesoscale case studies, while the difference between the micro- and mesoscale case studies was nonsignificant (Table 3). There was also weaker, but still statistically significant, evidence for a relationship between “trust” and case studies (Table 2). In this case, scores for the proposition the process had increased trust were significantly higher for the macroscale case study than for the microscale case study, while the mesoscale case study showed no significant differences with either of the other case studies.

Although the quantitative data did not show a significant difference between case studies in scores for stakeholder learning, conflict resolution, and the incorporation of stakeholder values (Table 2), analysis of the qualitative data found that high-quality decisions that integrated local values were seen as an important outcome in the macroscale case study. This resulted in a situation where “it was the salmon guys working directly with the scientists and actually getting some robust data” [MBU1], thereby leading to acceptance of the science and buy-in to the management plan by fishermen and netsmen. Furthermore, this cooperation improved trust and reduced conflict by promoting learning of how different stakeholders framed the problems affecting them, and a broader understanding of the social and political context of the conflict.

In contrast, biodiversity users in the micro- and mesoscale case studies perceived power imbalances, one farmer commenting that the plan reflected “the values of those with the money rather than the values of the people on the ground” [BBU3], differentiating between the national-level organizations and the local stakeholders. The process led to frustration over the failure to adequately address or resolve conflicts (at the microscale, the conflict between salmon fisheries and silvicultural practices; and at the mesoscale between raptor conservation and grouse management), which led to mistrust in national government organizations. The fact that a Fisheries Trust was heavily involved in the microscale case study did help bridge knowledge scales and was evaluated positively by biodiversity users.

Biodiversity outcomes are more likely to be evaluated positively in the case study where scale is framed explicitly (Hypothesis 3)

Perceived biodiversity outcomes did not differ significantly between case studies (Table 2).

It was clear from the qualitative interview data that for all scales of case study, establishing direct biodiversity outcomes was made difficult by the complexity and uncertainty surrounding the ecology of the species for which the management plans were developed. Biodiversity users in both the micro- and mesoscale case studies had seen minor improvements to biodiversity in the short term but whether these changes were necessarily linked to their individual management, or to the management plans, was unclear.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

This study provides empirical evidence that scale framing may lead to a more sustainable governance of biodiversity through improved social outcomes. Our results also highlight other contextual factors linked to scale that may impact on perceived success of conservation efforts.

The most positively evaluated case study in terms of processes and social outcomes was the macroscale case study where scale was explicitly framed. Improved trust and reduced social conflict in the macroscale case study may, in turn, impact positively on the way in which biodiversity is managed (Young et al. 2013). The management plan in the macroscale case study reflected the broad spatial scale at which the problem (in this case, the conflict between seal conservation and salmon fisheries) was perceived by local stakeholders. Following from this innovative framing around the conservation conflict, the process of involving relevant stakeholders was determined. In the other case studies, where scale was not framed explicitly, processes and social outcomes of participation were less positively evaluated. In the microscale case study, where one might have expected better representation of stakeholders and their values (Richards et al. 2004; Rockloff & Moore 2006), some of the affected landowners residing outside the locality were not involved. In addition, power imbalances were perceived by biodiversity users, who also stressed mismatches in terms of knowledge scales. This highlights the importance of acknowledging the role, and socially constructed nature, of scale (Cash et al. 2006; Buizer et al. 2011; Kok & Veldkamp 2011; Mohan 2001) and the impact of scale frame mismatches (van Lieshout et al. 2011; Apostolopoulou & Paloniemi 2012).

Contextual factors linked to scale also exerted an important effect on perceptions of processes and social outcomes. Much of the “success” at the macroscale was achieved by the efforts of one individual who functioned as an effective “boundary-spanner” (Williams 2012) and tackled the challenges of larger scale comanagement processes (e.g., numerous interests, limited social learning), seeking stakeholder input, and creating joint ownership of the management plan. In the microscale case study, spanning knowledge boundaries was achieved by an institution, the Fisheries Trust, which incorporated local scientific knowledge and helped improve the technical quality of decisions. These findings support the comanagement principles emphasizing the importance of champions (Armitage et al. 2009; Young et al. 2012) but also highlight the potential role of institutions in building capacity. The important relationship between levels of governance and socioecological scales was also highlighted in the macroscale case study, where the involvement of national-level actors, providing clear boundaries on the scope of the plan and their involvement, and supporting long-term capacity building, was seen by stakeholders as essential to the success of the process (Young et al. 2012).

Finally, this study highlights the important links between conflicts and scale. All case studies were embedded in conservation conflicts; however, only the macroscale case study was conflict explicitly acknowledged and addressed, resulting in a scale-adapted approach involving all relevant stakeholders. The relations that form the focus of “local” conflicts are rarely confined to the local scale but are connected in various ways to wider scales and patterns of political relationships and of biodiversity use (Meadowcroft 2002). Successful stakeholder involvement in biodiversity management depends on the mutual recognition of biodiversity conflicts (Redpath et al. 2013) and, while not widely discussed in the literature, the framing of management responses around socioecological conflicts may be an approach to sustainable scale-adapted biodiversity governance (Gray 2003).

To conclude, we need to examine scale framing processes constructively and deliberately in biodiversity management planning and implementation processes to reduce conflict and achieve socially legitimate and ecologically sustainable outcomes. Otherwise there is a risk that policy may outstrip the evidence on the role of scale in biodiversity management (Cash et al. 2006; Young 2006).

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

This article was supported by NERC CEH (Project NEC04049). We thank all interviewees and external experts who took part in this research. We also thank David Elston (BIOSS), Adam Vanbergen (CEH) and three anonymous reviewers for their valuable comments on an earlier draft of this manuscript.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information
  • Adger, W.N., Brown, K. & Tompkins, E.L. (2005). The political economy of cross-scale networks in resource co-management. Ecol. Soc. 10, 9.
  • Apostolopoulou, E. & Paloniemi, R. (2012). Frames of scale challenges in Finnish and Greek biodiversity conservation. Ecol. Soc. 17, 9.
  • Armitage D.R., Plummer, R. Berkes, F. et al. (2009). Adaptive co-management for social–ecological complexity. Front. Ecol. Environ. 6, 95-102.
  • Beierle, T.C. & Konisky, D.M. (2001). What are we gaining from stakeholder involvement? Observations from environmental planning in the Great Lakes. Environ. Plan. C 19, 515-527.
  • Berkes, F (2006). From community-based management to complex systems: the scale issue and marine commons. Ecol. Soc. 11, 45.
  • Borowski, I., Le Bourhis, J P. Pahl-Wostl, C. & Barraque, B (2008). Spatial misfit in participatory river basin management: effects on social learning, a comparative analysis of German and French case studies. Ecol. Soc. 13, 22.
  • Buizer, M., Arts, B. & Kok, K. (2011). Governance, scale and the environment: the importance of recognizing knowledge claims in transdisciplinary areas. Ecol. Soc. 16, 21.
  • Butler, J.R.A., Middlemas, S.J., McKelvey, S.A. et al. (2008). The Moray Firth Seal Management Plan: an adaptive framework for balancing the conservation of seals, salmon, fisheries and wildlife tourism in the UK. Aquat. Conserv. 18, 1025-1038.
  • Carlsson, L. & Berkes F. (2005). Co-management: concepts and methodological implications. J. Environ. Manage. 75, 65-76.
  • Cash, D.W., Adger, W.N., Berkes, F. et al. (2006). Scale and cross-scale dynamics: governance and information in a multilevel world. Ecol. Soc. 11, 8.
  • Christensen, R.H.B. (2011). Analysis of ordinal data with cumulative link models – estimation with the R-package ‘ordinal’. http://cran.r-project.org/web/packages/ordinal/vignettes/clm_intro.pdf. Accessed 11 July 2012.
  • Cumming, G.S., Cumming, D.H.M. & Redman, C.L. (2006). Scale mismatches in social-ecological systems: causes, consequences, and solutions. Ecol. Soc. 11, 14.
  • European Commission. (2000). Managing Natura 2000 sites, the provisions of article 6 of the Habitats Directive 92/43/CEE. http://ec.europa.eu/environment/nature/natura2000/management/docs/art6/provision_of_art6_en.pdf. Accessed 11 July 2012.
  • Folke, C., Pritchard, L. Jr., Berkes, F., Colding, J. & Svedin, U. (2007). The problem of fit between ecosystems and institutions: ten years later. Ecol. Soc. 12, 30.
  • Gray, B. (2003). Framing of environmental disputes. Pages 11-34 in R.J. Lewicki, B. Gray, M. Elliott, editors. Making sense of intractable environmental conflicts. Island Press, Washington, DC.
  • Harrison, C. & Burgess, J. (2000). Valuing nature in context: the contribution of common-good approaches. Biodivers. Conserv. 9, 1115-1130.
  • JNCC. 2009. UK SAC site list: River Bladnoch site details. http://www.jncc.gov.uk/protectedsites/sacselection/sac.asp?EUCode=UK0030249. Accessed 23 August 2010.
  • Kok, K. & Veldkamp, T.A. (2011). Scale and governance: conceptual considerations and practical implications. Ecol. Soc. 16, 23.
  • Lebel, L., Garden, P. & Imamura, M. (2005). The politics of scale, position, and place in the governance of water resources in the Mekong region. Ecol. Soc. 10, 18.
  • Lee, K.N. (1993). Greed, scale mismatch, and learning. Ecol. Appl. 4, 560-564.
  • Lewis-Beck, M.S., Bryman, A. & Liao, T.F. (2004). The Sage encyclopaedia of social science research methods. Thousand Oaks, London.
  • Meadowcroft, J. (2002). Politics and scale: some implications for environmental governance. Landscape Urban Plan. 61, 169-179.
  • Mohan, G. (2001). Beyond participation: strategies for deeper empowerment. Pages 153-167 in B. Cooke, U. Kothari., editors. Participation: the new tyranny? Zed Books, London.
  • Newig, J. & Fritsch, O. (2009). Environmental governance: participatory, multi-level – and effective? Environ. Policy Gov. 19, 197-214.
  • Norusis, M. (2011). IBM SPSS statistics 19 advanced statistical procedures companion. Pearson Education, US.
  • Olsson, P., Folke, C., Galaz, V., Hahn, T., Schultz, L. (2006). Enhancing the fit through adaptive co-management: creating and maintaining bridging functions for matching scales in the Kristianstads Vattenrike Biosphere reserve, Sweden. Ecol. Soc. 12, 28.
  • Ostrom, E. (2009). A general framework for analyzing sustainability of socio-ecological systems. Science 325, 419-422.
  • Padt, F.J.G. & Westerink, J. (2012). Addressing scale in open space preservation: learning from the Hague region in the Netherlands. Tijdschrift voor Economische en Sociale Geografie. Published online May 9, 2012.
  • Parkins, J.R. & Mitchell, R.E. (2005). Public participation as public debate: a deliberative turn in natural resource management. Soc. Nat. Resour. 18, 529-540.
  • QSR International. (2010). NVivo 9 QSR International, Melbourne, Australia.
  • Redpath, S.M., Young, J., Evely, A. et al. (2013). Understanding and managing conservation conflicts. Trends Ecol. Evol. 10.1016/j.tree.2012.08.021.
  • R Development Core Team. (2011). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0.31.
  • Rowe, G. & Frewer, L.J. (2000). Public participation methods: a framework for evaluation. Sci. Technol. Hum. Val. 25, 3-29.
  • Richards, C., Sherlock K. & Carter, C. (2004). Practical approaches to participation. SERP policy brief no.1. Macaulay Institute, Aberdeen.
  • Rockloff, S.F. & Moore S.A. (2006). Assessing representation at different scales of decision making: rethinking local is better. Policy Stud. J. 34, 649-670.
  • Termeer, C.J.A.M., Dewulf, A. & van Lieshout, M. (2010). Disentangling scale approaches in governance research: comparing monocentric, multilevel, and adaptive management. Ecol. Soc. 15, 29.
  • Van Lieshout, M., Dewulf, A., Aarts, N. & Termeer, C. (2011). Do scale frames matter? Scale frame mismatches in the decision making process of a “mega farm” in a small Dutch village. Ecol. Soc. 16, 38.
  • Williams, P.M. (2012). Collaboration in public policy and practice: perspectives on boundary spanners. Policy Press, Bristol.
  • Young, J.C., Butler, J.R.A., Jordan, A. & Watt, A.D. (2012). Less government intervention in biodiversity management: risks and opportunities. Biodivers. Conserv. 21, 10951100.
  • Young, J.C., Jordan, A., Searle, K. et al. (2013). Does stakeholder involvement really benefit biodiversity conservation? Biol. Conserv. 158, 359-370.
  • Young, J. & Marzano, M. (2012). Embodied interdisciplinarity: what is the role of polymaths in environmental research? Environ. Conserv. 37, 373-375.
  • Young, O. (2006). Vertical interplay among scale-dependent environmental and resource regimes. Ecol. Soc. 11, 27.

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Disclaimer: Supplementary materials have been peer-reviewed but not copyedited.

FilenameFormatSizeDescription
conl12012-sup-0001-Tables.doc103K

Table S1: Median scores for each social and process outcome characteristic and for perceived biodiversity outcomes for each of the three case studies

Table S2: Model estimates and test statistics to summarize differences between case studies in perceived biodiversity, process, and social outcomes, based on models that contain “case study” and “stakeholder type” as explanatory variables.

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