Transposition of Natura 2000 Directives Into Forestry of Croatia

Transposition of Natura 2000

Directives into Forestry of Croatia -Multiple perspectives on policy formulation –

Thesis submitted in partial fulfillment of the requirements of the degree Philosophiae doctor of the Faculty of Environment and Natural Resources, Albert-Ludwigs-University Freiburg, Germany

Marko Lovrić

Freiburg im Breisgau, Germany

2014

Dean: Prof. Dr. Barbara Koch

Supervisor: Prof. Dr. Ulrich Schraml, Albert-Ludwigs University of Freiburg

Second supervisor: Prof. Dr. Margaret Shannon, Honorary Professor at Albert-Ludwigs University of Freiburg

Readers: Prof. Dr. Ulrich Schraml, Albert-Ludwigs University of Freiburg

Prof. Dr. Tom A. B. Snijders, University of Oxford, University of Groningen

Graduate School Environment, Society and Global Change

Research area: Environmental Governance

Faculty of Environment and Natural Resources, Chair of Forest and Environmental Policy

Date of defense: 16.6.2014

FOREWORDS

Acknowledgements

First and foremost, I would like to express my sincere gratitude to my supervisors, Prof. Dr. Ulrich Schraml and Prof. Dr. Margaret Shannon, for their tireless enthusiasm, invaluable support, and for their significant contribution to this work.

I am deeply indebted to Prof. Dr. Tom A. B. Snijders and to Dr. Christian Steglich for providing encouragement and guidance, as without their assistance, this thesis would lack the state it is currently in.

I am very grateful to my colleagues from the Chair of Forest and Environmental Policy Faculty of Environment and Natural Resources, University of Freiburg, as through frequent discussions they have contributed to the methodological setting of the thesis. I would like to extend a special thanks to Ms. Sabine Dehn who has helped me on numerous occasions.

I would not have had the opportunity to be a PHD candidate at the Faculty of Environment and Natural Resources, at University of Freiburg without the FOPER I and FOPER II projects. To a large extent, my scientific capacities originate from the participation in these projects. As such, I would like to use this opportunity and thank the managers and teaching staff of the FOPER projects for providing me with the necessary knowledge and skills required for a PhD. I would also like to thank Prof. Dr. Ivan Martinić for introducing me to the topic of Natura 2000 and shaping the initial setting of the research. Prof. Dr. Martinić’s practical guidance on conducting research in Croatia has made it possible.

The cornerstone of this thesis is the analysis of the Expert working group on forestry. I would like to kindly thank all of its members for providing me access to the meetings, and for diligently filling in all the questionnaires and providing answers to my numerous questions. The opportunity to closely follow a policy formulation process is what makes this research unique.

I would also like to extend my gratitude to Dr. Bernhard Wolfslehner and Dr. Dijana Vuletić for finding a mode of work which enabled me to combine my obligations at the EFICEEC-EFISEE (Central-East and South-East European) Regional Office of the European Forest Institute with the tasks of a PhD candidate.

Last but not least, special thanks goes to Nataša Lovrić, who has assisted me in every way possible – in the methodological preparations of the thesis, in data collection and analysis, in reviewing the text, and most importantly as an emotional support throughout the years.

Zusammenfassung

Natura 2000 gilt als ökologisches Netzwerk der Europäischen Union und somit das größte Schutzgebietsnetzwerk der Welt. Es gründet auf der Flora-Fauna-Habitat-Richtlinie, die jedes EU-Mitglied in seine nationale Gesetzgebung implementieren muss. Eine EU-Richtlinie ist ein Gesetzgebungsakt, welcher auf ein Ergebnis abzielt, aber die Maßnahmen um dieses zu erreichen, nicht im Einzelnen spezifiziert. Jedes EU-Mitglied kann die Maßnahmen zur Erreichung des Ziels selbst bestimmen. Die nationale Umsetzung von Natura 2000 unterscheidet sich innerhalb der EU sowohl was den Anteil der Schutzgebiete als auch den Grad des Schutzes angeht. Kroatien, als 28stes EU Mitglied, unterwirft sich aktuell diesem Prozess und die Regierung bereitet bereits seit einigen Jahren die rechtlichen Grundlagen für die Umsetzung von Natura 2000 vor. Die nationale Implementierung von Natura 2000 ist ein Politikgestaltungsprozess in dem die Machtverteilung unter den Akteuren eine wichtige Rolle spielt. Dies wirft folgende Forschungsfrage auf:

Wie beeinflussen die politischen Akteure das forstpolitische Entscheidungsverhalten in Kroatien?

Zur Beantwortung dieser Frage beginnt die Untersuchung mit einem Überblick über Natura 2000 im Allgemeinen, die Formulierung der Richtline und nachfolgende Umsetzung in Europa, um dann einen Blick auf die Umsetzung in Kroatien zu werfen. Anschließend richtet sich der Fokus auf die Expertenarbeitsgruppe, welche den forstlichen Teil der Natura 2000 Bestimmungen in Kroatien verfasst hat. Die Untersuchung betrachtet außerdem den Diskurs innerhalb der Arbeitsgruppe und analysiert wie verschiedene Grundüberzeugungen der Akteure die Entscheidungen geformt haben. Die letzten Kapitel widmen sich der Analyse des betreffenden Netzwerkes, namentlich der Einflussnahme während des Formulierungsprozesses aufgrund persönlicher Beziehungen sowie aufgrund von Machtverhältnissen innerhalb von Organisationen und deren Bedeutung für Meinungsänderung der Arbeitsgruppenmitglieder und damit für ihre Entscheidungen.

Kapitel II liefert zur Analyse der Expertengruppe Forst eine Beschreibung von deren Umfeld und deckt die Formulierung der Natura 2000 Richtlinie ab, beschreibt ihre nationale Implementierung und gibt einen historischen Überblick über die Entwicklung in Kroatien. Dieses Kapitel ist aus der Perspektive der “Europeanization of Environmental Governance“ (Börzel, 2009) geschrieben. Diese besagt, dass Nationalregierungen ihre Institutionen so gestalten oder anpassen müssen, dass sie in der Lage sind EU-Gesetzgebung umzusetzen. Die Analyse stützt sich auf eine Literaturanalyse und auf 57 Interviews mit Experten. Die Ergebnisse weisen darauf hin, dass beide Verordnungen in enger Kooperation mit Umwelt-NGOs auf der einen Seite und gegen den Widerstand durch die Vertreter der Landnutzer auf der anderen Seite vorbereitet wurden.

Die erste Phase der nationalen Umsetzung der Richtlinie war europaweit stark durch einen Top- Down-Ansatz geprägt und wurde später jedoch durch einen Mehrebenen-Governance-Ansatz abgelöst. Westliche EU-Mitgliederstaaten haben im Rahmen des Natura 2000 Netzwerks relativ kleine Schutzgebiete ausgewiesen, aber dafür die Umsetzung hartnäckiger eingefordert, während die östlichen EU-Mitgliedstaaten große Flächen unter Schutz gestellt haben, in denen die Verpflichtungen, die sich aus Natura 2000 ergaben, nicht so strikt eingehalten wurden. Kroatien hat sich über 10 Jahre, in denen eine ganze Reihe fremdfinanzierter Projekte durchgeführt wurden, auf die Umsetzung von Natura 2000 vorbereitet. Durch diese Projekte wurde die Leistungsfähigkeit der staatlichen Verwaltung gesteigert und angemessenes Fachwissen für die Umsetzung von Natura 2000 generiert. Diese internationalen Projekte haben außerdem die Bildung eines nationalen ökologischen Netzwerkes, einem Vorläufer des Natura 2000 Netzwerkes, gefördert. Obwohl diverse Versuche zur öffentlichen Anhörung und zum Informationsaustausch gemacht wurden, waren die Landnutzer nicht umfassend an der Implementation des Netzwerkes beteiligt. Nicht-Regierungsorganisationen aus den Bereichen Umwelt- und Naturschutz wurden auch nicht sehr stark einbezogen und entwarfen dann eine eigene Karte auf der sie Vorschläge für Natura 2000 Flächen ausweisen (Schattenlisten). Der Forstsektor war stärker als andere in die Vorbereitung einbezogen, trotzdem sind noch nicht alle Konflikte ausgeräumt. Schaut man sich die Beispiele anderer Länder an, so ist zu erwarten, dass der große Enthusiasmus über die Implementation von Natura 2000 vor dem Beitritt in der Phase danach nicht aufrecht erhalten werden kann, da mit Eintritt der Einfluss der EU nachlassen wird und die zentralen nationalen Verwaltungen nicht in der Lage sein werden, dem Druck der Landeigentümergruppen standzuhalten.

Kapitel III konzentriert sich auf die Aktivitäten der Arbeitsgruppe und analysiert wie verschiedene Diskurse deren Entscheidungen geprägt haben. Das Kapitel nutzt drei theoretische Ansätze, deren Eignung, die Entscheidungen der Arbeitsgruppe zu erklären, durch den Testn von 28 Hypothesen überprüft wird. Die theoretischen Ansätze gründen auf dem „Advocacy Coalition Framework (Jenkins-Smith and Sabatier, 1994), der “Rational choice theory (Coleman, 1990) und der „Theory of Communicative Action“ (Habermas, 1979). Die Daten aus den Interviews mit Mitgliedern der Arbeitsgruppe und aus der nicht-teilnehmenden Beobachtung ihrer Treffen wurden mittels Inhaltsanalyse ausgewertet. Die Ergebnisse zeigen, dass die Mitglieder der Arbeitsgruppe ihre Meinungen der vorherrschenden Haltung ihres Sektors angepasst haben. Staatliche Verwaltungsorganisationen dienen als Bindeglied zwischen Forstwirtschaft und Naturschutz. Mitglieder des Forstsektors haben ihre ursprünglichen Positionen zur Rolle von Natura 2000 in der Forstwirtschaft nicht verändert, eine Meinungsänderung war eher für zweitrangige Themen nachweisbar. Dies ist sowohl mit dem normativen als auch dem rationalen Ansatz erklärbar. Die Ergebnisse deuten auch auf die Existenz eines sog. „Devil-Shift“ hin, ein Phänomen bei dem Akteure ihre Widersacher als einflussreicher beschreiben als sie tatsächlich sind. Die wesentlichen Entscheidungen der Arbeitsgruppe bezogen sich auf den Ausweisungsprozess der Flächen und das Definieren der waldbaulichen Maßnahmen. Mitglieder der Arbeitsgruppe haben häufig konstatiert, dass wissenschaftliche Argumentation Grundlage für

III die Formulierung ihrer Entscheidungen ist. Der Test der Hypothese „Theory of Communicative Action“ liefert indes wenig Anhaltspunkte für diese Feststellung. Eine Erklärung für diese Diskrepanz kann man in den unterschiedlichen Auffassungen darüber finden, was „angemessenes“ Fachwissen ist. Die beschriebenen Unterschiede haben ihren Ursprung in den verschiedenen Konzepten von Ökosystemansatz und nachhaltiger Forstwirtschaft.

Kapitel vier betrachtet die Rolle von Macht- und Einflusssystemen auf die Entscheidung der Arbeitsgruppe aus der Sicht der „Social-Network-Analysis“. Einflussnahme durch persönliche Verbindungen und Macht innerhalb von Organisationen werden mit der „Resource dependence perspective“ (Pfeffer and Salacnik, 1978) analysiert. Die Daten wurden mit Fragebögen generiert, die an die Mitglieder der Arbeitsgruppe verteilt wurden sowie durch die Beobachtung der Treffen. Die Ergebnisse zeigen, dass im Laufe der Diskussionen persönliche Einflussnetzwerke dichter wurden und dass der Anteil der einflussreicheren Akteure zugenommen hat. Verlaufsmuster von Zweiergesprächen (dyadic communication) zeigen einerseits eine hohe Konzentration auf die Schlüsselakteure und andererseits, dass die Unterschiede der Gesamteinflussnahme auf das Netzwerk bei den zentralen Akteuren mit der Häufigkeit gescheiterter Kommunikationsversuche zusammenhängt. Die Analyse von Untergruppen zeigt, dass in den ersten Treffen die Arbeitsgruppe in zwei Untergruppen aufgeteilt war, welche der sektoralen Aufteilung entsprach. Beim letzten Treffen war schließlich eine Kerngruppe von Senior-Akteuren beider Sektoren und eine Randgruppe aus Junior- Akteuren festzustellen. Machtbeziehungen innerhalb von Organisationen zeigen Ähnlichkeiten mit Einflussgefügen auf persönlicher Basis. Meinungsänderung wurde mit dem „Friedkin and Johnsen`s (1997) model“ analysiert, welches auf persönlicher Ebene eine leichte Neigung zu den Positionen des Forstsektors zeigt. Auf Organisationsebene zeigt die Analyse, dass die ursprüngliche Meinung der Vetreter mächtiger Organisationen näher an der Mittelposition liegt als die der Vertreter der weniger mächtigen. Entsprechende Modelle von Netzwerkdynamiken (Snijders et al, 2010) zeigen die Wirkung der Macht von Organisationen auf interpersonelle Verbindungen und dass Verbindungen eine hierarchische Struktur besitzen. Die Anwendung des „Models of co-evolution of network and behavior” (Steglich et al, 2010) weist auf die passende Veränderungen des Netzwerkes hin, bestätigt aber den Einfluss meinungsbildender Akteure der jeweiligen Sektoren nicht. Damit finden beide Faktoren aus „Friedkin and Johnsen`s model“ keine Bestätigung.

Die Implementierung von Natura 2000 in die Forstwirtschaft Kroatiens kann letztlich als kleiner Ausschnitt einer langandauernden Politikdebatte zwischen dem Umwelt- und dem Forstwirtschaftslager gesehen werden, welche aus verschiedenen Perspektiven heraus versuchen die biologische Vielfalt in europäischen Forst-Ökosystemen in Europa (Glück, 2000a) zu stärken.

Summary

Natura 2000 is the ecological network of the European Union (hereafter referred to as the EU), the largest network of protected areas in the world. It is based on the ‘Habitats’ and on the ‘Birds’ directives, which every EU member country has to implement in its national legislation. An EU directive is a legislative act which sets to achieve a certain result; however, it does not specify in detail the means to achieve it as it is up to each EU member country to individually identify it. National implementations of Natura 2000 differ across EU, both in the share of protected area and in the level of protection. Croatia, as the 28th EU member state, currently faces the same process; its government is preparing the Ordinance on Natura 2000, a document with which Natura 2000 will be formally implemented. As national implementations of the Natura 2000 can be characterized as policy formulation processes in which power relations between its stakeholders play an important role, the following research question emerges:

How do stakeholders influence the Natura 2000 forest policy decision making in Croatia?

In order to provide an answer to the above question, the research starts with a general overview of the Directives, followed by the manner in which they are formulated and subsequently implemented across the EU, concluding with a historical view of its implementation in Croatia. The focus then shifts to the Expert working group on forestry, which has defined the forestry section of the Ordinance on Natura 2000. The research looks at the discourse within the working group and analyzes how different rationales have shaped its decisions. The final chapters of the research are devoted to the analysis of the effects of inter-personal influence relations and of inter-organizational power relations on the opinion change on the members of the working group, and subsequently on their outcome decisions.

Chapter II provides the contextual setting for the analysis of the Expert working group on forestry, and it covers the formulation of Natura 2000 directives, their national implementations, and the historical overview of developments in Croatia. The Chapter takes the theoretical perspective of “Europeanization of environmental governance” (Börzel, 2009), by which national governments have to build or modify their institutions in order to be able to implement EU legislation. Analysis is based on literature review and on 57 face-to-face interviews with key informants. Results demonstrate that the Directives have been prepared in strong cooperation with environmental non-governmental organizations (NGOs) as well as with opposition arising from the land user groups. The first phase of the national implementations of the network was characterized by a top-down approach and strong compliance which was later on transformed to a multi-level mode of governance characterized by weak compliance. Western EU member states have protected relatively small areas under the Natura 2000 network but have more diligently enforced its implementation. On the contrary, eastern EU member states have protected large areas in which obligations derived from Natura 2000 were not as strictly implemented as was the

V case with the western EU countries. Croatia has had more than a decade of preparations for the implementation of Natura 2000, which was characterized by a series of externally funded projects. These projects have built the capacities of the state administration and have created adequate scientific knowledge for the implementation of Natura 2000. They have also assisted in the creation of the National Ecological Network, a predecessor of the Natura 2000 network. Although several cycles of public consultations and information sharing have been made, the land user groups were not greatly involved in the preparations for the implementation of the Network. In addition, non-governmental organizations in the field of environment and nature protection have not been strongly involved and are preparing their own country-wide proposal of Natura 2000 areas. The forestry sector was more involved in the preparations for the implementation of Natura 2000 in comparison to other sectors; nevertheless, numerous issues still persist. Following the examples from other countries it is expected that the high level of dedication towards the implementation of EU Natura 2000 directives in the pre-accession phase will not be as vigorously followed in the post-accession phase. The reason for such lies in the fact that the EU will lose its influence through the accession conditionality and the central national administration will not be able to strongly oppose the pressures arising from the land- user groups.

Chapter III focuses on the activities of the Working group on forestry and on how different discourses have shaped its decisions. The chapter utilizes three distinctive theoretical approaches: normative, rational and scientific. The domain of validity in explaining the decisions of the working group is set by testing a total of 28 hypotheses. The three theoretical approaches are based on the ‘Advocacy coalition framework’ (Jenkins-Smith and Sabatier, 1994), on the ‘Rational choice theory’ (Coleman, 1990) and on the ‘Theory of communicative action’ (Habermas, 1979). Content analysis is used on data coming from interviews with the members of the working group and from non-participant observation of its meetings. Results show that members of the working group have their opinions aligned with the general positions of their sectors, where state administrative organizations serve as a connection between the forestry and nature protection. Members of the forestry sector had not changed their initial positions on the role of Natura 2000 in the sphere of forestry. Opinion change was more prominent for secondary topics (such as limiting final cut and permanent presence of deadwood), which is in line both with the normative and the rational approach. Results also point to the presence of the “devil shift”, where actors tend to describe their “opponents” more influential than they actually are. The most central decisions of the working group were the site designation process and the defining of management guidelines for forest dependent species. It is prudent to note that both of these decisions were based on compromise between different policy preferences. Members of the working group have frequently stated that the scientific argumentation is the basis for the formulation of their decisions. Nevertheless, the testing of the hypothesis with the Theory of communicative action provides little evidence for such conclusions. Explanation of this

VI discrepancy is found in the differences on what “adequate” scientific knowledge entails, which is rooted in the differences between the concepts of ecosystem approach and sustainable forest management.

Chapter IV looks at the role of power and influence relations on the decisions of the working group from the perspective of social network analysis. Inter-personal influence relations are analyzed through the ‘Friedkin`s model’ (1993) of inter-personal influence, and the inter- organizational power relations are analyzed from the ‘Resource dependence perspective’ (Pfeffer and Salacnik, 1978). Data is drawn from a series of questionnaires distributed to the members of the working group, and from the direct observation of its meetings. Results show that inter- personal networks of influence have became denser, and that the share of influence spread by more influential actors has increased. Patterns of dyadic communication demonstrate high centralization on several key actors. Also, the difference in the total “spread” of influence between the central actors is closely related to the frequency of their failed communication attempts. Analysis of the sub-groups shows that in the first meetings the working group was divided into two sub-groups which corresponded to sectoral division. However, by the time of the final meeting there was a core group of senior actors from both sectors, in addition to one peripheral group which consisted mostly of junior actors. Inter-organizational power relations bare similarities to the inter-personal influence relations, with a correlation between them of 0.46. Opinion change has been analyzed through the Friedkin and Johnsen`s (1997) model, which on an individual level shows slight shift of decisions toward the positions of the forestry sector. On an organizational level it shows that the initial opinions of the more powerful organizations are closer to the equilibrium opinion than in the case of the less powerful organizations. Models of ‘network dynamics’ (Snijders et al, 2010) demonstrate the impact of organizational power on inter-personal influence relations, and that strong influence relations show indication of local hierarchical structure. Models of ‘co-evolution of network and behavior’ (Steglich et al, 2010) show similar patterns of network dynamics, but do not confirm presence of the social influence process or the effect of sectoral affiliation on opinion change; both of which were important factors in the application of the ‘Friedkin and Johnsen`s’ model.

Pronounced sectoral division of actors and adherence to their central positions stipulates the normative rationale of decision making. Implementation of Natura 2000 in forestry of Croatia can be seen as a small part of a long-lasting policy debate between the “environmentalist” and the “forestry camp” on different perspectives, all with the purpose of enhancing biological diversity in forest ecosystems in Europe (Glück, 2000a).

VII

INDEX Table of contents

FOREWORDS I Acknowledgements I Zusammenfassung II INDEX V Table of contents VIII Index of tables and figures VIII X CHAPTER I: INTRODUCTION 1 CHAPTER II: NATURA 2000 AND THE CONTEXT

OF ITS TRANSPOSITION 1. Summary 5 2. Introduction 7 3. Legislative basis of Natura 2000 and its effect on forest management 9 3.1.Legislative basis of Natura 2000 9 3.2.Natura 2000 site designation process 13 3.3.Aims of forest management in Natura 2000 areas 15 4. Methodological approach 20 5. Results 25 5.1.Formulation of the Natura 2000 directives 25 5.2.National implementations of Natura 2000 27 5.3.Natura 2000 in Croatia 34 5.3.1. Formal compliance, 2002-2013 34 5.3.2. Practical compliance, 2002-2013 43 6. Discussion 45 46 CHAPTER III: NORMATIVE, RATIONAL AND COMMUNICATIVE 49 PERSPECTIVE ON THE WORKING GROUP ON NATURA 2000 1. Summary 49 2. Introduction 50 3. Conceptual basis 52 3.1. Advocacy coalition framework 52 3.2. Rational choice 56 3.3. Boundary between science and policy 60 3.4. Communicative action 63 4. Methodological approach 66 5. Results 78 5.1. Normative approach 78 5.2. Rational approach 82 5.3. Communicative approach 86 5.4. Deductive falsification of hypotheses 89 6. Discussion 90

VIII

CHAPTER IV: NETWORK PERSPECTIVE ON THE FORMULATION OF NATURA 99 2000 FOREST POLICY 1. Summary 99 2. Introduction 100 3. Conceptual basis 102 3.1. Social network analysis 102 3.2. Inter-organizational relations 105 3.3. Network models of social influence 111 3.4. Models of network dynamics 113 4. Methodological approach 119 4.1.Modeling inter-personal relations 119 4.2.Modeling inter-organizational relations 125 4.3.Questionnaire design and data collection 128 4.4. Data analysis techniques 130 5. Results 132 5.1. Networks of inter-personal relations 132 5.1.1. Internal validity of the Friedkin`s (1993) model 132 5.1.2. Whole network characteristics 134 5.1.3. Centrality measures 136 5.1.4. Analysis of sub-groups 138 5.1.5. Network visualizations 141 5.2. Organizational analysis 148 5.3. Modeling opinions change 155 5.3.1. Individual level 155 5.3.2. Organizational level 159 5.4.Longitudinal network models 162 6. Discussion 168

CHAPTER V: DISCUSSION AND CONCLUSIONS 173

REFERENCES 179

ANNEXES 223 Annex I : Code book 223 Annex II: Social power code book 225 Annex III: Interview protocol 226 Annex IV. Operationalization of hypotheses for Chapter III 227 Annex V. Contradictions among the hypotheses from Chapter III 233 Annex VI. Network visualizations with fixed layout 237 Annex VII. Questionnaires, interview protocol and notification CD

Index of tables and figures

Tables Table 1.Overview of the research design 4 Table 2. Forest management measures for Natura 2000 areas in Slovenia 19 Table 3. List of important national projects related to Natura 2000 36 Table 4. Management measures for birds and other species related to forest habitats 38 Table 5. Coverage of Natura 2000 in proposal (year 2009 and 2012) 40 Table 6. Differences between the normative, rational and communicative theoretical 69 approaches Table 7. Hypotheses and their operationalization 72 Table 8. List of organizations that were represented in the working group 76 Table 9. Contradictory hypotheses 88 Table 10. Deductive falsification results 89 Table 11. A typology of ties studied in social network analysis 105 Table 12. Overview of effects in RSiena 115 Table 13. Values of objective function for ego`s network change opportunities 118 Table 14. Stakeholders` statements on the Natura 2000 forest policy 127 Table 15. QAP correlation between items on French and Raven`s (1959) power bases 132 Table 16. QAP correlations among items on inter-personal influence 133 Table 17. MRQAP of Friedkin`s (1993) model of inter-personal influence 133 Table 18. Basic parameters of the inter-personal influence networks 134 Table 19. QAP correlations between different items related to inter-personal 136 influence Table 20. Normalized centrality measures for inter-personal influence networks 137 Table 21. Density and average tie strength ratio among sectors in different influence 138 networks Table 22. Whole network characteristics of resource flows for T1 and T2 148 Table 23. Centrality measures in organizational network 150 Table 24. Correlations between inter-personal and inter-organizational relations 154 Table 25. Inter-personal influence values for the Friedkin and Johnsen`s model 155 Table 26. Differences between various opinions at organizational level 160 Table 27. Changes in influence networks 163 Table 28. Densities of influence networks 163 Table 29. Models of influence dynamics 164 Table 30. Co-evolution models of network and behavior 167

Figures Figure 1. Overall research design 3 Figure 2. Overview of Chapter II 7 Figure 3. Natura 2000 and the Emerald networks 12 Figure 4. Designation process for Natura 2000 14 Figure 5. Designation process of SAC areas 14 Figure 6. Two logical frameworks of domestic change 22 Figure 7. Research design of Chapter II 23 Figure 8. National ecological Network and the forest habitats in Croatia with dot 35 NEN forest areas Figure 9. Natura 2000 proposal (year 2009 and 2012) 41 Figure 10. pSCIs for forest habitats as agreed at the expert working group in the 42 year 2012 Figure 11. Overview of Chapter III 50 Figure 12. Advocacy coalition framework flow diagram 54 Figure 13. Research design of Chapter II 67 Figure 14. The coding scheme 75 Figure 15. Similarity of opinions between actors 78 Figure 16. Association of individuals and groups 79 Figure 17. Opinions of different group of actors 80 Figure 18. Distribution of Rationale codes by topic 84 Figure 19. Strategic usage of information by actor and by topic 85 Figure 20. Methodological overview of Chapter IV 100 Figure 21. Network change opportunities for ego 118 Figure 22. Illustrative case of social influence network 120 Figure 23. Longitudinal model of social influence 122 Figure 24. Inter-personal influence relations at time 1 142 Figure 25. Inter-personal influence relations at time 2 143 Figure 26. Correspondence analysis of influence networks from time 1 to time 2 144 Figure 27. Influence relations derived from communication patterns 145 Figure 28. Reciprocated dyadic communication 146 Figure 29. Failed communication attempts 147 Figure 30. Network of inter-organizational resource flows 153 Figure 31. Change of opinions within the working group 157 Figure 32. Changes in organizational opinions by Friedkin and Johnsen`s model 161 Figure 33. Histogram of influence values (0-8 range) at time 1 and time 2 162 Figure 34. Histograms of opinions at time 1 and time 2 166

CHAPTER I INTRODUCTION

The most important elements of the European Union (hereafter referred to as EU) nature protection legislation are the ‘Habitats’ and the ‘Birds Directive’ which together form the basis for the ecological network of the EU – Natura 2000. The national implementations of these directives differ across the EU. The social science literature has traced the causes of these differences in diverse power relations among national stakeholders, in their varied capacities to follow the implementation process, and in the general capacities of national governments to resist supra-national influences.

Croatia now as the 28th EU member is tasked with the preparation of the Ordinance on Natura 2000, a legislative document by which Natura 2000 will be formally implemented. The forestry part of that ordinance was defined by a working group under the leadership of the State Institute on Nature Protection. The working group consisted of representatives from a number of stake- holding organizations, both from nature protection and forestry. From the year of 2010 until the end of 2012, the working group held a total of eleven meetings. These meetings have resulted in expert proposal of sites for the protection of forest habitats and forest dependent species, as well as with the introduction of management guidelines for the protection of forest dependent species. As national implementations of the Natura 2000 can be characterized as policy formulation processes in which power relations between its stakeholders play an important role, the following research question emerges:

How do stakeholders influence the Natura 2000 forest policy decision making in Croatia?

In order to answer the research question the study utilizes three different approaches all of which have different sub-questions, scope and methodology. Each approach answers one segment of the research question, and they are presented in the three subsequent chapters. Weber and Christophersen (2002) have stipulated that understanding of national implementations of Natura 2000 requires understanding on how its Directives have been formulated, while Ferranti et al (2010) have stipulated the importance of the European context of protection of biodiversity and natural heritage when analyzing national implementations of Natura 2000. For Moscari (2004), McCauley (2008) and for Van der Zouwen and Van den Top (2001) the understanding of national implementations of Natura 2000 lies in the differences between national policy culture and the EU multi-level mode of governance. The importance of contextual setting forms the first sub-question: “What is the contextual setting for the formulation of Natura 2000 forest policy in Croatia?” This sub-question is addressed in Chapter II (titled “Natura 2000 and the context of its

1 transposition”), which provides a deeper insight in the Directives and their implementation in different EU member countries. The impact of EU directives onto national policy domains is viewed from two competing theoretical perspectives on Europeanization: the differential empowerment which is in line with the Rational choice, and the internalization of norms which is in line with the new institutionalism. Through these theoretical perspectives policy outcomes are related to the capacities and to the power relations of different national stake-holding groups. The chapter also provides a historical overview on the implementation of Natura 2000 in Croatia, which is embedded in the framework of the previously addressed Europeanization theories. Chapter II also serves as a contextual setting for Chapter III and Chapter IV, which provide more detailed accounts on the relation between the formulation of Natura 2000 forest policy and its stakeholders.

Chapter II has shown that national Natura 2000 policy formulations should be based on scientific argumentation, but also that they are affected by its stakeholders whose power relations and different normative standpoints have led to very diverse formal and practical implementations of the Network. For Julien et al (2010) the key factor of implementation of Natura 2000 in forestry is the misunderstanding of its objectives and implications by the land-user groups, who guard their opposing normative standpoints. For Alphandéry and Fortier (2001) national implementation of Natura 2000 is simply a process where different groups of actors rationally pursue their interests, which ultimately leads to sub-optimal outcomes. Ferranti et al (2013) look at the national implementation processes as interplay between conservation-scientific and rational economic discourses. Since the expert working group on forestry represents a formal forum where decisions should be made through joint communication, the following sub-question emerges: “What types of discourses have shaped the formulation of Natura 2000 forest policy in Croatia?” In addition, Chapter III, titled “Normative, rational and communicative perspective on the working group on Natura 2000”, looks at the interplay of these three group of factors in the formulation of the working group`s decisions. The normative approach is based on the Advocacy coalition framework (Sabatier and Jenkins-Smith, 1993; 1994), the rational approach is based on sociological Rational choice theory (Coleman, 1990), and the communicative perspective is based on the communicative action from the Theory of communicative action (Habermas, 1979). For each of these approaches a series of formal hypotheses have been constructed, upon which a deductive falsification procedure has been applied.

Chapter III reveals the role of different rationales that were behind the formulation of Natura 2000 forest policy in Croatia; unfortunately, it does little to reveal the effects of power and influence, which are important elements of the normative and the rational discourse. The impact of these effects is analyzed in Chapter IV titled “Network perspective on the formulation of Natura 2000 forest policy”. This chapter is based on the application of social network analysis, and the effects of power and influence relations on the working group`s decisions, which are in turn analyzed both at inter-personal and inter-organizational level. The abovementioned models are used to model the change of opinions on the salient issues, which is done through the

2 application of Friedkin and Johnsen`s (2011) network model of social influence. Inter-personal relations are examined by using the Friedkin`s (1993) model of social influence and inter- organizational relations are viewed from the perspective of Resource dependence framework (Pfeffer and Salancik, 1978). The dynamics of influence relations and its interplay with opinion change is analyzed through application of stochastic actor oriented network models (Snijders et al, 2010). An overview of the research design is presented in Figure 1.

CHAPTER II

CHAPTER III

CHAPTER IV Europeanization; Advocacy coalition Differential framework, Resource dependence Opinions Beliefs Norms empowerment Rational choice framework, and theory, Social influence Power and Interests Interests internalization of Theory of models norms Communicative influence action Social network Working group analysis

Working group Content analysis

Croatian history of implementation Content analysis

EU implementation Literature review

Figure1. Overall research design

Figure 1 shows that the research is designed in such a way that one chapter serves as a framework for the subsequent one, both in the conceptual and in the geographical-temporal scope. The purpose of such a design with multiple converging lines of inquiry is to strengthen the internal validity of the research, which is basically a study of a single case – the working group of Natura 2000. Several types of triangulation have been used; triangulation in data sources (secondary data, questionnaires, interviews and direct observation), investigator triangulation (in data collection and analysis), theory triangulation (Europeanization, Advocacy coalition framework, Resource dependence framework, and the like), as well as the use of methods (literature review, content analysis and social network analysis). The purpose of triangulation in the research design was to overcome the criticism of using deductive theorizing on data which is primarily qualitative. A more detailed overview of the research design is presented in Table 1.

Table 1.Overview of the research design

CHAPTER II III IV ELEMENTS Normative, rational and Network perspective on Natura 2000 and its communicative perspective the formulation of transposition on the working group on Natura 2000 forest policy Natura 2000 Scope EU, Croatia Working group Working group Europeanization through Advocacy coalition framework, Resource dependence Theoretical differential empowerment Rational choice theory, Theory framework, social framework and internalization of of communicative action influence models norms Type of research Qualitative Qualitative Quantitative Method of data Literature review, content Content analysis Social network analysis analysis analysis Secondary data – Data scientific and grey Interviews, secondary data Questionnaires literature; interviews Formal compliance, Key concepts of Policy learning, compromise, Power, influence, opinion practical compliance, analysis discourse change policy formulation

Table 1 also shows that with the passage from Chapter II to Chapter III and then on to Chapter IV the scope narrows down from the general context of Natura 2000 towards the working group on forestry. The research also gets more structured - in the methods section and in the data that is used. The research moves from literature review through qualitative data and content analysis, and finally to usage of questionnaires and social network analysis. Each chapter can also be seen as its ‘stand-alone’ research, as each chapter contains a separate introduction, literature review, methodology and results and discussion section. Chapter II (Natura 2000 and the context of its transposition) is primarily based on secondary data from scientific and grey literature, and its section on developments in Croatia is also based on a total of 57 interviews performed in the period 2010-2013. Chapter III (normative, rational and communicative perspective on the working group on Natura 2000) is based on interviews performed with the members of the working group, all of whom have been interviewed on two occasions – in the beginning of the research and after the final meeting of the working group. Data for Chapter IV (Network perspective on the formulation of Natura 2000 forest policy) primarily derives from questionnaires distributed to the members of the working group. There are two questionnaires (one on inter-personal and the other on inter-organizational relations). Both questionnaires were distributed twice in order to capture the changes in inter-personal and the other on inter- organizational relations. Communication within the working group was captured by non- participant observation of its meetings. The research concludes with a discussion chapter. The main aim of the discussion chapter is to bridge all previous parts of the thesis by employing critical review of the methodological complement of its different elements, in addition to taking into account the coherence and contradictions among the results stipulated in all of the chapters.

CHAPTER II NATURA 2000 AND THE CONTEXT OF ITS TRANSPOSITION

1. Summary

Natura 2000 is the ecological network of the European Union, and it is based on the ‘Habitats’ and on the ‘Birds Directive’. These directives represent the most important part of the EU legislation from the field of nature protection, and their national implementations differ across the EU. Social science literature has attributed these processes with the characteristics of a policy formulation process, in which power relations between its stakeholders play an important role (Alphandery and Fortier 2001; Apostolopoulou and Pantis, 2009; Börzel and Buzogány, 2010; Buzogany, 2009; Chilla, 2007; Fairbass and Jordan, 2001; Ferranti et al, 2010; Papageorgiou and Vogiatzakis, 2006).

The aim of this chapter is to provide insight to the relations between different actors in the implementation of Natura 2000 in Croatia and to provide understanding on their influence in the formulation of the national Natura 2000 policy. The impact of Natura 2000 on the national policy domain is seen through two different perspectives: the differential empowerment and internalization of norms. The initial step of the research is to trace the relations between the actors in the formulation of the ‘Habitats’ and the ‘Birds Directives’. These findings serve as a framework for understanding the national implementations of the directives, where policy outcomes are linked through two different theoretical perspectives - to the capacities and to the power relations between the national actors in many EU member states, such as France, Italy, Bulgaria and Netherlands. The analysis is performed both formal and practical implementation of the Directives. The insight of the relations in the formulation of the Directives and understanding their formal and practical implementation in different EU member states serves as a framework through which past steps of the Natura 2000 implementation are analyzed, and future steps are anticipated. Analysis of the national implementations of Natura 2000 is based primarily on the literature review, while analysis of the Croatian implementation is based on additional 57 interviews with key informants.

Results show that the Directives have been prepared in strong cooperation with environmental NGOs and with opposition coming from the land user groups. The first phase of the national implementations of the network was characterized by a top-down approach and strong compliance which was later on transformed to a multi-level mode of governance characterized

5 by weak compliance. Western EU member states have protected relatively small areas under the Natura 2000 network but have more diligently enforced its implementation. On the contrary, Eastern EU member states have protected large areas in which obligations deriving from Natura 2000 were not as strictly implemented as they have been in Western EU countries. The differences in the level of practical compliance can be traced to the capacities of the national non-governmental organizations, whose direct contacts with the EU bodies have circumvented the power relations of the national policy domains and enhanced the level of practical compliance.

Croatia has had a much longer period of preparations for the implementation of Natura 2000 than it was the case in other EU countries. In this ten-year period and through a series of internationally funded projects, a high level of scientific data on habitats and species was collected, which was mandatory for the national proposal of Natura 2000 areas. Although several rounds of public consultations and information sharing have been made, the land user groups were not much involved in the preparations phase for the implementation of the Network, whose future steps will become increasingly politicized. Non-governmental organizations in the field of environment and nature protection have also not been strongly involved and are preparing their own map of Natura 2000 areas. It is prudent to note that the forestry sector was more involved in the preparations for the implementation of Natura 2000 than was the case with the other sectors; nevertheless, many challenges persist. One should note that roughly 20% of the forest habitats have entered the official proposal of the Network, which is on the average level of European coverage of protection of forest habitats; unfortunately, it is still uncertain how Natura 2000 will influence the forestry sector. Following the examples of other countries, it is expected that the high level of devotion toward the implementation of EU Natura 2000 directives in the pre- accession phase will not be followed in the post-accession phase. Such is the likely scenario as the EU will lose its influence through the accession conditionality and what is more, the central national administration will be unable to strongly oppose the pressures arising from the land-user groups.

2. Introduction

The research question focuses the study on the stakeholders` impact on the formulation of Natura 2000 forest policy in Croatia. This relation is embedded in the historical developments of Natura 2000 in Croatia, and understanding the beliefs and interests of the national actors provides an insight to the Natura 2000 implementation processes in other EU countries; as comparable groups of actors have faced the same or similar processes. On a larger scale the understanding of national implementations of Natura 2000 in forestry requires knowledge on the kind of changes brought to the sector. In addition, a multi-level system of EU behavior of national actors in national implementations of Natura 2000 requires an understanding of the behavior of international actors in the formulation of Natura 2000. These elements are the preconditions for answering the research question, and also set the question for this chapter: What is the contextual setting for the formulation of Natura 2000 forest policy in Croatia?

The chapter tackles all of the above elements, and serves as an introduction to the two subsequent chapters. Its overview is presented in Figure 2.

Figure 2. Overview of Chapter II

Chapter II begins by defining what the procedure for implementation of a directive entails and by analyzing the basic legislative elements of Natura 2000. The chapter then provides an overview of the procedure for implementation of Natura 2000, and the practical changes that it brings to the forestry sector. Subsequently, the chapter presents the theoretical framework and the data collection procedure as a background for the study of Natura 2000 national implementations. The chapter takes the perspective of Europeanization of domestic environmental governance (Carmin and Vandeveer, 2004; Börzel, 2009), by which national governments are required to build institutions and structures in order to implement EU legally binding agreements. The level of institutional changes which are required for effective implementation of these agreements is set by the level of misfit between the national and the EU policies. Two processes can be applied to explain the change in national institutions (Börzel and Risse, 2000, 2003): differential empowerment and internalization of norms. Differential empowerment is a process by which EU policies create redistribution of power and resources in the national policy domains. The implementation of these policies is set by the EU conditionality mechanisms, which foster “top- down” approaches prior to accession to the EU and “bottom-up” approaches post accession. Internalization of norms is a process where networks of actors and epistemic communities bring about change in the national policy domains by adhering to new (EU) norms which are regarded as appropriate and legitimate. Such is facilitated by the availability of new scientific knowledge, participatory exchange of information and political culture of consensual decision making. These elements also lead to re-defining of the interests of the national actors.

By means of a short analysis on the formulation of the ‘Habitats’ and of the ‘Birds’ directives, the chapter proceeds to review the Natura 2000 implementation processes in a number of EU states, such as France, Italy, Netherlands, Bulgaria and Slovenia. This particular section of the chapter covers several Central and Northern European countries where Natura 2000 is characterized by an “intensive” forest management system, in addition to several South and Eastern European countries where Natura 2000 is characterized by “extensive” forest management system. Furthermore, the section links the Natura 2000 policy outcomes to the relations between its stakeholders, their beliefs and norms, and to their power relations. All of the information presented above serves as a context for analysis of the past steps of Natura 2000 implementation in Croatia, where Europeanization concepts are used to describe the history of its development, both from the perspective of formal and practical implementation. Patterns in the relations between the actors in the implementation of Natura 2000 in other countries serve as a framework for understanding the relations between actors in Croatia, and with respect to distribution of power and resources it also provides a framework for anticipating its future steps. The entire Chapter II may also be viewed as a contextual introduction to Chapter III and Chapter IV which focuses on the activities of the forestry working group on Natura 2000.

3. Legislative basis of Natura 2000 and its effect on forest management

3.1. Legislative basis of Natura 2000

A directive (as opposed to regulation) of the European Union is a binding legislative act whose exact means of implementation are left to the discretion of the member states. Its formulation is made by an ad-hoc committee authorized by the European Commission. The committee designated for formulation of a certain directive must consult with the international advisors and with the national advisors from the countries in which the directive is going to be implemented. Before coming to power the directive has to be approved by the European Parliament and by the Council of Ministers of member states (EC, 2007a).

Prior to the implementation of a directive the implementing county is given a certain period of time during which it has to define the exact terms of implementation and the country needs to undergo all the necessary and required preparations. On some instances, the institutional setting of a member state is already aligned for the implementation of a directive, but more commonly, they have to adapt (transpose) it to their legislation. If this is not adequately done or if the directive is not implemented in practice (no direct effect) the European Court of Justice (ECJ) may start a legal action against a member state; by 2007 the Commission has warned 13 member states for non-compliances with environmental directives (Justice and Environment, 2007).

Natura 2000 is the most important legal framework in the field of nature conservation in Europe (Keulartz, 2009). It is composed out of the ‘Birds Directive’ which defines protection regime for bird species and the ‘Habitats Directive’ which defines protection regime for habitats and other species on the level of EU.

The official name of the ‘Birds Directive’ is the “Council Directive 2009/147/EC on the conservation of wild birds”, which replaced (undergoing several alterations) the modified “Council Directive 79/409/EEC”. The ‘Birds directive’ is meant to protect wild birds from the negative anthropogenic influence, both direct and indirect, done through loss or degradation of their habitats. This protection is performed through establishment of the network of ‘Special Protection Areas’ (SPAs). The directive also promotes various types of research (listing of endangered species, and populations of migratory species, studying the effect of chemical pollution on bird populations, etc. – listed in Annex V).

The protection of wild birds differs among species; grouped according to their status as depicted in the Annexes of the Directive:

 Annex I: It is prohibited to kill, capture or to keep birds, to destroy or to damage their nests or eggs, or to disturb birds during breeding or rearing. This applies to both domicile and migratory ones.  Annex II/1: can be hunted in all EU member states, as long as it does not jeopardize the conservation goals  Annex II/2: can be hunted only after agreement with the European Commission. They should not be hunted in vulnerable periods (such as return migration or nesting), or be hunted on large-scale nor by non-selective methods (especially by ones listed in Annex IV).  Annex III/1: can be killed or captured if done in accordance with the national legislation  Annex III/2: can be killed or captured after agreement with the European Commission

The greatest concerns that the ‘Birds Directive’ has raised encompass the hunting sector (Slepcevic, 2009). For that reason the ‘Guidance document’ on hunting under the ‘Birds Directive’ was created in the year 2004 and revised in 2008 (EC, 2008), which sets the rules for governing their exploitation: as healthy and viable populations must be maintained on long-term basis. Some birds that are in unfavorable conservation status from Annex II can be hunted if there is an existent, appropriate management plan for them. It should be noted that the derogation rules from the restrictions of the Directive are as follows: judicious use, small numbers, and strictly supervised and selective basis for their usage.

The Official name of the ‘Habitats directive’ is the “Council Directive 92/43/EEC on the Conservation of natural habitats and of wild fauna and flora”. The ‘Habitats directive’ aims to reach the favorable conservation status of habitats and species through the establishment of a network of ‘Special Areas of Conservation’ (SACs). In these areas the deterioration of natural habitats (Annex I) and the habitats of species is strictly prohibited, as well as the disturbance of designated species (Annex II).

The management of the SAC requires the existence of appropriate management plans either specially designated for each site or integrated into other (sectoral or administrative) management plans. Any activity that might have implications to a Natura 2000 site must have an appropriate assessment of the impact on the site. If the conclusions of the assessment find that the activity has negative effects on the site, then competent national authorities can forbid the activity or allow it after the implementation of compensatory measures (relates to designation of an alternative appropriate site). The provisions under the Directive must take into account economic, social and cultural requirements as well as regional and local characteristics (Article 2(3)). In a case where a site contains priority habitats (those in danger of disappearance; marked with asterisk [*] in Annex I) or priority species (those which are endangered, listed in Annex IV), a negatively affecting activity can still be performed in case of prevailing public interest

(related to human health, public safety or benefit to the environment) only after a positive opinion granted by the Commission.

If monitoring of a SAC area demonstrates an unsatisfactory situation of the conservation status of certain species (listed in Annex V), then the appropriate national authority has to subject them to management measures (same as if they were in Annex II). Similar to the ‘Birds directive’, it is prohibited to use indiscriminating means of capture and killing, as well as some modes of transport on species listed in Annex IV (Priority species) and in Annex V. The Directive protects a total of 220 habitats, 81 of which are forest habitats, accounting to approximately 1000 species. The designation of areas for protection should primarily focus on their contribution to the overall protection network on the European level, divided into five bio-geographical regions (Alpine, Atlantic, Continental, Macaronesian and Mediterranean). Natura 2000 network has an overall goal of reaching favorable conservation status for all of the habitats and species of Community’s interest. The term “favorable conservation status” for species is defined under the ‘Habitats directive’, Article 1, paragraph i, which states:  population dynamics data on the species concerned indicate that it is maintaining itself on a long-term basis as a viable component of its natural habitats, and  the natural range of the species is neither being reduced nor is likely to be reduced for the foreseeable future, and  there is, and will probably continue to be, a sufficiently large habitat to maintain its populations on a long-term basis

The favorable conservation status for habitats is reached when (Habitats directive, Article 1, paragraph e):  its natural range and areas it covers within that range are stable or increasing;  the specific structure and functions which are necessary for its long-term maintenance exist and are likely to continue to exist for the foreseeable future;  the conservation status of its typical species is favorable

Habitats of Community’s interest are the ones which (Habitats directive, Article 1, paragraph c):  are threatened with extinction in their natural range  have a small natural range following their regression or by reason of their intrinsically restricted area;  present outstanding examples of typical characteristics of one or more of the nine following bio-geographical regions: Alpine, Atlantic, Black Sea, Boreal, Continental, Macaronesian, Mediterranean, Pannonian and Steppic

Species of Community’s interest are also the ones which fall into categories of endangered, vulnerable, rare or endemic species.

Natura 2000 network encompasses 17.8% of land surface of EU 27 (EEA, 2013). The highest share of terrestrial coverage of Natura 2000 is present in Slovenia (35.5%) and Bulgaria (34%), while the lowest is in Denmark (8.5%) and the United Kingdom (8.7%), (EEA, 2012). In forest ecosystems, 8% of amphibians, 10% of reptiles, 27% of mammals and 11% of species of European interests are threatened with extinction (i.e. fall into one of the following three categories: critically endangered, endangered and vulnerable). The conservation status of species of European interest that are related to forest ecosystems is: 14.9% favorable, 29.3 unfavorable- inadequate, 23.5% unfavorable-bad and for 32.3% it is unknown. The conservation status of forest habitat types of European interests is: 21% favorable, 27.6% unfavorable-inadequate, 35.4% unfavorable-bad and 16% unknown. Forests ecosystems cover 43% of all SPAs and 48% of all SCIs (ETCBD, 2011). Natura 2000 covers 20% of the European Union’s forest habitats (CEPF, 2012).

Figure 3. Natura 2000 and the Emerald networks (Source: EEA, 2013)

3.2.Natura 2000 site designation process

The lists of pSCIs and SPAs are to be submitted to the Commission within three years of the notification of the Directive for EU member countries, and up to the accession date by the EU applicant countries. For this proposal, site assessment criteria for a given natural habitat types are the following (Annex III of the Habitats Directive):  Degree of representativity of the natural habitat  Area of the site covered by the natural habitat type in relation to the total area covered by that natural habitat type within national territory  Degree of conservation of the structure and functions of the natural habitat type concerned and restoration possibilities  Global assessment of the value of the site for conservation of the natural habitat type concerned Accordingly, site assessment criteria for a given species (Annex III of the Habitats Directive) are:  Size and density of the population of the species present on the site in relation to the populations present within national territory  Degree of conservation of the features of the habitat which are important for the species concerned and restoration possibilities.  Degree of isolation of the population present on the site in relation to the natural range of the species  Global assessment of the value of the site for conservation of the species concerned

In conjunction with the abovementioned scientific criteria, until the rulings of ECJ from 1999 (C-67/99, C-71/99, C-220/99; ECJ, 2006) the designation process also took into account economic, social and cultural requirements and regional and local characteristics. The list of sites of Community importance has to be established within six years after the notification of the Directive. If the Commission finds the approved list of SCIs insufficient, the member country can enter bilateral negotiations with the Commission, which can last up to a total of nine months, counting in the three months deadline of the Council to reach a decision. The designation process for Special Protection Areas (‘Birds directive’) falls on member (and/or applicant) states, while the Commission acts only as a consultative body (the Commission has the same role taking into consideration the derogation of amendments under the ‘Birds directive’.

Figure 4. Designation process for Natura 2000. (Source: Martinić, 2009)

The designation process of Special Areas of Conservation (‘Habitat directive’) is more complex than the designation process of SPAs. For SACs, the EU bodies besides consultative role also have to approve the list prior to the final designation. This procedure is performed in the following manner: A member (or candidate) state draws up a preliminary list of Natura 2000 sites and sets basic guidelines for their management (not mandatory). This is done in a participatory manner, and the list must be based on scientific research of habitats and species which follow a series of predefined assessments. This list is then sent to the European Commission (Directorate General for Environment and the European Environmental Agency) for evaluation. Within the designation process the preliminary list of Natura 2000 areas is called ‘potential Sites of Community Importance’ (pSCIs).

CROATIA EU

EU candidate Preliminary list of pSCI Preliminary control

Improved preliminary list of pSCI

Expert control

First biogeographical seminar pSCI list

NO 3 years Improved list of pSCI OK?

YES EU member Second biogeographical seminar

EU/EC list of SCI 6 years Acceptence of SCI asSAC

Figure 5. Designation process of SAC areas

The pSCI list is evaluated through bio-geographic seminars (organized by the European Topic Centre on Biological Diversity under EEA) whose members include representatives of member states, EU and NGOs. Every bio-geographical seminar is organized specifically for a single bio- geographic region (Croatia is part of the Mediterranean and Alpine region). In a case that an agreement cannot be made, the issue is forwarded to the Council of Ministers which sets the verdict. The designation of sites is based on “20% - 60% rule”, which means that if occurrence of habitats and species is covered in an extent higher than 60% it is regarded as sufficiently represented, while if it is represented by less than 20% of occurrence, it is principally regarded as insufficiently represented. Representations between 20% and 60% of occurrence are subjected to case-by-case analysis. When it comes to priority species and habitats the minimal representation is 80% of its occurrence; however, when a member state hosts more than 5% of the total areal of a specie or of a habitat, the criteria for minimum representation of priority species and habitats can be lowered. A list of pSCI’s can go through two bio-geographic seminars for the same region. When the pSCI list is agreed upon, the member state enters a phase of bilateral negotiations with the Commission. Only after the bilateral negotiations the Commission adopts the pSCI list of the SCI areas. The member state must hold bio-geographic seminars within the first three years after accession. This process is coordinated by the DG Environment.

The final designation of SCI areas as SPAs is done by the member state, and it has to be completed within six years after the designation of SCI areas by the Commission. The designation means the transposition of Natura 2000 requirements onto the national legislation, which can be done both on the level of laws and by-laws. What follows is the member state taking on full responsibility for reaching, maintaining and monitoring of favorable conservation status of habitats and species of Community’s interest.

3.3.Aims of forest management in Natura 2000 areas

Article 6 of the ‘Habitats Directive' lays down the general conservation regime for the special areas of conservation. Due to its high importance and lack of detail, in the year 2000, the Commission issued a 73 - page explanation manual (EC, 2000). The Manual provides detailed explanation of many important concepts, such as disturbance of species, deterioration of habitats, overall coherence of the network and significant effect, to a level where there is little space for misinterpretation. Natura 2000 is not meant to prohibit economical activities in its sites, but rather to limit those which can have a negative impact on species and habitats on the Community’s interest. In a case

15 of prevailing public interest an economic activity can be performed in Natura 2000 sites; nevertheless, in such cases, certain compensation measures have to be implemented (EC, 2000).

The principal mechanism for the management of the Network are the management plans specially designated for Natura 2000 sites, which can be either stand-alone documents, or can be integrated into other development or sectoral management plans. Any plan or project that might have significant impact on the network (even if physically located outside of it) will be subjected to an appropriate assessment of its implication on the respective site within the Natura 2000 network. If the plan or project does not adversely affect the conservation status of the site, (preferably after public consultation), the project can be implemented. In the case that the project does adversely affect the conservation status of the site and there are no adequate alternative solutions, then it can still be implemented for the imperative reason of public interest, which may be socially or economically defined. In these cases the member state has to take all compensatory measures necessary for the insurance of the overall coherence of the Network. Under the assumption that the site concerned hosts priority species and/or habitats, the only acceptable arguments of public interest are the ones related to human health and public safety.

Natura 2000 in forest areas is set to be governed by the postulates of sustainable forest management (in line with the Bruntland report and the MCPFE process; Wallström et al, 2003), thus recognizing the equivalence of its three pillars: ecological, social and economical. According to Helms (1998), the SFM can be disseminated into the following categories: conservation of biodiversity; maintenance of productive capacity of forest ecosystems; conservation and maintenance of soil and water resources; maintenance of forest contributions to global carbon cycles; maintenance and enhancement of long-term benefits to meet the needs of societies; a legal, institutional and economic framework for forest conservation and sustainable management. The above mentioned typology is used in the DG Environment`s Interpretation guide for “Natura 2000 and forests” (Wallström et al, 2003). Implementation of Natura 2000 in the forestry sector varies greatly among the member states, but it can be stated that the implementation of Natura 2000 in forestry is twofold (Wallström et al, 2003):  Predominantly in central and northern Europe the designated Natura 2000 areas are small or medium sized. These regions are characterized by intensive land use through its history, and thus making average forest size smaller than they are in other parts of Europe; and accordingly making on average smaller Natura 2000 forest areas. However, the management of forest under the Natura 2000 network in these regions stipulates compliance with strict environmental provisions, designation of fairly large budgetary expenses, purchasing of land and designating it for nature protection, and conservation of important habitats in a fixed stage of the natural succession cycle. All of these characteristics mark it as an “intensive” management system of forest under the Natura 2000 network.

 Predominantly in the south and eastern part of Europe (and some mountainous areas in other parts of Europe) the land use has been less intensive, and thus determining a coexistence of large and ecologically valuable forest ecosystems alongside the extensive farming. In these areas Natura 2000 forest sites are bigger than they are in other parts of Europe. In addition, they are characterized with preservation of traditional farming and forestry practices. This relatively liberal system of nature protection can be marked as an “extensive” one.

When referring to the implementation of Natura 2000 in the forestry sector, another dichotomy can be observed (EC, 2003):  Forests have their natural ecosystem cycle, which Natura 2000 recognizes; in that sense, the vegetation succession process, the natural disturbances through windfalls and tree decay, along with the human simulation – sustainable harvesting and mosaic distribution of age- groups are all recognized as an integrative part of the dynamic nature protection system. This approach generally applies to habitats and species listed in Annex I and Annex II of the ‘Habitats directive’.  Some forest habitats and species are considered especially valuable or endangered, and whose favorable conservation status cannot be reached with sustainable forest management; in such cases, an exclusive system of nature protection is established. This static approach generally applies to priority habitats and species (Listed with ‘asterisk’ [*] in Annex I, and Annex IV of the ‘Habitats directive’).

In the case of reaching conservation goals on private forests another mechanism is introduced in the domain of nature protection of forest habitats – ‘contract conservation’. This instrument is meant to serve as a balance to the forgone income due to implementation of the Natura 2000 network. By the scheme of ‘contract conservation’, the landowners themselves can perform conservation measures, or they can be performed by a third party (NGOs, contractors and the like). In turn, the compensation can be in a form of direct payment, tax breaks, compensatory land-use right(s), etc. In the case of direct payments, they are mostly decided on a case-to-case basis, and may vary greatly; the range as demonstrated starts from 80 €/ha in Spain and up to 4000 €/ha in Sweden (Torkler et al, 2007).

When it comes to the operational level of management of Natura 2000 forest sites, the network proposes the implementation of quantitative criteria and indicators for SFM of the Ministerial Conferences on the Protection of Forests in Europe (Annex I of the L2 resolution, 1998), and its accompanying Pan-European Operational Level Guidelines for Sustainable Forest Management (Annex 2 of the L2 resolution, 1998). These basic criteria for SFM are:  maintenance and appropriate enhancement of forest resources;  maintenance of forest ecosystem health and vitality;

 maintenance and encouragement of productive functions of forests (wood and non-wood);  maintenance, conservation and appropriate enhancement of biological diversity in forest ecosystems;  maintenance and appropriate enhancement of protective functions in forest management (notably soil and water);  maintenance of other socio-economic functions and conditions

It is imperative to note that, even with recognition of the principles of sustainable forest management as an adequate regime for management of forests under Natura 2000, the “Nature conservation objectives must have priority on Natura 2000 sites, while the economic and social function of the forest should also be taken into account” (Wallström et al, 2003, p. 29).

A good indication of the management of Natura 2000 forests in Croatia can be the Slovenian implementation, as they share majority of the Natura 2000 forest habitats. The propriety in the management of Natura 2000 in Slovenia fails onto the forest habitats, as they cover 70% of the network (EEA, 2013). According to a Slovenian study (Golob, 2006), the most important indicators of a favorable conservation status of forest habitat types are the following:  area of habitat  tree species composition in growing stock and in regeneration layer  horizontal structure and the scale of regeneration areas (phases diversity)  presence of old growth forests  habitat trees (cavity trees)  dead trees  presence of bush and herb layer  water bodies  quietness/disturbance free periods

The Slovenian implementation of Natura 2000 in forestry formally recognizes the equality in importance of ecologic and economic factors in forest management. It ardently follows the precautionary principle (Foster et al, 2000), by which it often happens that the demands of the habitats and species exceed what can be offered by sustainable forest management. Under such scenario, it is crucial to find a pragmatic solution that is in favor of all parties, e.g. establishing at certain places forest reserves with no active management, and in other places managing the forests without special restrictions (Vrček, 2007). As for the main types of forestry activities, the measures/restrictions for forest management recognized by the Slovenian Institute on Nature Protection (Vrček, 2007) are presented in Table 2.

Table 2. Forest management measures for Natura 2000 areas in Slovenia (Source: Vrček, 2007) Measure Explanation No new forest clearings for infrastructure Important for protection of small habitats No forest clearings in 50m radius Possible damages to habitat Parts of the habitat should be left to natural For areas of softwood species and flooded forests development Group regeneration of forest In cases where there is no natural regeneration Preservation of natural phytocenosis Valid for entire forest Establish natural phytocenosis Valid for entire forest No planting of alochtonous species Valid for all forests Do not regenerate with species X Species to be determined for each site Preserve uneven age structure of the forest Valid for all uneven aged forests Preserve at least 30% of forest as old-growth Valid for very large forest areas Leave at least 5% of deadwood Differential for coniferous and broadleaved forests, and for lowland and mountain forests Preserve habitat trees For preservation of bats and birds that require cavity trees Enable natural regeneration Valid for all habitats of Grouse, the Western Capercaillie and forest butterflies Enable natural regeneration of noble broadleaved Valid for maple species on slopes species Fell forest edge trees out of the forest May have negative impact on forest Fell with minimum damage to habitat Valid for felling, hauling and skidding Fell thick oak, beech and spruce trees with high For protection of great capricorn beetle, rosalia stumps longicorn and the capricorn beetle Fell broad leaved trees with high stumps For protection of the flying stag beetle Leave high stumps up to 25 meters away from water For protection of Carabus clathratus Broadleaved sortiments felled between 15.06. and For protection of rosalia longicorn 15.7. transported as soon as possible Broadleaved sortiments felled between 15.05. and For protection of flying stag beetle and great 15.9. transported as soon as possible capricorn beetle Broadleaved sortiments felled later than 15.08. are For protection of rosalia longicorn transported by 15.7. next year Broadleaved sortiments felled later than 15.09. are For protection of flying stag beetle and great transported by 15.5. next year capricorn beetle Preservation of forest edges Important source of food Preservation of forest clearings Important habitat for many species Preservation of undergrowth and ground layer of Important habitat for many species plants Preservation of small water surfaces Important for amphibians Preserve 300m buffer of no forest activities around Black stork is very sensitive to disturbance known nests of black stork in time of nesting Preserve 400m buffer of no forest activities around The Lesser Spotted Eagle is very sensitive to known nests of the Lesser Spotted Eagle in the 1.05.- disturbance; keep the locations secret 31.10. period Preserve 500m buffer of no forest activities around Very sensitive to disturbance; keep the locations known nests of the Golden Eagle and the White- secret tailed Eagle in time of nesting

Preserve 300m buffer of no forest activities around Very sensitive to disturbance; keep the locations known nests of the Eurasian Eagle-Owl in time of secret nesting Preserve 500m buffer of no forest activities around Very sensitive to disturbance; keep the locations known nests of the Western Capercaillie in time of secret nesting

As for any other habitat type, the actual management regime of the forest habitats is to be decided upon by the member states. Most of the EU support is through LIFE funding, which provides support to the designation of appropriate management plans. As for direct technical support, until mid-2013 the Commission had issued technical management guidelines for four habitat types (9070, 9110, 9360 and 9530) out of the total of 81 forest habitats listed in the ‘Habitats directive’ (DG Environment, 2013).

4. Methodological approach

In a broader context Natura 2000 is just one out of approximately 200 pieces of EU law related to environmental protection to which the EU acceding countries have to adhere to. This process does not require simple transposition of the acquis communautaire, but also building-up institutions and structures by which these legally binding agreements can be effectively implemented. This process is commonly understood as Europeanization of domestic environmental governance in Central and Eastern European Countries (Carmin and Vandeveer, 2004; Börzel, 2009). The “typical” mode of governance in this context in the pre-accession phase was an EU top-down influence on the national policy domain. Such scenario allowed for the policy making process to be dominated by the states` environmental protection administration, low involvement of stakeholders and strong inclusion of non-state actors, mostly the transnational NGOs (Carmin and Vanderveer, 2004). After the accession to the EU this mode is to a large extent replaced (Fairbass and Jordan, 2001) by the system of multi-level governance (Marks, 1992, 1993). In this system the states are still the dominant actor in the EU integration process; however, power is shared with sub-national and super-national actors. In turn, this process dilutes authority of the state, which has different conceptions on the integration process from the EU bodies. Due to the complexity of the decision making process the policy outcomes in most cases are the lowest common denominator of a limited subset of decisions. As actors from any level can be directly connected to any other level, the state no longer has the brokerage role between the super-national and sub-national actors, which are being used by the EU to strengthen the integration process beyond the level that is favorable for the national actors. From a theoretical perspective, this process is in line with neo-pluralism (Lindblom, 1977), in which different interest groups are competing over political influence, unlike the pluralist perspective

(Dahl, 1961), where the state is no longer a mediator of interest. The state is regarded as a relatively autonomous actor with its own interests, and the political agenda is biased towards multinational interests and dominant states.

Europeanization can be conceptualized as “the process of influence deriving from European decisions and impacting member states’ policies and political and administrative structures” (Heritier et al., 2001: 3). The role of NGOs in this process is seen from one side as gaining importance in national policy formulation by strengthening their capacities and links with the EU institutions (Carmin and Vandeveer, 2004), whereas others (Börzel and Buzogany, 2010) see the dominance of a top-down approach due to the limited capacities of NGOs and limited capacity for horizontal and vertical coordination. EU policy is effectively implemented and complied with if the policy is fully incorporated into national law. This is accomplished with the conflicting national rule being amended (formal implementation), followed by the competent authorities providing adequate administrative resources, all with a purpose to put the policy objectives into practice, while monitoring, and encouraging (and/or coercing) rule-consistent behavior by the actors (practical implementation) (Börzel, 2003). On the lowest level of Europeanization (absorption) countries just incorporate the acquis into their domestic policies without alteration. On a medium level of change (accommodation) countries “patch up” (Héritier, 2001) new European rules onto existing domestic policies without substantial modification. Europeanization reaches its full extent then there is a major domestic policy change (transformation) in which countries replace of substantially adjust the existing policies (Börzel and Risse, 2003). The extent of institutional change needed for effective implementation of the EU policies depends on the extent of misfit between the national and the EU policy. The greater the misfit, a greater institutional change is required to effectively implement the EU policies. The causality of change can be explained by (Börzel and Risse, 2000, 2003):

 Differential empowerment It is consistent with rational choice institutionalism (Hall and Taylor, 1996). Under such approach, the EU through its policies and institutions provides new opportunities and constraints for the redistribution of power and resources among its national actors. Based on its interests and cost-benefit calculations the EU can instigate national policy change by selectively empowering certain stakeholders. The empowerment process during the accession phase rests on the conditionality of the accession, i.e. on the strict acceptance of the acquis, in which the EU threatens with postponing the accession and offers incentives in the form of financial assistance and EU membership (Schimmelfennig and Sedelmeier, 2008). Accession negations empower the EU and the central national governments (Grabbe, 2004). Since the pre-accession system of conditionality does not function upon accession to the EU, national non-compliance towards the EU can be expected (Sedelmeier, 2008). The mechanisms for post-accession compliance include legal enforcements by the EC and the ECJ, and the empowerment of non-governmental actors

(NGOs), along with blaming and shaming campaigns against national governments (Börzel and Risse, 2003).

 Internalization of norms and development of new ideas It is consistent with sociological institutionalism (Hall and Taylor, 1996) and with new institutionalism (Koeble, 1995). This theoretical stream is also based on the assumption that actors behave in order to comply with the social norms they regard as appropriate and legitimate. Such change is facilitated by the actors` networks and epistemic communities acting as entrepreneurs of new policy ideas and agents of change. Normative change occurs through scientific knowledge, participatory exchange and strategic constructions of moral arguments developing upon policy failures and in times of crisis. Combined with supportive informal institutions such as political culture of consensus-oriented and cost-sharing policy making, the internalization of norms and redefinition of interests among domestic actors can lead to domestic policy modifications (Börzel and Risse, 2003).

Figure 6. Two logical frameworks of domestic change (Source: Börzel and Risse, 2003)

Both of these processes may occur simultaneously or successively, and they do influence each other. The rational choice approach has a more distinct set of assumptions and offers a clear theoretical standpoint, whereas the institutional approach provides the structural setting within which the rational choice actions are defined (Powell and Di Maggio, 1991). The rational choice analysis lacks the "cultural embeddedness” of the actors` actions which can be viewed as rational only within a certain social structure (Granovetter and Swedberg, 1992 p. 75) and within the context of social exchange (Blau, 1964). Conversely, the institutional approach is more suitable for explaining stability and inertia of institutions, whereas it has more difficulties in explaining institutional change and in establishing causality. From the institutional perspective change might occur as a result of internal contradictions and misfits within the institution itself (Tolbert

22 and Zucker, 1996) or may arise as a result of normative, mimetic and coercive isomorphism by which organizations (DiMaggio and Powell, 1983) and institutions (DiMaggio in Powell and DiMaggio, pp. 64-74) cope with uncertainty. Following the internal drivers of change the institutions are becoming increasingly different because they develop their own logic of conflict and legitimacy, whereas by following the external drivers of change (“institutional isomorphism”) institutions develop similar patterns of social structure. The Rational choice theory provides explanation for cooperative behavior and collective action which in turn explains the cultural and social norms and institutions. From that perspective rational individuals design institutions in order to achieve certain goals and to form a structure for exchange of relations (Koeble, 1995). The overview of the research design of Chapter II is presented in Figure 7.

Figure 7. Research design of Chapter II

Figure 7 shows that the two approaches of the Europeanization of environmental governance are used to trace the national implementations of Natura 2000 in many EU member countries, which is based on the literature review. The purpose of the literature review was to gain insights to the Natura 2000 formulation and implementation, and to analyze the role of its actors from the perspective of social sciences. In order to identify such publications several on-line search engines and data bases have been used; ‘Web of science’ and ‘Google Scholar’ including ‘Science Citation Index Expanded’ and ‘Natural Science Citation Index’. The following key terms were used: “Natura 2000” and “Policy implementation”; “European Union”, “Environmental policy” and “Implementation”; “European Union” and “Biodiversity”. The first round of search was done in September 2011 and repeated in June 2013.The search resulted in

169 articles, out of which 40 were chosen for analysis; as the remaining did not fit the purpose of the literature review. This list was further expanded by nine other social science papers that were referenced in the first group of papers. The primary source of legislative and expert literature was the EC`s site on Natura 2000 (EC, 2012). All the relevant documents referenced in the EC`s documents were also used, which resulted in 45 legislative and expert documents. In order to improve the analysis a separate search on Natura 2000 for Slovenia has been made with key words “Natura 2000” and ”Slovenia” on ‘google.si’ and ‘Google Scholar’; which bore one relevant graduate thesis, six expert documents, three legislative acts and eight conference papers. The primary source of legislative and expert literature on the implementation of Natura 2000 in Croatia was the Internet site of the State Institute on Nature Protection (public institute responsible for the implementation of the Network; SINP, 2011) and the relevant literature referenced in those documents. The Institute began with the preparations for Natura 2000 in the year 2002 through a series of internationally funded projects, during which time they managed to produce and compile a substantial number of relevant documentations. The Institute has accepted to make available a large part of that documentation for the purpose of this research; including project documentation, presentations, minutes from the meetings with stakeholders of Natura 2000, and their internal documentation and GIS information on the Natura 2000 sites. This resulted with 101 relevant documents on the implementation of Natura 2000 in Croatia. Analysis of these documents produced an extensive list of stake-holding organizations and individuals who were interviewed for this research. The most important documents for the selection of interviewees were the ones related to the project Knowledge for Ecological Networks (SINP, 2007; SINP, 2008), within which identification and analysis of stakeholders for the National Ecological Network (a direct predecessor of Natura 2000) has been performed. For identification of stakeholders within the forestry and nature protection sector additional important documents were consulted: the National Forest Policy and Strategy (Government of the Republic of Croatia, 2003) and the list of stakeholders for the FSC system of forest certification (Croatian Forests, 2010). The selected interviewees were also asked to name other relevant groups of stakeholders. In the period from March 2010 until June 2013 a total of 57 interviews have been performed, where 19 individuals have declined to be interviewed. As a supplement to the interviews, an analysis of the minutes from the stakeholder consultation workshops within the PHARE project (SINP, 2009) has been conducted; through which opinions and beliefs of all relevant groups of stakeholders have been identified. Another supplementary source of data was the notes from the two researchers who were allowed to follow the meetings of the expert working group on forestry in Natura 2000. The working group held a total of eleven meetings which lasted from March 18th, 2010 until October 11th, 2012. The researchers who were present at the meetings took detailed minutes of the meetings and have focused on writing quotations that represent opinions of different stakeholders on Natura 2000, and have also documented the patterns of communication that occurred between the members of the working group.

5. Results

5.1. Formulation of the Natura 2000 directives in general

The preconditions for understanding the implementation of Natura 2000 is the comprehension of the political factors which led to the preparation of the ‘Birds’ and the ‘Habitats’ directives, the process of the preparation of the Directives, and the mechanisms by which the Directives are enforced.

The origins of the ‘Birds’ directive can be traced to ‘The Convention on Wetlands of International Importance’ that was signed in Ramsar, Iran, in 1971. Faced with a sustained citizen’s campaign from Germany and the Netherlands, in 1973, the EC introduced the ‘Fist Environmental Action Plan’ which had emphasized the role of biodiversity. Upon continuous studies and consultations with wildlife experts the proposal of the Directive was issued in 1976 and was more comprehensive than it was originally envisaged by the European Parliament. The Directive was finally adopted in April 1979, despite the objections from member countries, especially coming from Italy and France (Fairbass and Jordan, 2001) on the continuous expansion of the acquis.

One of the important factors that contributed to the adaptation of the ‘Habitats’ directive was the window of opportunity created by the Rio discourse on sustainable development, especially ‘The Convention on Biological Diversity’ and the ‘Convention on the Conservation of European Wildlife and Natural Habitats’ (Bern, 1982) (Chilla, 2007). The NGOs have recognized the ‘Habitats’ directive as an opportunity for the EU to implement the ‘Bern Convention’ and to that end have started a strong lobby campaign (Ferranti, 2011). The objective was for the areas under the ‘Habitats’ directive to match, according to the ‘Bern Convention’, the corresponding ecological network for the countries outside the EU which is called the ‘Emerald Network’. National level contribution to the ‘Emerald Network’ is called the ‘National Ecological Network’. With endorsement from the ‘Pan-European Biological and Landscape Diversity Strategy’ (PEBLDS, 1993) the Natura 2000 network and the ‘Emerald Network’ together make the Pan-European Ecological Network’ (PEEN). In the context of forest policy the reasons for strengthening the environmental organizations can be traced back to the lack of trust in governments and the forest industry to take into account adequate measures towards the protection of the environment (Ingram and Enroth, 1999) and to install acceptable safeguards for trade of illegal timber (Barden, 1994). This entrance to the policy arena has been so strong that they have been taking on roles traditionally assigned to governments, exerting influence on national and international policy making (Anderson et al., 1998). In order to influence the drafting of the ‘Habitats’ directive the ENGOs based in Brussels,

25 in 1991, created the ‘European Habitat Forum’ (EFH). The EHF (mostly WWF) had formed a coalition with the DG Environment, who had jointly drafted the ‘Habitats Directive’. As a response to these events the land-user groups (European Land Owner Organization, Confederation of European Forest Owners Organization, Copa Cogenca and The European Federation of Associations for Hunting and Conservation) had formed the Natura 2000 Users` Forum. As a reaction to the coalition of EHF and DG Environment, the Natura 2000 Users` Forum had established a countervening coalition with the DG Agriculture (Weber and Christophersen 2002).

The ‘Habitats Directive' was passed down with very little consultation involving stakeholders and policy actors which had to implement it; such approach raised a high level of resistance (Keulartz, 2009). As the Directive was adopted in 1992 under the Dutch presidency, it was also perceived as the “Dutch Directive” (Wurzel, 2008). Operationally the Directive originated from the Dutch Nature Policy Plan (LNV, 1990), by which the goal of nature protection was to be achieved by the ecological reference as the benchmark, i.e. a scientifically designed state of nature characterized by conditions which would exists if there was no human influence. This goal was to be achieved within the ‘National Ecological Network’, which spanned onto 21% of the Netherlands.

In 1993 the EHF became a part of the ‘Habitats Committee’ which is chaired by DG Environment and composed of the EU member state representatives, all with a task of steering and monitoring the implementation of the Directive. The bio-geographical seminars, as the formal forum for the negotiation of the lists of protected sites between the member states and the Commission, are open for the participation to the ETCBD, EEA, the EC and to the representatives of the member countries. They are also open for participation of EHF and NGOs which have prepared their own, alternative version of national Natura 2000 protection areas (“shadow list”). After many applications (Fairbass and Jordan, 2001), the Natura 2000 Users` Forum was allowed to participate to the bio-geographical seminars in 2006 (Ferranti et al, 2013). The shadow lists were in some cases also used by the European Court of Justice (Weber and Christophersen, 2002). Another tool to influence directives was the joint effort of the ‘Green Party’ in the European Parliament and WWF to use the funds of the ‘Common Agricultural Policy’ for the implementation of the Directives. In this way the relation of the Commission with the sub-national actors was strengthened, which gave another opportunity to circumvent the influence of the national governments (Börzel, 1997).

Approximately one third of habitats listed in Annex I of the ‘Habitats’ directive are forest habitats. Given the fact that the adequate share of managed and un-managed old-growth forests is an explicit goal for the Natura 2000 set by the Commission (European Commission, 2000), unfortunately, on a national level, Natura 2000 is more often perceived by the forestry sectors as

26 a threat than as an opportunity. One of the aims of the ‘Confederation of European Forest Owners’ (CEPF) is to lobby for the changes of the Directive; however, in the current policy setting the fulfillment of that goal seems highly improbable (Weber and Christopherseon, 2002).

5.2. National implementations of Natura 2000

Although Natura 2000 network was modeled according to the Dutch experiences from the National ecological network, its implementation in Netherlands was one of the most troublesome implementations (Keulartz, 2009). The central Dutch government believed that Natura 2000 could be implemented with just minor changes to the existing system, and so the Ministry of Agriculture, Nature and Food Quality almost literally translated the Directives into national legislation (Beunen, 2006) without any institutional changes. No substantial guidelines for the implementation of the Network were made, which resulted with vaguely defined impact assessment that mainly supported the decisions of the investors. This was followed by many lawsuits instigated by the NGOs against the investors for the validity of the impact assessments. The Dutch civil society had enough capacity to follow the authorization processes and to collect the required bio-geographical data (Rosa et al, 2005). These were the main reasons for breaching the deadline for submission of the list of protected areas, for the delays in the implementation of the Network, and for the subsequent infringement procedures (Ferranti et al, 2010). Another reason for a subsequent revolt against Natura 2000 was the lack of dissemination of information by the Ministry during the transposition process. The national government also did not expect the influence of the EC (infringements) against the national government for not superposing ecological interest over societal ones in the designation process (Van der Zouwen and Van den Top, 2001).

The Netherlands was not the only country which struggled with the implementation of Natura 2000, as more than half of the European Union’s 15 member states have been put to trial by the Commission at the European Court of Justice for not punctually submitting the list of designated sites according to the ‘Habitats Directive’ (Paavola 2004). The first four countries that were taken up by the Commission to the European Court of Justice for not designating the SPAs and pSCIs were Germany, France, Ireland and Finland, and most of the submitted lists were found to be unsatisfactory comparing them with existing scientific inventories of bird populations and habitat (Krott, 2000).

In France it took ten years for the national courts to fully apply (December 1984) the hunting restrictions (no hunting during breeding and rearing of protected species) on birds posed by the ‘Birds Directive’. The implementation of the Directive was subsequently stalled from 1997

27 onwards when the lower French administrative courts started to systematically breach the dates of hunting bans, due to the fact that the hunting of birds became the symbol of intrusion of urban population onto rural traditions (Alphandery and Fortier 2001). The ‘Birds Directive’ was finally on track of its implementation when compliance of the hunting bans was installed in 2006 after the EC had threatened France with penalty payments. Another way to systematically hamper the implementation of the Network was the refusal of the French courts to adhere to Article 6, by which the competent authorities (the Ministry of Environment) was not bound to follow the authorization procedure of the Article 6 of the ‘Habitats Directive’. Furthermore, it decreased the success rate of litigations aimed to enforce the sites` protection regime. The EC`s penalty threats have put pressure on the Supreme Administrative Court to accept direct effect of the Article 6 in the case of protection of birds, and in 2005 to rule towards the acceptance of species and habitats under the ‘Habitats Directive’. The French designation of pSCIs` was completed in 2000, and was led by the Ministry of Environment. First, the state scientists coordinated the drafting with some public dissemination of results, but soon opened to joint drafting with local authorities. The first opposition came from private forestry because the initial proposal encompassed 25% of forest land (13% of total land cover) and was agreed upon without adequate flow of information to stakeholders. From the position of the Ministry of Agriculture one of the reasons behind the initial Natura 2000 proposal was the “militant ecologist” attitude of a part of the personnel on the Ministry for the Environment, whose primary role in the defining protection areas was “one of extending the territory under control” (Alphandéry and Fortier, 2001). Foresters found support in hunters, the agricultural sector and in the fisheries sector, all of which have formed a unified lobby - “Group 9”, under the parole of “not against but in line with the owners and users of nature” (press release from the National Union of Departmental Hunting Federations, 10th of April 1996). Nevertheless, the central motif which united these members was the question of the legitimacy of the drafting procedure done by the Ministry of Environment – i.e. basing territorial policy solely on biological-scientific arguments. Due to the land users` pressure the process of site designation was suspended in the year 1996, and then subsequently restarted back again in 1997. That year the Ministry of Environment gave in and included the arguments of the local stakeholders into consideration. The main mechanism for the inclusion of these socio-economic interests was the establishment of the ‘national monitoring committee’, composed of many of the representatives from “Group 9”. The Committee had grouped the areas depending on the level of conflicts that might arise from their nomination, all with a goal of nominating a total of 2.5 – 3% of land cover for Natura 2000. Even the new Minister coming from the Green party acknowledged the usage of local and national power relations in the designation process, which led to a proposal of 5.7% of land coverage (Alphandéry and Fortier 2001).

The “negative” position of the French Ministry of Agriculture and the “scientific-managerial” position of the Ministry of Environment had stalled the practical implementation of Natura 2000.

Such scenario led to the EC penalizing the Ministry of Environment on several occasions for not taking into consideration the interests of local stakeholders in the implementation of the Natura 2000. A good example of that was the ‘Poitevin Marsh’ case (C-96/98; and C-103/02), where non-state actors demanded legal contractual arrangements when designing the management of Natura 2000 sites. This pressure, soon after made the Ministry of Environment establish for each site a local “steering committee”, whose members had contractual agreements on the implementation on Natura 2000. The role of non-state actor in the implementation of the Network was financially backed-up by the LIFE-Nature funds (maximum up to 75% for priority and up to 50% for non-priority species and habitats). The rest of the cost was financed by the Ministry of Environment. This mechanism provided strong incentives for local stakeholders to actively engage in the protection of Natura 2000 sites; nevertheless, this system also suffered from the principal-agent problem (Rees, 1985) and had varied success across the country (McCauley, 2008). This led to coverage of 7.6% in 2006, and has even led to situations where many local steering committees have applied for Natura 2000 contracts before the objectives of conservation have been agreed upon. These site-related Natura 2000 contracts on average entitled 30 000€ of costs per year for the annual review of a document outlining the agreed objectives (i.e.. meetings, facilities, etc.), 15 000€ for annual management of a site, and 16 000€ per year for scientific reports prepared by the committee. In 2006 there were 1029 committees, and it is estimated that for their work in the 2006-2010 period a total of 3.070 million Euros will be required (McCauley, 2008).

As was the case in France, the UK National courts systematically hampered the implementation of the Network by not referencing the rulings of the ECJ in their own processes. This led to strengthening the role of the ENGOs and subsequently to activation of infringement procedures at the ECJ regarding the UK implementation of the Network (Fairbass and Jordan, 2001). In the case of the German transposition of Natura 2000 the deadlines have been breached, and only after the pressure of infringement procedures by the European Court of Justice have the protection areas been clearly defined. At one public hearing of the Bavarian Government the landowners initiated a total of 27 000 objections (Von Haaren and Reich, 2006; Chilla, 2007). Although originally the ‘Birds Directive’ had its own protective regime, the subsequent (C-57/89 [1991] Commission v. Germany,) rulings of the ECJ had defined a stricter interpretation on the possibilities by which a deterioration of a site designated for the protection of birds might be approved. Such maneuver effectively aligned it with the protection regime of the ‘Habitats Directive’ as defined in its Article 6. The continued pressure from the environmental groups and the frequent juridical halting of plans and programs had eventually changed the position of the competent authority which started to place much more effort in preparing the appropriate assessments (Rosa et al, 2005).

The Italian government managed to submit pSCIs on time, mostly due to the scientific input from the Italian Botanic Society, the Italian Zoologic Union and the Italian Society of Ecology. The mapping was coordinated by the Ministry of Environment, Land and Sea Protection, and financed by the LIFE-1994 fund (Ferranti et al, 2010). Other NGOs and the public were not involved in the designation process. The management was passed down to the level of regions, but the implementation was “not promising”, as the regional authorities lacked the capacity necessary for monitoring Natura 2000 areas and for drafting and enforcing the management plan. Another reason for a weak practical implementation was the Italian ‘top-down’ political culture, which was used in the designation of areas; the regional administration was clinging onto guidance from the level of Ministry which was not effectively involved. The formulation of impact assessments was also passed down to the level of regions which did not have the capacity do design them. This led to the EC initiating legal actions against the Italian government which has destabilized the conservation status of the Natura 2000 areas (Postiglione, 2006). The chosen Natura 2000 areas did not integrate the existing protected areas into one coherent network. The Natura 2000 network was also found unable to maintain 44-80% of its species and habitats in “favorable conservation status” (Mariano et al, 2008; but authors also state that Natura 2000 is probably more robust than the modeling suggests).

A similar political culture exists in Greece, where the institutionalized power and influence rest on the central public authority. Initially, Natura 2000 responsibility for nature protection was under the Ministry of Agriculture`s forestry administration, which did not allow much participation in the decision making process. However, in 2005 the Ministry of Environment designated Natura 2000 areas together with the external experts, creating an overlapping authority on nature protection and a severe gap in the implementation of the Network. The Directives were literally transposed onto national legislation and due to the short history of nature protection in Greece the transposition was not followed by the systematic build-up of institutions needed for their implementation (Apostolopoulou and Pantis, 2009). An underlying problem in the implementation of Natura 2000 was the widely accepted premise that the national interests in protected areas are essentially environmental whereas the local interest is essentially socioeconomic and connected to the distribution of power. This has systematically hindered the dissemination of decision making rights to the regional level, and kept the practical implementation on a symbolic level (Papageorgiou and Vogiatzakis, 2006).

From an ENGO perspective (WWF, 2006) the main problems in the implementation of the Network are the lack of adequate management plans, species conservation measures and plans, and insufficient considerations of assessments for plans and projects from the Article 6 of the ‘Habitats Directive’. From a legal perspective the main problems in the transposition of Natura 2000 directives in Estonia, Czech Republic, Hungary and Slovakia were the narrowing down of the obligations for appropriate assessments and of alternative solutions that need to be

30 considered before authorizing a plan or project. The concept of compensatory measures was most often not understood yet implemented, and alternative solutions were not searched for. The preconditions for the initiation of appropriate assessment (especially for large projects) were unclear, leaving the opportunity for manipulation. In cases when the assessments were carried out, the conclusions of absence of adverse effects to the integrity of the sites were too easily made (Justice and Environment, 2007). These practices go against the rulings of the ECJ (C- 127/02), which state that if there exists doubt on the presence of adverse effects to the integrity of a site, the competent authority will have to refuse the authorization.

In Hungary the implementation was delayed mostly due to lack of coordination (and even conflict between the agricultural and environmental administration) and due to the public administrations` lack of capacity. Hungary was only one out of 10 candidate countries that did not submit Natura 2000 proposal until the accession in 2003. Bird life Hungary (supported by Bird life International) was very close to the Ministry for Environment and Water. Their relation was based on long-term informal contacts, and was characterized by the revolving doors policy with NGOs. The SPAs were based on Important Birds Areas, 80% of which entered the official proposal of SPAs. This process was performed by Birds Life Hungary, EEF Hungary and Friends of the Earth Hungary (Mertens, 2009). The Ministry made the pSCI list together with the directorates of national parks and did not make the proposal public until it was submitted due to the (justified) fear of political complaints from the land owner groups (Buzogany, 2009). Subsequently, in the bio-geographical seminar on the Pannonean region, the NGO representative had almost all (more than 95%) of his suggestions accepted. The key factor for this success was good preparation by the CEE web (mandated by the European Habitats Forum) and experiences from previous seminars (Mertens, 2009). The situation escalated after the designation of Natura 2000 areas when the central government did not have enough financial resources to compensate the landowners, who none the less had to stop/modify their activities. As such, Natura 2000 has increased the capacity of the NGOs but due to the strong opposition from the landowners group they had only a limited effect in mobilizing the public and in most cases, their legal actions against investors were lost. The main reasons for the loss of court cases were not enough concise implementation of legislation related to impact assessments and lack of specific judiciary training (Börzel and Buzogány, 2010). The designation of Natura 2000 areas was the primarily reason for the lack in the implementation of the National Programme for the implementation of the acquis in Hungary (Moscari, 2004).

In Romania the state administration (the Ministry of Environment and Sustainable Development, Directorate for Biodiversity and Biosafety) also suffered from a lack of capacity to designate the areas, and there was a lack of scientific data on the species and habitats; but unlike Hungary, Romania did not have enough money to outsource this activity (Krüger, 2001). Like in Hungary, the Romanian transposition of the Directives was done with little participation of stakeholders

31 and was also marked with a conflict between the Ministry of Environment and the Ministry of Agriculture, which represented the interest of land user groups (Börzel and Buzogány, 2010). The Romanian NGOs were weak and uncoordinated, focused on local issues and did not have enough capacity to engage themselves into national policy formulation processes (Dragomirescu, 1998). This was recognized by the Ministry of Environment who did not include them in the designation process, and had treated them with skepticism over their legitimacy and expertise (Börzel and Buzogány, 2010). The designation process speeded up in 2005, when backed up by EU-funded LIFE and PHARE projects, the Ministry of Environment involved research institutes, local authorities and NGOs (WWF, Pro Natura, Romanian Society of Ornitologists, Milvus Group; under coordination of BirdLife International) in the designation process. However, NGOs were not involved in subsequent implementation of the Network, leaving them to actively lobby in Brussels against ineffective implementation of the Network (Börzel and Buzogány, 2010). One of the impacts of the symbolic practical implementation of the Directives (Angelova et al, 2009) was a continuous loss of old-growth forests, where the majority (72%) of loss occurred within nationally protected Natura 2000 areas. Due to the lack of institutional change, majority of the loss, triggered by poor management practices and socio-economic changes, was in accordance to the national legislation (Knorn et al, 2013).

In the beginnings of Bulgaria`s negotiations on EU accession the EC had regularly reported on significant misfits between the EU and domestic policy and lacking administrative capacity in the field of biodiversity conservation (EC 1997, 2001). In order to meet these demands a new Law on biological diversity was adopted in 2002, which was proposed by the Ministry of Environment and Water together with environmental NGOs. Although this Law has been seen by the EC as a progress it was still regarded as incomplete transposition (EC, 2003). With a threat of infringement procedures the law was amended in 2005, achieving almost full formal transposition (WWF, 2006). The mapping of the Natura 2000 areas was given to NGOs (Green Balkans) and scientists from national research organizations. This activity was supported both by externally funded project and with national funding (WWF, 2005; Green Balkans, 2013). In November 2006 NGOs submitted to the Ministry of Environment and Water a proposal which covered 35% of the country. At the same time both the supporters and the opponents to Natura 2000 engaged in public protests. Due to this highly political debate an official proposal of protection sites was not submitted by the accession date (January 1st 2007), and with a three month delay submitted a minimal proposal with 18% of coverage. Upset with these cutbacks the NGOs in Bulgaria formed an advocacy coalition called “Coalition for the Nature” and directly submitted their own proposal to the European Commission (Brunwasser, 2007). The Law on biological diversity was changed again in 2007 to allow for the developments in the Black Sea coast and mountain regions that were authorized just on administrative screening with no real environmental impact assessments, which in the vast majority of cases showed no negative impact (WWF 2008, Hristova, 2012). Between 2007 and 2009 the Coalition for the Nature

32 complained many times to the EC on the improper implementation of the Directives, which permitted the EC to initiate eight infigment procedures. In 2012 all these pressures resulted with official submission of protection areas with the coverage of 34%, which is very close to the first proposal that NGOs have prepared (EP, 2012; Hristova, 2012).

In Slovenia the Ministry for Environment and Spatial Planning was in charge for the implementation of Natura 2000, and as in other countries, there was lack of dialogue and trust between them and the Ministry of Agriculture who traditionally had different philosophies and concepts about nature conservation: for forestry sector nature protection is integrated within sustainable management, whereas for the nature protection sector nature protection is segregational, separated from sustainable management (Ferlin et al, 2005). The forestry sector was afraid of losing a part of its administrative authority, and nature protection did not recognize the environmental aspects of forest management plans. The project of designation of sites was marked as a political priority, so the project was chaired by the state secretary and had three working groups: inter-ministerial, technical and communication. Although a communication structure existed the local level stakeholders were not adequately informed on the Natura 2000 and on the process of its implementation. Moreover, it was a one-way communication channel (Kolar-Planišič, 2004). There also was not enough of stakeholder`s involvement, and in most cases there was a lack of scientific data for many species and habitats (WWF, 2005). The only exception was the forestry sector. The pSCI proposal for the forest habitats prepared by the Slovenian Forest Service was accepted with minor alterations; unfortunately, forestry experts were not present at the defining of forest related SPAs` and species pSCIs` (Ferlin et al, 2005). The transposition of Natura 2000 directives in Slovenia was done with a low level of politization. The proposal was provided to the Slovenian Parliament on a short notice before the accession. Given their limited knowledge on the subject matter and the pressure from EU conditionality, they have accepted the proposal with no objections and with a high majority of votes (44 in favor and 8 against). In the analysis of informal structure of the implementation of the Network, Boh (2004) defines local communities as the central actor and expresses great ambiguity on the practical implementation of Natura 2000.

5.3. Natura 2000 in Croatia

5.3.1. Formal compliance, 2002-2013

From the Croatian application to EU membership in the year 2003, the accession process has been the dominant driver of domestic policy-making. During this time the EU conditionality principle has prevailed in defining the public interest in all policy sectors (Markušić, 2013). Already in 2003 Croatia adopted a new Law on nature protection followed by one amendment in 2008 and eight by-law ordinances in order to transpose and comply with the EU biodiversity acquis (MC, 2010). In the 2007 screening report on Croatia, Chapter 27 “Environment”, the Commission acknowledged advanced alignment of the Law on nature protection to the Birds and the Habitats Directives (EC, 2007b). Yet, the ordinance on Natura 2000, whose annex would contain the preliminary national list of pSCIs and SPAs, has still not been adopted. The administrative body responsible for the implementation of the Natura 2000 network in Croatia is the State Institute for Nature Protection (SINP). The designation of Natura 2000 sites and a strengthening of state administrative capacity were the recurring requests for improvement in all of the Commission’s monitoring reports on Croatia’s progress in the period from 2006 to 2011, even after the negotiation chapter 27 “Environment” was closed in December 2010 (MFEA, 2012). Scientific preparations for Natura 2000 had already started in 2002, when the LIFE III CRO- NEN project was launched. The purpose of the project was to establish a proposal for a National Ecological Network (NEN) that would secure the protection of habitats and species pursuant to both national and EU biodiversity legislation. Within this project SINP delegated tasks of biodiversity inventories to private consultancies, public research organizations and few NGO activists. The non-state ecological experts found that 47% of the terrestrial and 39% of the marine territory of Croatia would comprise the NEN, which encompasses all the Natura 2000 species and habitats as well as several ones that are of national interest. This project enabled SINP to develop a proposal for regulation on establishing the NEN which was adopted by an ordinance in 2007. In Croatia there was a lack of interest among experts to participate in the data collection needed for the implementation of the Habitats Directive. The level of information on the EU funding opportunities was low, and the government was often not open to cooperation with NGOs, who on the other hand also had limited capacity to follow the process (WWF, 2006).

Figure 8. National ecological Network (Source: European Centre for Nature Conservation) and the forest habitats in Croatia with dot NEN forest areas (Source: Vukelić et al, 2007)

The management measures for forest habitats under NEN are set in Annex III of the Ordinance on habitat types, map of habitats, endangered and rare habitat types, and on the measures for their preservation (Official Gazette 07/06). These measures are also part of the nature protection section of the general forest management plans which applies for all forests in Croatia. These measures are:  121: Management of forest according to the principles of forest certification  122: Where possible and appropriate, when performing final cut in an even-aged forest leave small patches of forest untouched  123: Preserve to a large extent forest clearings (pastures, meadows), as well as forest edges  124: Secure the prolongation of rotation period of the autochthonous tree species, bearing in mind the physiological age of respective species and health status of the forest ecosystems  125: Avoid usage of chemical agents and control agents for the plant protection; not to use genetically modified organisms  126: Preserve biological species significant for the respective habitat types; not to introduce alochtonous and genetically modified organisms  127: Secure a permanent percentage of mature, old and dry (both standing and on the ground) trees, especially those with cavities  128: Assure the appropriate preservation and monitoring of rare and endangered wild species  129: Where site conditions allows, perform aforestation and reforestation with “close-to- nature” methods and with autochthonous tree species and in a mixture which represents natural development. The aforestation of non-forest areas should be done only where it does not jeopardize rare or endangered non-forest habitat types

As the NEN represents the basis upon which the Natura 2000 is built, the management measures for forest habitats under NEN will probably represent the basis for designing the future management measures for forest habitats under Natura 2000. Building on the NEN, the SINP and its consultants made a draft national proposal of Natura 2000 sites covering 44.83% of the territory within the PHARE 2007-2008 follow up project “Institutional building and implementation of Natura 2000 in Croatia”. The 2010-2011 IPA project “Identification and setting-up of the marine part of Natura 2000 network in Croatia - Marine Natura 2000” suggested marine sites for the Natura 2000 network that were not covered by the PHARE project (SINP, 2013). These EU funded projects have increased the capacities of SINP whose employees at the national level increased from three to more than fifty over the course of a decade. The capacities of the county level nature protection authorities, which will be responsible for the Natura 2000 practical implementation, are now also being developed by the World Bank funded project loan “EU Natura 2000 Integration Project – NIP” lasting from 2011 to 2016. Hence, Natura 2000 served as an opportunity by which the state nature protection authority has multiplied its human, financial, and material resources (Croatian interviews). Although some environmental groups such as Green Action and WWF Croatia have contributed to Natura 2000 preparations via specific habitat and species mapping, domestic NGOs have generally lacked capacities to follow the whole policy process. Overall preparations for the implementation of Natura 2000 made by SINP was modeled after the Slovenian preparations for the Network, and SINP personnel had frequent contacts with the Institute of the Republic of Slovenia for Nature Conservation (Croatian interviews). All important national projects related to Natura 2000 are presented in Table 3.

Table 3. List of important national projects related to Natura 2000 TIME TITLE MAIN RESULTS PERIOD 2002- Emerald network pilot Identification of habitats and species per geographical 2003 project regions and six SPAs

2003- Building-up of National GIS and basic description of habitats and species; draft of 2005 Ecological Network NEN CRO-NEN 2005- 2nd Phase of the Emerald Detail identification of sites (404 sites, 43% of territory). 2006 Network implementation Final designation of NEN 2007- 3nd Phase of the Emerald Valorization of NEN in the Natura 2000 context, defining 2008 Network implementation of pSCIs, Transposition of basic elements of Natura 2000 in national legislation 2008- Institutional building and First draft of Natura 2000, two management plans for 2009 implementation of potential Natura 2000 sites

NATURA 2000 in Croatia 2010- Marine Natura 2000 Identification and setting-up of the marine part of Natura 2011 2000 network in Croatia 2011- CRO fauna and CRO Development of faunistic and speleological databases as 2012 speleo Part of Nature Protection Information System 2011- MAN-MON Six management plans for Natura 2000 sites 2013 2012- DCRO Habitats Development of Habitat Types Database as Part of 2014 Nature Protection Information System 2011- EU Natura 2000 Building capacity of nature protection administration, 2016 Integration Project monitoring of biological diversity, stakeholders` engagement in Natura 2000

Within the 2007-2008 PHARE Project SINP sought to involve state and non-state actors from agriculture, spatial planning, forestry, water management and science. Environmental NGOs representing civil society were relatively imperceptibly engaged. A strong approach to cross- sectoral coordination has occurred only in the relation of nature protection among the forestry actors. In this issue area SINP had formed an expert group which was mandated to design expert proposal of pSCI’s for forest habitats, and to design management guidelines for birds and other forest dependent species. The management measures for forest dependent bird species were scheduled to be adopted by an ordinance until the accession to the EU, whereas the management measures for other forest dependent species will be adopted by an ordinance after the Commission approves the final SCI list. The meetings of the expert working group lasted from March 2010 until October 2012, and its results were incorporated into SINP’s expert proposal on Natura 2000 areas. The issue of defining management measures for forest habitats was introduced at four meetings. In 2011 a proposal for management measures was jointly developed by the Faculty of Forestry, University of Zagreb and Croatian Forests Ltd (Janeš, 2011). These measures included:  121: Forest management must be ecologically responsible, useful to society and economically viable  122: In final felling larger than 100 ha leave a central part uncut, up to 5 ha of size  123: Forest management should preserve to a largest possible extent forest clearings, meadows and pastures that exist within the forested areas  124: On every 1000 ha of forests leave 5 ha specially dedicated to conservation of that habitat, where the rotation period will be set by the physiological age of the tree species present  125: Avoid chemical agents in forest protection. Use biological and biological-technical means. No usage of genetically-modified agents

 126: Preserve plant species important for the habitat type. No introduction of alohtonous species  127: In even-aged forests before the preparatory cut and in all uneven-aged forests leave 3-5 cavity habitat trees and 3-5 dead or decaying trees. These trees must not threaten the sustainability of the stand  128: Forest management plans should take special notice to rare and endangered plant species  129: Aforestation of bare forest soil should be done by autohtonous species by using methods that are close to nature. Do not aforestate bare forest land on areas where rare and endangered non-forest habitats are present

The issue of management guidelines for forest habitats was not concluded. Rather it was decided at the final meeting by SINP that the working group will reconvene after the bio-geographical seminar is completed for Croatia. The list of measures for bird and other species that are related to forest habitats and were agreed upon at the working group are presented in an abbreviated form in Table 4. All the presented measures are related to a specific list of SPAs and pSCIs.

Table 4. Management measures for birds and other species related to forest habitats (Source: working materials of the expert working group on Natura 2000 in Croatian forestry) Measure Species Birds Leave an adequate portion of stands older than 60 years for beech Ural Owl, Middle and older than 80 years for oak Spotted Woodpecker, In final felling larger than 100 ha leave a central part uncut, up to 5 Black Woodpecker, ha of size Grey-headed Forest stands older than 60 years (beech) and older than 80 years Woodpecker, Collared (oak) must have at least 10 m3/ha of deadwood. At tree marking Flycatcher, Red-breasted leave the cavity trees Flycatche, Boreal Owl, Leave as much as possible Prunus sp for breeding of Picidae bird European Honey family Buzzard Forest stands older than 60 years (beech) and older than 80 years Three-toed Woodpecker, (oak) must have at least 15 m3/ha of deadwood. At tree marking White-backed leave the cavity trees Woodpecker, Eurasian Pygmy Owl Secure quietness and perform monitoring from 01.01. - 01.03. within The White-tailed Eagle a 100 m radius around nests. If an active nest if found, secure (Haliaeetus albicilla) quietness and no forestry operations in a 100 m buffer from 01.01 till 30.06 Same as for the White-tailed Eagle but until 15.08 Lesser Spotted Eagle, Black Stork Manage according to national legislation and keep appropriate game Western Capercaillie populations

Preserve forest clearing on sites of breeding and rearing Secure quietness in 300m radius around breeding areas from 31.03 till 31.05

Secure quietness in 300m radius around breeding areas from 31.03. till 30.06 Manage according to national legislation and keep appropriate game Hazel Grouse populations Preserve forest clearing on sites of breeding and rearing Secure adequate portion of degraded forest stands (garrigues) European Nightjar Other species Secure at least 30% of trees with dbh ≥30 cm, especially cavity and Western Barbastelle, habitat trees Bechstein's bat Leave cavity and habitat trees when marking trees Preserve forest edges and clearings Secure adequate portion of older stands; ≥60 years for beech, ≥ 80 years for oak In final felling larger than 100 ha leave a central part uncut, up to 5 ha of size Secure natural habitats in 15m buffer around water courses Italian Agile Frog Preserve small water surfaces in forests Italian Agile Frog, Scarce Fritillary Gradually transform poplar cultures into natural stands Italian Agile Frog Preserve forest edges and clearings Jersey Tiger Moth, Fenton's Wood White, Scarce Fritillary Do not manage forest edges in spring and summer; mowing once a Fenton's Wood White, year Secure at least 3% of dead or decaying woody biomass Rosalia longicorn, Great Stag Beetle Secure at least 3% of dead or decaying woody biomass. In economic Morimus funereus, Great forests leave at least 50% of stumps Sag Beetle Leave an adequate portion of oak stands older than 80 years Great Capricorn Beetle Preserve forest water streams and their alder vegetation. Preserve Carabus variolosus continuous forest canopy in these areas Monitor their habitat trees and secure them from felling Hermit Beetle

There was a dispute regarding the management measures for the western capercaillie and hazel grouse. The opinion of the Croatian Academy of Sciences and Arts was that populations of other endangered species that might have negative influence on these bird species should not be actively managed, whereas the opinion of the Faculty of Forestry, University of Zagreb and of the Ministry of Agriculture was that other endangered species may be actively managed if they threaten the populations of those bird species. As both sides provided scientific data for their

39 claims, both opinions have entered the list of management measures. The management measures encompassing the wolf, bear and lynx are set by separate management plans.

Although, at the onset, group members had divergent policy core beliefs and normative standpoints, the decisions they made on Natura 2000 and forestry were based on compromise characterized with elements of policy learning (further addressed in the following chapter). The working groups` members coming from the nature protection sector have increased their awareness on the nature protection characteristics of forest management by learning on the principles of practical sustainable forest management, while the policy learning from the forestry side was less pronounced. The gradual acceptance of Natura 2000 in forestry accrued by continuous inputs on the formal implementation of Natura 2000 by representatives of SINP, but even more by their continuous re-assurance that the forestry is the most nature-protection inclined from all land-use sectors and that Natura 2000 will not have a devastating economic impact on the forestry practice. The general position of SINP was that in most cases for non- priority forest habitats compliance to the Principle 6 (Environmental impact) of the FSC system of forest management certification is adequate for reaching the favorable conservation status for these habitats. The working group has decreased the level of conflict between the forestry and nature protection sectors, and has also established cooperation in the forestry sector on joint public presentations between the members of SINP, Faculty of Forestry and the State Forest Management Company on Natura 2000 in forestry (source: Croatian interviews).

SINP issued an expert proposal of the list of Natura 2000 sites in December 2012 which spans onto 37% of land area and on 17% of national marine area. Presented by the Minister of Environment and SINP in April 2013, this new proposal has decreased from the 47% designated by NEN and the 45% designated by in the 2009 proposal.

Table 5. Coverage of Natura 2000 in proposal from 2009 and 2012 (Source: SINP, 2012) Land No. of Marine % of marine area, % of land sites area, km2 area km2 2009 SPA 22.101 38 39,05 10.097 32,50 pSCI 14.529 1.099 25,67 4.360 14,04 Natura total with 25.373 1.137 44,83 12.107 38,97 overlappings 2012 SPA 17.138 38 30,28 1.048 3,3 pSCI 16.203 756 28,63 4.948 15,64 Natura total with 20.897 793 36,92 5.249 16,60 overlappings

The majority of the decreased pSCIs fall into areas of economic development zones adjacent to larger cities (source: Croatian interviews). The important pSCIs that have been included in the 2012 expert proposal are: Limski zaljev – forest vegetation reserve; northern parts of the Drava basin; lowland forests at Bokčić lug, beech and pedunculate oak forests of Psunj; increased coverage of horse chestnut forests at Zrinska gora; Lisac – dry submediterranean grasslands; Islands of Cres and Krk with its halophytic and grassland habitats, Mountain Mosor and Trogir hinterland for its grasslands, caves and hazmophitic vegetation. It is of interest to note that the abovementioned forest areas have entered Natura 2000 because of its forest related species, and not because of the habitats itself. The biggest exemption to this is parts of the island of Hvar, which has been included due to its Pine and Holm Oak forests. However, all these changes have just marginally increased the pSCI areas. The biggest difference between the 2009 and 2012 proposals lies in the diminishing of SPA areas. With the exemption of the majority of the Lika plateau, almost all SPA decrease has occurred within the Croatian territorial sea area. The reason for diminishing SPAs it that subsequent research has shown that the respective bird species do not inhabit the previously designated areas (source: Croatian interviews).

Figure 9. Natura 2000 proposal from 2009 and 2012 (Source: SINP, 2012)

Figure 10. pSCIs for forest habitats as agreed at the expert working group in 2012 (Source: SINP, 2013)

Figure 10 shows the pSCIs chosen for the protection of forest habitats that were agreed upon by the working group at the meeting before the last one, held on March the 9th 2012. The expert proposal made by SINP in November 2012 diverges from what was agreed upon by the working group, as some new areas were added which were not initially included. The most important additions are: Zrinska Gora, parts of the island of Hvar, Ogulin area, Sunja field, Gorski Kotar and Northern Lika. Gorski Kotar and Norther Lika are sites larger than all of the others combined, and are dominated by un-even aged forests of beech and spruce. It these sites, the only forest habitat that is protected is the (Sub-) Mediterranean pine forests with endemic black pines (9530*), a habitat type very rare in that site. All the other newly chosen pSCIs for forest habitat are chosen because of their dominant habitat types. This represents a significant raise of forest habitat pSCIs from what was agreed upon at the working group. This increase was made possible by an agreement between SINP, Croatian forests and the Faculty of Forestry, whose high-ranking members have formed an “inner” working group which had meetings on ad-hoc basis. The reasons for this “inner” group was a high level of technical details that needed to be addressed at several points, and in some cases, was coping with the long time lapse between the meetings of the working group (source: Croatian interviews). Nonetheless, representatives of the forestry sector have expressed their dissatisfaction with these inclusions, as “Whole Zrinska Gora and some other areas have been taken away from us” (source: Croatian interviews). The preparation of the Natura 2000 Ordinance is now done through a committee, comprised of state authorities responsible for nature protection, forestry, water management, energy and development. At the same time there is a Parliamentary discussion on a new Law on Nature protection whose final draft would put much emphasis on Natura 2000 impact assessment and

42 management rules. The coverage of Natura 2000 network is an important policy issue in both inter-agency and Parliamentary discussions (source: Croatian interviews). Since thus far, the inter-agency committee has not produced a final version of the Ordinance, the Croatian Government has failed to meet its obligation to submit to the Commission a national pSCI list by the date of EU accession. The final Natura 2000 proposal is however unlikely to significantly diverge from the 2012 expert proposal which the Ministry of Environmental and Nature Protection had presented in April 2013 (source: Croatian interviews). The nature protection administration has used the approaching EU accession date to put pressure on the Government and the Parliament to adopt the final Natura 2000 proposal before opposition of development and land use interest groups has fully emerged (source: Croatian interviews).

5.3.2. Practical compliance, 2002-2013

Consistent with the impact assessments rules provided in Article 6 of the Habitats directive, habitats and species protection within the NEN should be guaranteed by environmental impact assessment of development or land use plans, programs, and interventions. Yet, the pitfall of NEN has been the practical implementation. Impact assessments very rarely stop development projects (FoE-CR, 2011) since 90% of all impact assessments have concluded that there was no significant negative impact on biodiversity (MNP, 2013). Private consultancies have frequently made speculative conclusions in their assessment reports favoring investors and there is little control over project implementation (Kartus, 2012). In addition, nature and national parks, in which most of Natura 2000 areas are to be designated, do not have binding management plans which provides an opportunity for economic interest groups to run their land-use businesses without fearing infringement proceedings (Lovric et al., 2011).

Currently pronounced conflicts over Natura 2000 area designation and management have evolved in areas where large infrastructural investments in the energy sector and river corrections in water management (Hina, 2012) met with opposition from both the state nature protection administration (Biocina, 2012) and few environmental NGOs. Domestic environmental groups have recently learned to cooperate with their transnational civil society partners to turn directly to EU institutions and to jointly put pressure on domestic authorities and land-users. For example, NGOs pressures targeted at the European Bank for Reconstruction and Development (EBRD) and the Commission were successful in the case of the Ombla hydro- power plant. Civil society’ protests and arguments based on technical knowledge made not only the EBRD, state energy and water authorities to reconsider the investment (Hina, 2013), but also the Commission to question in general the Natura 2000 relevant impact assessments of land-use

43 projects in Croatia (Soldo, 2013).In the 2011-2013 period MANMON (Natura 2000 Management and Monitoring) SINP has made six pilot Natura 2000 management plans, two of which encompass forest habitats. The Management plans were made in cooperation with local stakeholders and scientists, and the management measures for habitats and species that were designated within these two pilot management plans are very similar to the management measures that were agreed upon by the working group (source: Croatian interviews).

Despite the extensive stakeholder consultations, other land-user groups have expressed great discontent with the designation procedures. State and non-state actors from agriculture, energy, water and spatial planning sectors were only informed and consulted, but not empowered with decision-making (source: Croatian interviews). As anticipated by nature protection authorities, the land-user groups as regulatory targets, along with local citizens, demonstrated strong resistance towards the implementation of the network. They questioned the financial viability and believed in the possibility of substantial negative impacts on their economic welfare (SINP, 2012). Perceiving improper stakeholder engagement and little coordination, most of the land-use sectors have put substantial informal pressure to incorporate their economic interests into the Natura 2000 proposal. The Croatian Chamber of Civil Engineers stands at the forefront of the land users’ pressure group (CCCE, 2013).

The power of domestic civil society actors is likely to increase in the future as environmental NGOs, coordinated through Green Forum, are preparing a shadow list of Natura 2000 areas to be directly submitted to the Commission. These activities are coupled by capacity building, i.e., training to monitor practical application and to influence national policy-making, which are supported by transnational NGOs such as the CEE web, a network of non-governmental organizations for biodiversity conservation in Central and Eastern Europe. Members of the Green Forum have received training for the preparation of a shadow list and for participation in the bio-geographical seminars. Both the Green Forum and the State administration have accepted as a normal status quo their separate preparations of proposals of the pSCIs and SPAs (source: Croatian interviews).

The central Government has positioned itself as the sole decision-maker regarding the implementation of the network, as the choice of the sites will be set by a by-law for which public consultation begun only a couple of months before EU accession, blocking the influence of the Parliament and pressures from the land-use interest groups (source: Croatian interviews).

Substantial conflicts between the nature protection authorities and land-user groups are hence likely to increase in the near future once the Natura 2000 Ordinance is formally adopted. The final draft version of the new Law on nature protection also empowers the central Government to make final decision to set up the Natura 2000 management without the input from the county

44 level administrations. This fact is also likely to strongly impede the future implementation of Natura 2000, as the latter may not endorse the central government’s policy on putting the financial burden of the Natura 2000 management onto the scarce local budgets. Such is the reaction due to the approaching elections and the expiration of capacity building projects funded by the international donors.

6. Discussion

The basic strategy of the EU for the implementation of the acquis in “weak” transition countries is to use the resources of non-state actors (companies and civil society) which have been empowered during the process. Another reason for empowering non-state actors is that governmental capacities were already stretched out in the transition process, and the participation of non-state actors is an explicit requirement of the EU for the implementation of acquis, even in the Birds and the Habitats directives. There were also many pre-accession programs (PHARE, SAPARD, IPARD, ISPA, IPA), that provided a venue for the transfer of EU money and expertise needed for the inclusion of non-state actors. The NGOs generally did not have enough capacity to utilize EU funding sources and have achieved generally low level of participation, which can be attributed to their antagonistic political culture of being included in formal policy formulation processes. Another reason was that NGOs have also shielded themselves from public skepticism by refraining from participation to policy formulation, which is often considered as an activity that supports the continuation of traditional clientelistic networks, and so they rather remained EU`s “watchdogs” (Börzel, 2009). This is in line with the findings of Fairbass and Jordan (2001), by which the strengthening of environmental groups in the implementation of the Directives is more an unintended consequence of the EU integration than it is a matter of their agency.

The increasing complexity of multi-level EU governance had a strong impact on the implementation of Natura 2000 in Eastern EU member countries, where this complexity hindered the competences of the central state and its hierarchical relations to the other national actors. This resulted in inefficient institutional designs and over-exploitation of natural resources (Kluvánková-Oravská et al, 2009). Literal transposition of EU biodiversity rules into national laws was possible through empowerment of central environmental authorities and private actors based on the acquis conditionality set by the EC and capacity building projects funded by the EU. Key veto players lacked negotiating power due to the high time pressure, and the scientists and NGOs seized the opportunity and inventoried the national territory “under the radar” of formal political system, thus escaping any great controversy.

The expert proposal became increasingly “politicized” with its public presentation in April 2013, and pressure from land user-groups might be the reason for the delay of the submission of the official proposal (as was the case in Hungary and Bulgaria). During such “polarization” phase the relationship between the governmental authorities and the NGOs is likely to deteriorate, as they will circumvent the national authorities and coerce compliance to EU policies through shadow lists and threats of infringement procedures. Both the state administration and research organizations find NGOs lacking the capacity to engage in a mutual science-driven discussion on designation of Natura 2000 sites. On the other hand, the NGOs have accepted this relation as a permanent status quo and that the only way in which they can influence the designation process is through shadow lists and direct contact with the Commission.

While “supra-nationalization” strategies are also known for the older EU member states, there are also significant differences: First, many studies have pointed to close ties between national environmental NGOs and the respective environmental protection agencies (Fairbrass and Jordan, 2001, Weber and Christophersen, 2002), which is not the case in Croatia. The high share of territory that is being designated as protected area under Natura 2000 is another difference when compared with most of the other European countries. The Croatian case demonstrates that in the specific situation of the EU accession process, as was the case with other SEE governments, it was less able to ‘defend’ their territories against an EU protection status compared to the Western European governments (McCauley, 2008).

The high degree of the Croatian formal compliance as policy output is likely to occur given the highest share of pre-designated territory, supportive EU and domestic formal institutions and approaching membership. Alternative explanation of the high share of Natura 2000 could also be the inherent objective of the nature protection administration to expand their domain and take additional activities (Pfeffer and Salacnik, 2003; p.272), just as the French Ministry of Agriculture has seen their national implementation of Natura 2000 (Alphandéry and Fortier, 2001).

The management measures for species dependent on forest habitats that are set by SINP`s expert proposal are very similar to the ones set in Slovenia, and they represent a list of thoroughly defined restrictions from what has been forestry practice so far. However, the first impediment in their implementation is monitoring, for which the nature protection administration does not have adequate capacity, and the forestry administration is not assigned with this task. With the passing of pressure from the EU accession conditionality, as was the case in Slovenia, it will be difficult to insure the practical implementation of these measures. The management measures for forest habitats that were proposed by the members of the forestry sector have not been adopted; they do not represent a significant change from what is prescribed already by the national forestry legislation and the FSC system of certification of forest management that is held by the state

46 forest management company. The measures set in Slovenia are more bounding, and as some of SINP`s proposal for management measures (such as exclusion of active forest management from a given site) were not approved by the majority of members of the forestry`s expert group, it was a rational action of SINP to perform an act of non-decision making (Bachrach and Baratz, 1962) and to leave this issue to be resolved after the bio-geographical seminar for Croatia. This would also enable them to partially define these measures through designing site-specific Natura 2000 management plans. Such plans would be in actuality processes over which SINP and the nature protection experts would hold more discretionary rights than it was the case of the working group.

From the perspective of its stakeholders, the legal framework of NEN is well designed and renowned but there are great doubts on its implementation. The major difficulties in its implementation are recognized to be “general lack of knowledge, lack of communication between stakeholders, insufficient information and guidelines for implementing institution, and the overall perception of nature protection as a limitation to someone`s rights, development, etc.” SINP, 2008. Although Natura 2000, as a successor of NEN, is protected under European and national law, the authorization of economic development projects, lacking or sufficient environmental impact assessments, as well as symbolic administrative sanctions will probably lead to practical non-compliance. It also has to be noted that no matter how much supportive the institutional structure is, the enforcement of any nature protection related land-use policy is hard to secure on almost a half on the national territory.

And in accordance with the cases from other countries, a shift from a conservation science based hierarchical ‘top-down’ approach in the early phase of designation of candidate protected areas towards a more flexible approach that highlights stakeholder participation and is aimed for at least symbolic integration of land-users and local communities is expected. These observations are in line with the observations of Sedelmeier (2006), who also states that the new EU members comply with formal rules much better than most of the older member states. The findings from the Natura 2000 implementations show that the central governments rationally act in accordance to the opposed forces. State authorities complied with normative requirements of formal transposition of nature protection acts and have designated large parts of their territories under protection regimes. When faced with the opposition of economic interest, the central government has pacified their resistance by lax enforcement of the protection regime. Similar development is foreseeable with the implementation of Natura 2000 in Croatia, and is in line with the observations of Falkner and Treib (2006) that full transposition does not guarantee effective practical implementation on the ground.

In the domain of formal compliance the central government had transformed its nature protection policy. However, the Europeanization has not triggered the change in informal institutions and

47 behavior of domestic actors. This will have a profound effect on the practical implementation of Natura 2000 which will most likely be kept on the level of accommodation. This is in line with the previous observation describing a similar decoupling of formal compliance and practical non- compliance (“deception gap”) in the Europeanization of environmental policy in CEE in general (Jacoby, 1999).

Future research will be needed to explore in how far the gap between formal policies and institutions, and rule-inconsistent behavior of regulatory targets and authorities will narrow or even close over time. And future governance developments will demonstrate how far social learning and gradual adjustments, in the shadow of moral and regulatory pressure by the EU and domestic NGOs, will eventually lead to durable changes in biodiversity policy in Croatia subsequently, a question arises - how effectively will it conserve its rich natural heritage? Until then, the transformative power of Europe alone will not secure the Croatian biodiversity.

The most important segment of the implementation of Natura 2000 in Croatian forestry was the output of the working group on Natura 2000 in forestry, which had defined the protection areas for forest habitats and forest dependent species, and had defined management guidelines for forest dependent species. It was briefly mentioned in this chapter that these decisions were made through a mixture of policy learning, compromise and usage of scientific argumentation. Understanding interplay between these factors is important for future steps of the implementation process; management guidelines based on policy learning would be more in-line with the forestry practices and would be more accepted by the nature protection than those based on compromise. In addition, designation of protection areas based on science would be more accepted at the bio-geographical seminars than a protection proposal based on policy learning or compromise. The interplay of policy learning, compromise and usage of science by the working group is thoroughly analyzed in the following chapter.

CHAPTER III NORMATIVE, RATIONAL AND COMMUNICATIVE PERSPECTIVE ON THE WORKING GROUP ON NATURA 2000

1. Summary

With the accession to the European Union Croatia must joint its ecological network, the Natura 2000. This network is based on the Birds and the Habitats directive, for which the national designation of protection areas should be based on scientific criteria. Review of these processes in different countries shows that many factors have affected it, such as capacities of the nature protection administration, strength of different interest groups and the general capacity of a nations to resist supra-national influences.

The research follows the activities of the expert working group which has prepared the forestry section of the Ordinance on Natura 2000, the basic legislative act by which the network is formally implemented. Activities of the working group are analyzed through three different theoretical frameworks: the “normative approach” which focuses on the role of policy beliefs, the “rational approach” which focuses on the role of interests, and the “communicative approach”, which focuses on the role of science and the characteristics of communication between its members. The analysis is performed through content analysis of interviews with the members of the working group, all of whom have been interviewed on two occasions. Following the three theoretical approaches 28 hypotheses were constructed, upon which a deductive falsification procedure was applied.

The results mostly show adherence to the normative approach, according to which the policy core beliefs have created a division in the working group between the members of the nature protection sector and the members of the forestry sector. Policy learning has occurred only on secondary issues and mostly within the nature protection sector, while the most important decisions were reached through compromise. Practical participation in decision making was done by senior members of the working group who have strategically used information coming from their field of expertise. All of the scientific argumentation that was used is traced back to the concepts of conservation biology and sustainable forest management. Adherence to these concepts has systematically distorted communication within the working group, which was characterized by a lack of a joint understanding of what constitutes the appropriate scientific information for the transposition of Natura 2000 in Croatian forestry.

2. Introduction

Chapter II has reviewed the legislative basis of EU nature protection policy and its transfer to national policy domains. It was seen that the national implementations of this policy have been very diverse, and that important factors which set the course of this process were power relations among national stakeholders and their beliefs, the capacity of non-governmental organizations and the general national capacities to resist supra-national influence of the EU. The forestry part of the Croatian Natura 2000 policy is based on the decisions of the expert working group on forestry. Their decisions were formulated through communication between representatives of many stake-holding groups. Given the formal adherence of Natura 2000 to scientific criteria and the importance of interests and beliefs in its implementation, the following question emerges: What kinds of discourses have shaped the formulation of Natura 2000 forest policy in Croatia?

An overview of Chapter III is provided in Figure 11.

CHAPTER III INTRODUCTION Expert working group on forestry CONCEPTUAL BASIS Advocacy coalition framework, Rational choice theory, Theory of communicative action METHODOLOGICAL APPROACH Core assumptions → auxiliary assumptions → hypotheses

RESULTS Hypotheses testing

DISCUSSION Domian of validity of each theoretical approach

CHAPTER IV Role of, power and influence in the forestry working group on Natura 2000

Figure 11. Overview of Chapter III

The process of the preparation of the forestry part by the expert proposal of the Ordinance on Natura 2000 is analyzed through three different theoretical frameworks: (1) the belief-system based on the normative action(s) of stakeholders, (2) the rational interest-based action of the members of the working group and (3) the role of the scientific discourse. The belief-system normative perspective to policy formulation is based on the Advocacy-coalition framework (Sabatier and Jenkins-Smith, 1993; 1994). The rational interest-based perspective is based on the sociological Rational choice theory (Coleman, 1990). The role of science is viewed from the

Habermasian perspective on discourse rooted in communicative action (Habermans, 1984), based on scientific argumentation (Latour and Woolgar, 1986), while accepting the “real life” limitations of the policy formulation process (Lindblom, 1959). As discourse is a “sub-set” of the communicative action, other forms of social actions from The Theory of Communicative Action follow its corresponding theoretical perspectives; the strategic action follows the rational choice theory-based perspective, and the normatively regulated action follows the perspective of Advocacy coalition framework. From the rational choice perspective strategic action of scientific argumentation follows the perspective of sociology of knowledge on science (Marcuse, 1964; Zeltin 1968), which views science as an integral part of the societal debate with its vested interests (Gieryn 1983). These three approaches are not intertwined; rather they represent three alternative views on the activities of the working group. Their domain of validity is explored by testing a series of hypotheses that are defined for each approach; subsequently, all of the hypotheses are tested against contradictory hypotheses from alternative theoretical approaches. The discussion chapter provides insight to what parts of the activities of the working group can be explained by each of the theoretical approaches. The discussion is expanded by the “narrative coding” (Saldana, 2009), where the validity domain of each of the theoretical approaches is represented through a “story” constructed from a series of quotations by the members of the working group. The goal of the chapter is to find out how different rationales drove the formulation of the decisions of the working group. As the chosen methodology focuses on testing a series of hypotheses, the chapter does not provide detail accounts on what actually occurred in the meetings of the working group. Analysis is performed on the data obtained from the interviews with the members of the working group at two time intervals, from the interviews conducted with the key informants and from the analysis of the document. The research design follows the characteristics of what Bitektine (2008) calls a prospective case study, where several rival theoretical explanations are deductively analyzed on a same case, which utilizes a combination of pattern matching (Yin, 2003) and the alternate templates strategy (Langley 1999). Hypotheses coding (Bernard, 2006, Saldaña, 2009) and longitudinal coding (Giele and Elder, 1998 Saldaña, 2003, 2008) are applied, with subsequent usage of descriptive and multivariate analysis. The purpose of this research is to explain how the decisions of the working group were reached and which factors have influenced these decisions. The original contribution of this research to the body of knowledge is the comparison between different theoretical frameworks in the explanation of decision making related to Natura 2000 directives, as most of the other research (with the exemption of Glück, 2000a) has focused on usage of either Advocacy coalition framework (Sarvašova et al, 2012; Weber and Christophersen 2002; Cent et al, 2011), or on the rational choice approach (Alphandery and Fortier 2001; Papageorgiou and Vogiatzakis, 2006; Moscari, 2004). There has been no recorded research from the position of social sciences that has focused on exactly how scientific data was used to transpose the Natura 2000 directives. In addition, the research presented in this thesis embodies the first usage of the Theory of communicative action on the topic of Natura 2000.

3. Conceptual basis

3.1. Advocacy coalition framework

The Advocacy Coalition Framework (ACF) was developed as a response to the previously dominant stages heuristic (Jones, 1977) approach which breaks the policy process into functionally and temporary distinctive elements. Jenkins-Smith and Sabatier (1994) claimed that stages heuristic is not really a causal model, that it does not provide a clear basis for empirical hypothesis-testing, that it is often descriptively inaccurate and that it emphasizes the ‘top-down’ approach. ACF tried to unify the “top-down” and bottom-up” approaches (Sabatier, I986, Sabatier, I988; Jenkins-Smith, I988; Sabatier and Jenkins-Smith, 1993) and its basic premises (Jenkins-Smith and Sabatier, 1994) are that:

 Policy change requires a historical perspective that covers at least a decade  Policy change is best observed within a policy sub-system, i.e. in the interaction of stakeholders who follow and try to influence governmental decisions of a policy area  Sub-systems must include inter-governmental relations  Public policies can be conceptualized as belief systems, i.e. a set of values and assumptions on how to realize them

ACF also assumes that actors group themselves in advocacy coalitions based on a set of normative and causal beliefs. These beliefs are categorized on a three point scale. The overarching categories are the “deep core” beliefs that include basic ontological and normative beliefs, such as relative value of social equality, individual freedoms, or the left/right scale in politics. These deep core beliefs permeate all policy domains or sub-systems. On the lower scale are the “policy core” beliefs which relate to basic normative commitments and causal perceptions for a policy sub-system, such as anthropocentric / ecocentirc view on nature, salience of a given issue, its principal causes and strategies for realizing core values. On the lowest level of the scale are the secondary aspects of a coalition`s belief system, which comprise of a broad group of narrower beliefs within a specific policy domain, such as budgetary allocation or evaluation of an actor`s performance. One should note that deep core beliefs are resistant to change, while policy core beliefs are difficult to modify, and their change over time requires gradual accumulation of evidence. Moreover, policy core beliefs can be altered in case of strong external perturbation of the policy sub-system, such as change in general socio-economic conditions, or policy outputs from arising from another policy sub-system. Secondary aspects of policy beliefs are more open to changes with the input of new data, experience or change in strategy.

Each coalition has a strategy (through usage of budgets, personnel or information) by which they try to influence a government to change their policy/policies to be more in line with their policy

52 beliefs. Since each coalition has its own strategy that “pulls” the government into a different direction, a new kind of actor emerges – policy broker – whose task is to reduce the conflict and find a more reasonable compromise. This framework also models policy oriented learning (Heclo, 1974), which is a long-term alteration of beliefs and/or behavior that is caused by experience and leads to change in policy objectives. It requires the feedback-loops (Figure 12), where actors with increased perceptions of exogenous variables conduct policy-related activities, and with increased experiences from such activities they reiterate the feedback-relation. The framework also assumes that such learning process is instrumental, i.e. that it is caused by a desire to further their policy objectives, where information contradicting policy core beliefs is discarded, and policy analysis is used to either elaborate their policy beliefs, or to attack the opposing policy beliefs. The perception of the members of one coalition towards the members of another coalition might be distorted, as they may see them as more “malicious” and “powerful” than they actually are – this is called the “devil shift” (Sabatier et al., 1987).

ACF was later on modified (Sabatier and Weible, 2007) to expand its application to corporatist regimes, where two variables important for long-term opportunity structures (Kriesi et al, 1995) have been included: degree of consensus needed for major policy change and the openness of a political system. The same paper added two new paths to policy change (to the external sub- system events and policy oriented learning) to policy change: the internal sub-system events mark expectation of failure in current practices and negotiated agreements. Negotiated agreement builds on previous work on cross-coalition learning (Jenkins-Smith, 1990), where “professional forums” provide institutional setting for negotiating, agreeing and implementing these agreements. Sabatier and Weible (2007) have identified nine elements that increase the likelihood of such an agreements: a hurting stalemate (a situation when neither party can win in a conflict without excessive loss), effective leadership, consensus based decision rules, diverse funding, duration of process and commitment of members, a focus on empirical issues, an emphasis on building trust, and lack of alternative venues. An overview of the theory is presented by Figure 12 - on the left side are two sets of exogenous variables, one stabile and one more dynamic which influence the policy process.

Figure 12. Advocacy coalition framework flow diagram (Source: Weible and Sabatier, 2009)

The applications of ACF also showed that causality between external perturbations and changes in policy subsystem is difficult to grasp (Ameringer, 2002; Burnett and Davis, 2002; Carvalho, 2001; Davis and Davis, 1988), but it also shows that its expectations of the role of science in policy are supported (Eberg, 1997; Leschine, et al., 2003; Litfin, 2000; Nicholson-Crotty, 2005; Sato, 1999), where science is used to strengthen pre-existing policy belies and to legitimize arguments against their opponents. Coalitions tend to be stable over time (Jenkins-Smith and St. Clair, 1993; Zafonte & Sabatier, 2004), but some more extreme members may leave them in order to disrupt a possibility of a compromising outcome (Munro, 1993). The policy oriented learning actors belief systems has received mixed support, as it may occur if the issue covers secondary policy beliefs of both coalitions (Larsen et al., 2006), when the conflict is not very strong (Meijerink, 2005), or when professional forums are available (Brown and Stewart, 1993; Olson et al, 1999). However, a professional policy forum might not be enough for policy learning (Sabatier and Jenkins-Smith, 1999), and high level of conflict might hinder its effectiveness (Litfin, 2000).

Review of 80 applications of the ACF (Weible et al, 2009) showed that ACF was most frequently applied in the environment/energy sectors followed by economic and health related issues. In terms of geographical scope, the vast majority of applications occurred in the United States of America and in Europe. However, in most of its applications researchers have not specified the methods of data collection, nor have they tested its formal hypotheses. It should also be noted that more than 75 percent of applications have largely overlooked large portions of the theory, such as the devil shift, hurting stalemate and policy brokerages; sadly, a large portion

54 of applications of ACF have re-introduced stages heuristic by using linear depiction of political behavior and policy change – and interestingly enough, ACF was designed to avoid biases of such an explanation.

ACF has also been frequently applied in forestry. One of the first applications was by Davis and Davis (1988) when they modeled the changes in public land policies of the 1980s where they found it appropriate to explain ever increasing complexities of the policy sub-system. Hysing and Olsson (2008) have used it to elaborate the change in the Swedish forestry policy sub-system, but found the framework lacking in factors centered on forming of coalitions such as resource interdependence. Moreover, the concept of policy broker is too vague for analytical purposes, and the framework leaves out contextual arrangements in favor of “abstract theorizing”. Burnett and Davis (2002) have tested its first five formal hypotheses to show how the environmental coalition had strategically used new scientific information to advance their position, which resulted with a ban on clear-cutting in the Pacific Northwest of the USA. Elliot and Schlaepfer (2001) have also tested its formal hypotheses in order to explain developments of forest certification, where the key argument was that the developments of forest certification moves very swiftly through the process of policy learning. This paper has received severe criticism by Cashore (2003). He argued that Elliot and Schlaepfer have not properly conceptualized policy change, or its fast/slow change, that they have not properly identified the advocacy coalitions, have not established causal link between the behavior of coalitions and individual companies, and most importantly, that they may have used ACF as a theoretical explanation for providing legitimacy to private forest certification schemes; which is exactly how ACF describes the instrumental usage of new (scientific) information. Lertzman et al. (1996) used ACF to follow the changes in the Province of British Columbia, Canada forest policy sector and they found that a policy change can be facilitated by legitimizing the constraining behavior of the dominant coalition, and also the fact that ambiguity in scientific findings can be used by policy brokers to split up coalitions by targeting local-specific constituent interests. Nevertheless, this paper was deeply criticized by Hoberg (1996) who found the explanations in British Columbia forest policy sector lacking of alternative explanations, that the key concepts of the ACF were not properly specified, namely as policy learning, advocacy coalition and policy change, and that causal links between them were very vague.

Glück (2000a) looked at the changes in the European forestry sector since the 1960s onwards and its relation to biological diversity, where the dynamics of the forestry and the “environmentalists’ “camps” are seen through three theoretical perspectives: Rational choice theory, common-property regimes and advocacy coalition framework. Following this line of thought Hogl (2000) looked at the impact of these international changes on Austrian forest policy sub-system related to the dispute on forest certification, and found that the strengthening of the EU policy arena has brought new challenges to the national forestry community and weakened its national administration, which may reduce the influence of private interest groups. Sabatier (Sabatier et al, 1995) has also worked on the forestry sector by analyzing planning decisions of

55 the U.S. Forest service over a 30 year period, and found that the pressures for the status quo and the activities of the “amenity coalition” (mostly environmentalist groups) were a more important factor than the U.S. Forest service itself (which belonged to the “scientific management” coalition). The strength of the environmental groups was also pronounced in Weber and Christophersen`s (2002) study on the formulation of the EU Natura 2000 policy, where environmental groups gathered in the European Habitat Forum and formed a coalition with DG Environment, which was in opposition with the coalition of DG Agriculture and the land-user groups, gathered in the Forum Natura 2000. Developments of this issue have been thoroughly addressed in the previous chapter of this manuscript.

Following the previously mentioned review of ACF`s applications (Weible et al., 2009; p.134- 135), its authors state that although the hypotheses tend to be confirmed, questions remain about the composition and detection of the coalition members, the causal mechanisms linking external events and policy change, and the conditions fostering cross-coalition learning. Continuing or emerging areas deserving theoretical and empirical attention include the role of institutions and resource dependence in the framework, sub-system interdependencies, and coordination within, and between, coalitions”. The majority of its critique focuses on its lack of setting aside many important factors, such as collective action, political resources and institutional factors (Schlager, 1995; Schlager and Blomquist, 1996; Nohrstedt, 2005). Summarizing its critique, it can be stated that “…many of the ACF propositions about the fine causal links and mechanisms leading to policy change are still rather dubious, unclear or remain unexplored.” (Sotirov and Memmler, 2012).

3.2. Rational choice

Rational choice approach has its long roots in political science and economics (Marshall, 1997; Marx, 1993; Wright, 1978). Although it was generally marginal to sociology (Hechter and Kanazawa, 1997) it is getting more prominent in contemporary sociology (Wittek et al., 2013; Heckatorn, 2005; Lindenberg, 2000; Tilly, 1997). This change can to a great extent be attributed to the work of James S. Coleman (1986; 1989; 1993). He was the founder of the journal Rationality and Society in 1989, which is devoted to publishing work from the perspective of Rational choice theory. In addition, he wrote a very influential book Foundations of Social Theory (Coleman, 1990), which is written from the point of Rational choice theory; and he was also the president of the American Sociological Association from 1992 until his death in 1995.

Rational choice operates from the position of methodological individualism, and uses its micro- level explanations to macro-level phenomena. Given its narrow focus, Rational choice can also be defined by what it does not include, and that is “…work that is methodologically holistic, floating at the system level without recourse to the actors whose actions generate system... the

56 view of action as purely expressive, the view of action as irrational, and also the view of action as something wholly caused by outside forces without the intermediation of intention of purpose. It excludes the empirical work widely carried out in the social science field in which individual behavior is “explained by certain factors or determinants without any model of action whatsoever” (Coleman, 1989, p.6).

Coleman (1990, p. 13 - 14) sees individuals acting intentionally toward a goal, which is shaped by their values or preferences, and that the action maximizes their utility. An Important segment of the Rational choice theory encompasses the resources, which are things that actors control and in which they have some interests. With these two elements in mind, a minimal social system is defined as “… two actors, each having control over resources of interest to the other. It is in each one`s interest in resources under the other`s control that leads the two, as purposive actors, to engage in actions that involve each other…a system of action… It is this structure, together with the fact that the actors are purposive, each having the goal of maximizing the realization of interests, that gives the interdependence, or systemic character, to their actions” (Coleman, 1990, p.29). Coleman sees Rational choice as a grand theory, where “…success of a social theory based on rationality lies in successfully diminishing the domain of social activity that cannot be accounted for by the theory” (Coleman, 1990, p.18).

Given the fact that Rational choice puts emphasis on the micro-macro relation, the issue of macro-macro relations is “solved” by defining collective action. Usually transferring the authority and rights possessed by one individual to other(s), thus creating an independent collective unit, where an individual may act to fulfill interests of another individual or the collective that they form (Coleman, 1990, p.145). In this manner, collective action is seen as rational actions of individuals where one actor unilaterally transfers her/his control over actions to another individual (Coleman, 1990, p. 198). Individual maximization of utility usually includes harmonizing control among multiple actors, and this may lead to equilibrium within a society. Nevertheless, given the fact that transfer of control is unilateral, maximizing individual utility may not produce equilibrium outcomes. This is the rationale by which the instability in collective action is explained. Coleman (1990, p.292) was also interested in the process of norm formation, where he sees it as emerging and maintained by individuals who have benefit from them. In this manner an individual relinquishes part of control over their behavior in order to gain partial control over the behavior of others. According to Coleman, a key social change of modernity was a shift from primordial social structures such as family, religion groups and neighborhoods, to purposive structures, such as economic organizations and governments. This gives rise to corporate actor (Clark, 1996), where “…a large fraction of right and resources, and therefore sovereignty, may reside in corporate actors” (Coleman, 1990, p.531). Within a corporate structure such as a formal organization individuals may pursue their own goals which may diverge from the goals of the corporate actor, and corporate interests may go against the interests of an individual. This issue can be solved “…only by starting conceptually from a point where all sovereignty rests with individual person it is possible to see just how well their ultimate

57 interests are realized by any social system. The postulate that individual persons are sovereign provides a way in which sociologists may evaluate the functioning of social systems” (Coleman, 1990. p.531-532).

The basic misconception of the Rational choice theory is that individual behavior is explained through rational judgment. This causality is deeply set within the decision theory, while Rational choice theory is more concerned with social outcomes, i.e. given the individual rationality, will the aggregate outcome be “rational” or desirable? Individual and social outcomes may be very different, as social outcomes can have unintended and/or negative connotations. A good example of the latter is Hardin`s (1994) tragedy of the commons. Rational choice places equal weight to individual values and social constraints, but in empirical applications greater emphasis is typically placed on social structural determinants. Moreover, the model of action is set on individual level, based on subjective-expected utility theory (Hechter and Kanazawa, 1997).

Rational choice theories can be better described as a family of theories where one basic division is on “thin” and “thick” models, and where “thin” models say nothing on the actors` motivations, and “thick” specify them ex-ante (Ritzer, 2008). Thin models do not set the values of individuals; emphasis is on base causality on a limited number of strong assumptions. Thick models specify individual`s values and beliefs. Usually it implies that individuals seek to maximize quantities of certain exchangeable private goods such as wealth or prestige, or to maximize some non-exchangeable goods, such as enjoying classical music (Ferejohn, 1991). Accordingly, some applications of the theory specify common values that individuals pursue (Frank, 1985; Jasso,1990), while others model the process that might start the formation of these values (Becker, 1996). When scaled up to a certain social level, these idiosyncratic values tend to cancel each other out, so although individual behavior is unpredictable, Rational choice can make behavioral predictions on an aggregate level (Hechter, 1994).

However, thin ex-post models are tautological as they can be modified to interpret almost any kind of behavior, and thick models that are based on utility maximization without taking into consideration idiosyncratic values are often simply incorrect (Hechter and Kanazawa, 1997). An additional problem for Rational choice is that it is more focused on complex formal models of behavior than it is on its empirical testing; and there is no merit in judging a partly untested theory (Green and Shapiro, 1994).

Vast majority of applications of Rational choice theory in organizational research comes from the field of economics, but there are some contributions from sociology. To name a few, Petersen (1992) has analyzed differences between earnings of salespersons who have output-related salary models and those who do not; Hedström (1994) has looked at spatial diffusion of labor unions in Sweden from 1890 to 1940 (in combination with network analysis); Greve (1994) analyzed job mobility in terms of organizational diversity and Gambetta (1993) analyzed Sicilian Mafia as an organization which, in order to bring legitimacy to its services, first has to convince their potential “customers” in the “quality” of what they are “offering”. In a review of popularity and

58 trends in theory usage (Arts, 2012), the policy analysis based on Rational choice is the second most frequently used (after institutional) theoretical perspective, and from the year 2005 onwards it is becoming even more frequently used. Oyono et al (2005) have used RC to provide understanding on how the “forestry elite” in Cameroon has contributed to the inequality of access to forest resources, and where local communities, which have been marginalized, might have their situation improved by the decentralization process. Similar issue is taken up by Bujis and Lawrence (2013), where they, using the Netherlands and the UK as examples, demonstrate how the rational behavior of managers, researchers and politicians has labeled “irrational” emotions and traditions of local communities, environmental groups and the foresters themselves. The Netherlands is also taken up by Van Gossum et al (2012) as the study area for analysis of relation between policy design and policy success; and found out that an important factor for successful policy is the governmental support to surrogate regulators of the policy. In a case of strategic policy of the forestry sector – the National Forest Programme process, Elasser (2002) takes as a game-theoretic approach to explaining the stakeholders` participation and on how their co-ordination affects decision rules; all with a purpose of designing a more equitable negotiation process. Krott (2012) has studied the science-policy interface through RC perspective, where he points to how selection of topics is misused by political interests and where science loses a part of its legitimacy; nevertheless, it also identifies three strategies by which science can “defend” itself from the misuse by powerful stakeholders. Hiedanpääet al (2011) have used a series of case studies to demonstrate how lack of institutional incentives to comply within international biodiversity legislation has produced national policies which actually have negative effect on biodiversity conservation; and by concluding how a design of new governance principles may establish adherence to ecosystem approach in national policies. The same topic was taken up by Glück (2000a), where he has used RC to explain the behavior of actors in the global forest policy arena on how the international forestry and forest-related legislation enhanced the protection of biological diversity. He has also used RC the same year (Glück, 2000b) to analyze how the interests of private forest owners can be furthered by forest management regimes with different rotation ages. Environmental considerations were the topic of Stern and Predmore (2011), where they have studied the discrepancy between the interests of individual and corporate actor in the case of disclosing environmental impacts of forest management activities within the U.S. Forest Service. Relation between the Environmental Policy Act and the U.S. Forest Service was also taken up by Kaiser (2006), where the impact of the Policy on the Production of Environmental Amenities by the U.S. Forest Service was analyzed. Furthermore, the shift from a “narrow” to a “wider” perspective of the RC theory was taken up by Lejano and de Castro (2014), where they have used a vector payoff model to expand individual utilitarian decision logic on incorporating tradition and empathy in several different contexts. Seeing Rational choice as a theory that just incorporates pursuit for individual utilitarian interests O'Neill (1997) has deemed it unfit to explain the issue of valuation of biodiversity, where environmental management even still manages to resolve conflicts through decisions that do not appeal to monetary values. Similar perspective was taken up by McDermott

(2012), where she has shown how the rationalistic behavior of local suppliers in British Columbia has moved them away from NGO supported FSC system of certification toward the industry-backed competitor schemes, which in return caused normative distrust of their clients. By looking on how RC was used in natural resource management, Salazar and Lee (1990) have stated that in most of its applications RC is interpreted very narrowly, and is being focused on advocating certain public policies, rather than testing its theoretical claims through strong inference (which shows similarity to the findings of the literature review of ACF in forestry). Rational choice theory has created strong criticism within sociology, where Tilly (1997, p.83) calls it “misleading psychological reductionism” and Heckathorn (1997, p.15) states that Rational choice even produces “hysteria” in some sociological circles. However, all the criticism comes from proponents of other theoretical directions; as Blau (1997) from his focus on macro structures states that Rational choice to its focus on individual falls out of the domain of sociology. From the feminist position, England and Kilbourne (1990) criticize its focus on self- interests, and from the point of symbolic interactionism, Denzin (1990b) discards it is as implausible for explaining the organization of society. This kind of heavy criticism has caused a negative reaction of the proponents of Rational choice theory who have in turn developed a “…tendency to ignore, absorb, or discredit competing theoretical accounts” (Green and Shapiro, 1994), thus making the theory “…tautological and invulnerable to falsifiability” (Ritzer, 2008, p.452), and with a “…capacity to explain everything and hence nothing” (Smelser, 1992, p.400).

3.3. Boundary between science and policy

The demarcation between science and non-science has been the interest of sociologists for a long time; Comte`s (1975) “law of three stages” argues that only positive science uses “reasoning and observation”, Popper (1965) develops a demarcation of science from non-science through falsification, by which a theory is challenged against empirical data. A moderate shift from the positivistic view on science was held by Merton (1973) who sees modern science as disseminating “proven” knowledge which is in part defined by institutionalization of distinctive social norms:

 Communalism by which scientific results belong to the entire scientific community  Universalism by which prejudice on joining the scientific community is ruled out  Disinterestedness by which scientists act toward public, and not personal gain  Originality which further the development of the body of knowledge  Organized skepticism which assures the validity of a given claim through critical scrutiny

With the passage of time the positivistic conceptions on the separation of science from non- science by means of objective testing are more commonly seen as a failure (Bohme, 1979). Also, the proposition of the separation of science from non-science is an inadequate heuristic of the sociology of knowledge (Collins, 1982), where science can be seen as an ideology. There are two dominant sociological theories of ideology; the strain theory and the interest theory. The strain theory is associated with Parsons (1967), who sees it as “evaluative integrations” of conflicting demands and the ambivalence in society. The interest theory is associated with Marx (1976) who sees ideologies as tools of social groups to pursue their interests, and thus manipulate people to act in their interests. Geertz (1973) sees high level of compatibility between these two theories as ideologies as they can both level inconsistencies and further interests. In addition, both ideologies emphasize the social function and downplaying the symbolic formulations, and what is more, they see symbolic representations of norms and values.

From a positivistic position (Parsons 1967) ideology is distinct from science, which has a function of recognizing ideologies. Zeltin (1968) argues that ideology is an unavoidable part of scientific knowledge and that its boundary (to ideology) is difficult to locate, whereas for Marcuse (1964) science is ideology. This is also a strain of thought followed by Habermas (1970) where he sees forms of scientific knowledge having its own values and norms, and which may substitute the “bourgeois ideology”. In a similar vein Gieryn (1983) also sees science as ideology, and analyzes three historical examples of its “boundary work”, i.e. relation of science to policy. Gieryn sees little difference between science and any other profession and occupation, where the “boundary-work” is a resource for the focal ideology, namely:

 “when the goal is expansion of authority or expertise into domains claimed by other professions or occupations, boundary-work heightens the contrast between rivals in ways flattering to the ideologists' side”  “when the goal is monopolization of professional authority and resources, boundary-work excludes rivals from within by defining them as outsiders with labels such as ‘pseudo’, ‘deviant’, or ‘amateur’  “when the goal is protection of autonomy over professional activities, boundary-work exempts members from responsibility for consequences of their work by putting the blame on scapegoats from outside” (Gieryn, 1983, p.792)

Kohler sees same rhetorical style that reinforces ideology within scientific disciplines, stating that "Disciplines are political institutions that demarcate areas of academic territory, allocate the privileges and responsibilities of expertise, and structure claims on resources" (Kohler, 1982, p.1). Even more “bleak” perspective is the post-modern view of Foucault (1973), where he follows the developments of the medical profession, claiming that it was formed through usage of humanistic scientific discourse which furthered the power interests of its proponents. To add, in modernity people look up to the medical profession in order to break the illusions that mask the reality beneath it, just as they turned to medieval priests before that, where prayers and

61 otherworldly explanations have been replaced by the “clinical gaze”. Similar conclusions are made by Brickman et al. (1987), arguing that in situations with stipulated uncertainty, presentation of scientific findings is modeled to fit different “realities” in accordance to different political interests.

Science-policy interface is also marked with competing vested interests of policy and science. Emphasizing indeterminacy of scientific knowledge a policy maker can create a scientific “escape goat” for an evaluation of a (failed) policy. Following this line of though policy makers can stipulate the deviations from the Mertonian norms of the presented scientific finding; stating that experts frequently disagree on the issue, bring contradictory experts and/or data to the formulation process, or discredit certain findings as influenced by certain political interests (Jasanoff, 1987). Such actions are very threatening to the field of science as they challenge its dominant interpretation of “truth” and “facts”.

Gieryn (1983) argues that the “boundary” between science and non-science is set primarily through the usage of language. Another scholar, Jasanoff (1987, p.199) shares this view, and states that “the discourse of risk regulation has provided fertile ground for the creation of new linguistic labels whose primary function is to delimit the boundary between science and the political process…A study of the way these disparate interest groups use boundary-defining terms about policy-relevant science reveals their essentially contested character”.

The defense of the Mertonian ideals against the “negative” view of sociology of knowledge was given by Weinberg (1985, p.67), stating that:

“… it is not how science really works. Scientists are seen as competitors for prestige, pay, and power, and it is the interplay among these conflicting aspirations, not the working of some underlying scientific ethics, that defines scientific truth. To be sure, these attitudes toward science are not widely held by practicing scientists: however, they…nevertheless exert important influence on other institutions…that ultimately influence public attitudes toward science and its technologies”.

Even if interests are ruled out in a “real-life” situation, a public administrator cannot formulate a policy in a rational comprehensive way which follows all the steps of the positivistic-scientific approach, i.e, where all the values are expressive and are distinct from the alternatives, and where all the relevant factors are taken into account. Rather, the “real-life” policy formulation can be more precisely described through a model of successive limited comparisons, which is characterized by a complexity that blurs the distinction between policy alternatives and values that are to be addressed. Under such circumstances, the analysis neglects important possible outcomes, alternatives and values, and where the policies are formulated with diminished connection to the scientific theory (Lindblom, 1959).

3.4. Communicative action

Habermas` work is set with a goal of developing “… a theoretical program that I understand as a reconstruction of historical materialism (Habermas, 1979, p.95), where he critiques Marx for not differentiating between species-being (labor, a purposive-rational action) and social interaction (or communicative interaction). The purposive-rational action (teleological action) can be disseminated into instrumental action where a single actor pursues its self-interests, and the strategic action, where more actors coordinate their purposive-rational action to pursue their goals. The communicative action can be defined as where “the action of agents involved is coordinated not through egocentric calculations of success but through acts of reaching understanding. In the communicative action participants are not primarily oriented to their own success; they pursue their individual goals under the condition that they can harmonize their plans of action on the basis of common situation definitions” (Habermas, 1984, p.286). And just as Marx has looked at structural distortions that alienate people from their work, Habermas looks at social structures that distort communication. He draws analogies to psychoanalysis and Freud (Habermas, 1973), developing theory of systematically distorted communication. And just as psychoanalysts try to find sources in blocks of individual communication, so does critical theorists where they apply “a form of argumentation that serves to clarify systematic self- deceptions” (Habermas, 1984, p.21). This relates to the goal of the communicative action theory – its rationalization, which is free from power relations, and all other elements that distort it. The Theory of Communicative Action develops a concept of rationality that is not tied to limits of “the subjectivistic and individualistic premises of modern philosophy and social theory” (Habermas, 1979, p. VIII). He defines communicative action and not labor as the dominant characteristic of humanity, by saying “If we assume that the human species maintains itself through the socially coordinated activities of its members and that this coordination is established through communication – and in certain spheres of life, through communication aimed at reaching agreement – then the reproduction of the species also requires satisfying the condition of a rationality inherent in communicative action” (Habermas, 1979, p.397).

In a communicative model, actors coordinate their actions based on the shared and negotiated understanding of the situation, which is interest-free and is based on deliberative communication, where actors reflexively contest each other’s validity claims. This type of action is described (Habermas, 1979, p.100) as where

“…[a] definition of the situation establishes an order… A situation definition by another party that prima facie diverges from one`s own presents a problem of peculiar sort: for in cooperative processes of interpretation no participant has a monopoly on correct interpretation. For both parties the interpretative task consists in incorporation the other`s interpretation of the situation into one`s own in such a way that…the divergent situation definitions can be brought to coincide sufficiently”

Both strategic action and communicative action are of “teleological structure”, which means that both have their own “goals”, but strategic action assumes instrumental subject-object relation, whereas communicative action assumes mutual subject-subject relation. This difference between communicative and strategic action is seen as where “the rationality proper to communicative practice of everyday life points to the practice of argumentation as a court of appeal that makes it possible to continue communicative action with other means when disagreement can no longer be headed off by everyday routines and yet is not to be settled by the direct strategic use of force” (Habermas, 1979, p.17-18). As seen in this quotation, communicative action happens in everyday life; and is different from discourse, which is “that form of communication that is removed from contexts of experience and action and whose structure assures us: that the bracketed validity claims of assertions, recommendations, or warnings are exclusive objects of discussion. What is more is that participants, themes, and contributions are not restricted except with reference to the goal of testing the validity claims in question; that no force of the better argument is exercised; and that all motives except the cooperative search for truth are excluded” (Habermas, 1975, p.107-108). Since the object of inquiry (i.e. communication) is socially constructed by interpretative activities of its members, the researcher can gain access to its meaning only be interpretative understanding, which requires in-depth knowledge of the contextual arrangements.

Habermas defines two more types of action; normatively regulated action and the dramaturgical action. For normatively regulated action Habermas suggests that it occurs almost automatically, out of deeply set habits and beliefs, as it is fulfilling a generalized expectation of behavior, and he differs it from strategic action, where it “does not refer to the behavior of basically solitary actors who come upon other actors in their environment, but to members of a social group who orient their action to common values” (Habermas, 1984, p.85). In strategic action activities of actors are defined on an individual level, and in normatively regulated action activities of actors are defined on a group level. The dramaturgical action is defined as an interaction of actors who “[constitute] a public for one another, before which they present themselves. The actor evokes in his public a certain image, an impression of himself…” (Habermas, 1984. p.84). He also states that it could be an extension of the strategic action and that it is used “primarily in phenomenologically oriented descriptions of inter-action; but it has not yet been developed into a theoretically generalizing approach” (Habermas, 1984. p.86). The Theory of communicative action draws from a large portion of sociology`s body of knowledge; the basis lies in the critical thinking and the dialectical approach of Marx (1867/1990). The concepts of rationalization and interpretative meaning (versthen) was drawn from Weber (Brubaker, 1984 and Soeffner, 2005, respectively), the teleological action was drawn from von Neumann and Mergenstern`s (1953) theory of strategic games, and normatively regulated action was drawn from Parsons (1937) structural functionalism. Dramaturgical action was based on Goffman`s (1959) work on how people present themselves in everyday life, and the communicative action was based on Mead`s (1936/1967) symbolic interactionism.

Unlike the Advocacy Coalition Framework or the Rational Choice Theory, Communicative Action is rarely used in forest policy analysis (Arts, 2012); as from the critical-discursive theories the “Foucauldian” approach gained more prominence (Winkel, 2012). Martin and Rutagarama (2012) have tried to assess the applicability of deliberative decision making process to the context of rural Africa, and found out that in general, both procedural and outcome justice can be reached; nevertheless, caution is needed in reacting to prejudice and needs for empowerment of certain groups of stakeholders. Kleinschmit (2012) has looked at the presence of the Habermasian concept of deliberative discourse in media on exemplary cases of environmental and forest policy; and concluded that discursive elements are missing in the media communication and that public (or even majority) consensus cannot be reached on the basis of argumentation that is presented in the media – as they operate within a context of risk or crisis. In a similar style Steffek (2009) looked at the dynamics of discursive legitimation in environmental governance, in its goals, procedures and outcomes; and analyzes the relation between different groups of actors in each of the three segments of governance. Schanz (2002) has focused its use on the Habermasian concepts on defining what the central characteristics of the National Forest Programme processes are, and he has defined them in its discourse - communicative aspects; however he also noted that in its practical implementation it can be best characterized by instrumental rationality. Central determinants of complex concept(s) was also a topic explored by Purdon (2003), where we used communicative action to critically examine the legitimacy on the discourse between the concepts of sustainable forest management and the ecosystem management. Habermasian approach to discourse was combined with Bourdieu`s concept of symbolic violence by Ohja et al. (2009) to explain how certain groups dominate the national forest governance progamme; thus challenging the effectiveness of deliberative governance.

In a Foucauldian tradition, a social context free from power relations is utopia; as Rotry (1989, p.68) puts it, the communicative rationality is “… a healing and unifying power which will do the work of God”. Similar view is shared by Miller (1987, p.90), stating that “[T]here is no guarantee that a formally symmetrical distribution of opportunities to select and employ speech acts will result in anything more than an expression of the status quo”. From a methodological point a critique of the Theory of communicative action comes from Kompridis (2006), who argues that it is not possible to reach the “view from nowhere” which the theory prescribes. The explanation of rationality of procedures through which agreement is made should be defined without reference to background or to the perspectives of the participants in the process. Rienstra and Hook (2006) put emphasis on its implementation elements, stating that Habermas places great emphasis on the notion of agency; as it is psychologically very difficult for an actor to have clear understanding of its own reasoning, clear preference rankings and defendable goals and values – all of which are preconditions for communicative rationality.

4. Methodological approach

This case study research employs content analysis of primary data to deductively test a series of hypotheses from several theoretical perspectives Although usage of the case study design with testing rival theoretical explanations has produced substantial body of knowledge (Allison, 1971; Keil, 1995; Markus, 1983; Ross & Staw, 1993; Shane, 2000), deductive theorizing is usually connected to positivistic epistemological approach and to usage of quantitative data analysis (Yin, 2003); which also implies it being vulnerable to positivistic critique (Giddens, 1983). Using qualitative research techniques on testing a certain theory within a case study design is usually not a good strategy as “the study of a single case commonly yields more variables than data points” (Lee, 1989, p.35). Other argument against post-hoc deductive analysis is that researchers can “cherry-pick” the theoretical framework since they know the outcomes in advance, or they can choose a case that fits most with their (preferred) theory. A perspective “solution” to this situation is the pattern-matching technique (Yin, 2003), where a comparison of patterns from the observed outcomes is compared to some patterns of relations derived from the chosen theory (ies). In this manner evaluation of several variables is enabled, even in the instance of just one actual observation (case). The technique requires “a theoretical pattern of expected outcomes, an observed pattern of effects, and an attempt to match the two” (Trochim, 1989, p.360). Another approach to using deductive theorizing with qualitative data is to develop separate theoretical trajectory for each “theoretical lens” on a single case, where each of the “lenses” have their own assumptions, explanations and recommendations. This is in line with what Langley (1999) calls “alternate templates strategy”, and comparing these different “templates” allows for an opportunity for a post-positivistic falsification test (Popper, 1968). A well-known example of the alternate templates strategy is the view of Allison (1971) on the Cuban missile crisis, and an example of mixing alternate templates strategy with pattern matching is the work of Kiel (1995) where he applied the theories on a single case on the development of information systems. The research design of Chapter III is provided in Figure 13.

CHAPTER III

WORKING GROUP ON FORESTRY Role of different discourses

Normative approach Rational approach Scientific approach

Advocacy coalition framework Rational choice theory Theory of Communicative action

Hypotheses testing Hypotheses testing Hypotheses testing

Testing by contradictory hypotheses

DISCUSSION Narrative coding of the domain of validity for each approach

Figure 13. Research design of Chapter III

Combining alternate templates strategy with pattern matching is in line with what Bitektine (2008) calls a prospective case study design. In such a design analysis the formulation of the patterns of testable predictions (or hypotheses) based on theory is made at the beginning of the research. At this phase of research the criteria for the evaluation of outcomes are also developed; i.e. a “guide” to which kinds of outcomes will support / disprove a given theoretical perspective as the most fitting explanation of the research phenomenon. Only after these elements are developed a follow-up research is conducted, at which point outcomes are evaluated against the previously formulated propositions or hypotheses. In this manner, the outcomes in the analyzed case are not related to the choice of the case, the theories, or the hypotheses and propositions derived from these theories. The hypothesis coding is appropriate for hypothesis testing through content analysis of the qualitative data, and is especially appropriate as a continuation of a quantitative analysis, where it can relate to the previous findings of the research (Saldaña, 2009)

Following this line of thought, three “patterns of testable predictions” (or approaches) are chosen as a framework through which the data is analyzed. These patterns are:

1. Normative approach This approach is based on the Advocacy coalition framework (Sabatier, I986) and the normative action (Habermas, 1984). The primary unit of analysis is a group of actors who share the same beliefs, and their actions are deeply rooted in adherence to values commonly shared within the group. Policy learning is the mechanism by which certain change in these beliefs may occur, and in this process science is a frequently used instrument to further the

groups` interests within a given public policy. Power relations among the actors play an important role in this process.

2. Rational approach This approach is based on sociological Rational choice theory (Coleman, 1990) and strategic action (Habermas, 1984). The primary unit of analysis is the individual and his/her organization, within which individuals act as corporate actors. They act with the goal of maximizing the realization of self-interests. The interests are analyzed from the pluralist`s, one-dimensional view on power (Dahl, 1957), where they are equaled with policy preferences as revealed by political participation. The generalized organizational interests are seen from a resource-dependence perspective (Pfeffer and Salacnik, 1978), where it is inherent for organizations to have a desire to expand their resource base, increase the range of their authority, and to decrease the uncertainty in conducting their activities. With these wants as motivations for action actors rationally calculate what kind of strategy to employ in order to achieve these wants, and in a context of public policy try to reach a compromise that is favourable to them as much as possible. Science in this process is also used strategically to further certain interests. In addition, science has its own inherent interests, such as keeping the monopoly on truth and the expansion of authority or expertise held by other occupations. Power relations among the actors play an important role in this process.

3. Communicative approach This approach is based on communicative action (Habermas, 1984), while accepting the “real life” limitations of the policy formulation process (Lindblom, 1959). The starting point is the individual, who enters into communication with other individuals in order to find an “optimal” solution to the problem. Although only limited comparisons are possible between all the relevant alternatives, values and outcomes, all the individuals involved in the policy formulation process engage in a discourse based on scientific argumentation, and where they consensually make their decisions based on shared understanding of the situation. This kind of communication is undistorted by the power relations among its participants, or by differences in their values and norms. Science is seen as a social process where its community disseminates “proven” knowledge to society, a process which is rooted in strict adherence to a group of norms (Merton, 1973) commonly shared by that community. Results based on communicative approach are seen as results based on scientific argumentation, and are coded as such (code Science).

Based on literature review a series of factors by which these approaches differ between each other have been identified. These factors are presented in Table 6.

Table 6. Differences between the normative, rational and communicative theoretical approaches

Normative Rational Communicative Starting point Group Individual / Organization Individual Furthering of beliefs Maximizing the realization “Optimal” solution of Motivation within the public policy of self-interests the problem Discursive construction Mechanism Normative Rational of outcome

Decision based on shared understanding of Outcome Policy learning Compromise the situation

Adherence to Mertonian Instrumental usage of Role of science Science as ideology norms science

Type of action Normative Strategic Communicative

Importance of power High High Low /none relations

These factors are the basis for the construction of a series of hypotheses (Table 7, p.77) as envisaged by the prospective case study design. A “soft” approach to deductive hypotheses testing has been used. The “path” for construction of hypotheses begins with core assumptions of each of the theoretical approaches, through auxiliary assumptions and finally to the formal hypotheses. In this approach if a hypothesis is found to be untrue (falsified), a conclusion is not drawn that the theory is untrue; rather that it is not a well-fitting explanation of the phenomenon. In this context there is no null-hypothesis, and the outcomes of the falsification procedure can either “support” the hypothesis, have a “lack of support” for its predictions, or be “inconclusive”. The construction of the hypotheses that were tested follows a path from the core hypotheses of each of the theoretical perspective through a series of auxiliary hypotheses (or assumptions; Earman, 1992) that frame the conditions under which the testing of hypotheses can be performed. An example of an auxiliary assumption for testing ACF`s hypothesis on the similarity of policy core beliefs within an advocacy coalition would be that there exist one or several clearly identifiable advocacy coalitions. An example of an auxiliary assumption of the theory of communicative action would be that decisions of the working group are based on the communication between its members regarding the hypothesis. What is more is that the decisions of the working group are based on discourse with shared and negotiated understanding of the situation. In Rational choice theory auxiliary assumptions are called ‘bridge assumptions’ (Wippler and Lindenberg, 1987; Esser, 1998), as they bridge the distance from the social context to the individual actor. An example of a bridge assumption for the Rational choice hypothesis is that interests of the members of the working group will not change as there were no major perturbations in the policy sub-system during the period in which the working group was formulating its decisions. The hypotheses were also constructed in order to contradict one or

69 several other hypotheses from alternative theoretical approaches. The purpose of this procedure was to present alternative hypotheses as contradictory valid arguments for a given hypothesis, by which the “fit” of a given theoretical approach for explaining the activities of the working group would be improved. In this context the contradictory valid arguments do not need to have a strict logical contradiction to the focal hypothesis; it is adequate if they offer alternative explanations of the same phenomenon. An example of such contradiction is the contradiction between the first hypotheses in all of the three theoretical approaches. The abovementioned three hypotheses address the similarity of policy preferences between the members of the working group; as they are similar within an advocacy coalition (hypothesis N1), within an organization (hypothesis R1) or they are universally shared by the members of the working group (C1) at the end of the decision making process. If for example the “soft” deductive testing for hypotheses N1 and R1 supports their predictions but finds lacking support for C1, then through their comparison it could be stated that the falsification procedure is inconclusive for N1 and R1; as there is evidence for equally valid contradictory arguments. Following this hypothetical example based on testing of just three hypotheses it could not be stated whether normative or rational approach is a more fitting explanation for the similarity of policy preferences between the members of the working group. The explanation of the contradictions between the hypotheses is presented in Annex V.

Following the literature review, the core assumptions of the normative theoretical approach are (Jenkins-Smith and Sabatier, 1994; Sabatier and Weible, 2007):

 Policy change requires a historical perspective that covers at least a decade  Policy change is best observed within a policy subsystem, i.e. in the interaction of stakeholders who follow and try to influence governmental decisions of a policy area  Subsystems must include intergovernmental relations  Public policies can be conceptualized as belief systems, i.e. a set of values and assumptions on how to realize them  Beliefs are categorized on a three point scale: deep core beliefs, policy core beliefs, secondary aspects  The paths to policy change exist: policy oriented learning, external subsystem events and negotiated agreements  Coalitions are stable over time

Since this research is concerned with a short time horizon, it does not capture the entire policy sub-system. It is in fact centered on a single formulation process of a novel policy, and not all the hypotheses of the ACF could be tested. Due to these limitations four formal hypotheses of ACF (as written in Jenkins-Smith and Sabatier, 1994; references to these hypotheses are in Annex IV) have been selected for testing. In addition, the ACF`s four “devil shift” (Sabatier, 1987) are tested. The hypotheses developed by ACF`s authors that are tested in this research are used in their original form and do not have an explicit reference to the working group. This reference is

70 implicit, and all the actions addressed to these hypotheses (operationalization, testing, commenting) are performed with a reference to the forestry working group on Natura 2000. Other hypotheses are constructed following the factors which explain the differences among the theoretical approaches. From the perspective of Advocacy coalition framework, general beliefs of the forestry and nature protection sectors are equated with the “multiple use forestry” paradigm and the “environmentalist paradigm” (Glück, 2000a). In the multiple use forestry the objective function is to “maximize the periodic benefits minus the costs of sale of wood and non- wood goods and services”. In this context, the state intervention has to secure the minimum supply of non-marketable forest related services, such as biodiversity or avalanche protection. The environmentalist paradigm is based on ecological sustainability, and its objective function is to “maximize the resistance and resilience of forest ecosystems (including conservation of biodiversity)” (Glück, 2000a, p.197). In this context the state intervention has to secure the minimum requirements of non-timber goods and services, such as recreation and non-wood forest products.

Following the literature review, the core assumptions of the rational approach (i.e. Rational Choice Theory) are (Opp, 1999; Voss and Abraham, 2000; Fehr and Gintis, 2007):

 Behavioral explanation is explained by a selection among alternatives  Preferences and constraints of actors are the major determinants of their behavior  Actors choose alternatives which are optimal in terms of their preferences (with respect to their constraints)

In order to separate itself more from other alternative theoretical approaches and to avoid the criticism of tautology (Smelser, 1992; Mood, 2009) the “narrow” perspective on Rational choice theory has been chosen, which unlike the “wider” perspective (Yee, 1997), does not take into account values and internalized norms. The “narrow” perspective takes the position of Homo economicus (Mill, 1874; Persky, 1995), whose core assumption is that actor is “…optimally informed rational egoist, they are concerned with tangible consequences of their actions, and take into account only objective constraints” (Kronberg and Kalter, 2012).

Following the literature review, the core assumptions of the communicative approach (i.e. Theory of communicative action and Mertonian view on science) are:

 Communication is based on shared and negotiated understanding of the situation  Communication is free from power relations  Discourse is conditioned by a consensus on the validity of claims that are made by the actors  The primary function of science is to disseminate “proven” knowledge, which is primarily defined by institutionalization of the following social norms: Communalism, Universalism, Disinterestedness, Originality and Organized skepticism

A total of 28 hypotheses have been constructed. The path from the core assumptions, through the auxiliary assumptions and finally to the hypotheses that were tested is presented in Annex IV. Testing of the hypotheses is mainly done through content analysis of primary data. The basis of the content analysis is a code book designed to correspond to concepts and variables from the hypotheses. The formal hypotheses and their operationalizations are presented in Table 7. The codes in Table 7 are written in italic, the “/” sign marks two or more codes from the same group of codes, and the sign “→”designates the transition from a group of codes to its subset.

Table 7. Hypotheses and their operationalization

Normative approach Hypothesis Operationalization 1. Actors within an advocacy coalition  Differences in policy preferences within a coalition show substantial consensus on issues are smallest for the most policy core topics pertaining to the policy core but less so on secondary aspects 2. An actor or coalition will give up  Codes Topic → Opinion on topic →+1, -1 and 0 secondary aspects of a belief system from time 1 change in time 2, but the ones that had before acknowledging weaknesses in +2 and -2 do not the policy core 3. Policy-oriented learning across belief  Changes in Topic → Opinion on topic occurred in systems is most likely when there is an topics that did not have strong +2/-2 dichotomy intermediate level of informed conflict between the two coalitions 4. Problems for which accepted  Changes in Topic → Opinion on topic occurred in quantitative data and theory exist are topics where all groups of Subject → Information more conducive to policy-oriented on topic were marked mostly with +1 code learning across belief systems than  Changes in Topic → Opinion on topic occurred in those in which data and theory are topics for which the dominant code in the generally qualitative, quite subjective, Information on topic group of codes was Adequate or altogether lacking 5. Within a coalition, administrative  Actors from administrative agencies have less +2/-2 agencies will usually advocate more codes in Topic → Opinion on topic than other moderate positions than their interest actors group allies 6. Members of the working group will  Codes of actors within the Topic → Opinion on have their beliefs aligned with the topic category will be aligned according to the general beliefs of the forestry and the general sectoral policy beliefs (Glück, 2000a) nature protection sectors 7. Actors will evaluate their opponents'  The dominant code in the Rationale group for behavior in harsher terms than will actors out of the focal coalition is Compromise most members of their policy  The dominant codes in the Rationale group of community, while evaluating their codes for actors in the focal coalition are Science own behavior in more favorable terms and Policy learning  The Strategic code (for usage of information) is related to the actors from the out-group

8. Actors will perceive their opponents to  Non influential code is mostly used to describe be more influential, and themselves to members of the in-group, and Influential code is be less influential, than will most mostly used to describe members of the out-group members of their policy community 9. The amount of distortion (or "devil  The distribution of influence codes is positively shift") is correlated with the distance correlated to the difference in the Topic → Opinion between one's beliefs and those of on topic codes between the focal actor and the one's opponents one(s) that he/she is talking about Rational approach Hypothesis Operationalization 1. Policy preferences of the members of  Distributions of codes in Topic → Opinion on topic the working group are distributed group of codes are more similar among actors according to the organizational within the same organization than among actors interests from different organizations

2. Policy preferences of the actors will  Distributions of codes in Topic → Opinion on topic stay the same group of codes will not substantially change

3. Decisions which are aligned with the  Decisions which are skewed toward the opinions of interest of the focal group are the focal group have dominant Scientific rationale characterized as based on scientific code attributed to them, whereas the out-group will criteria, whereas the ones that are not attribute more codes Policy learning and are characterized as based on non- Compromise to the same topics scientific criteria 4. Actors will strive to restrain behavior  Interruptions in the dyadic communication in the of other actors that goes against the meetings of the working group are correlated with interest of the focal actor the difference in opinions (Topic → Opinion on topic) between the person doing the interruption and the interrupted person 5. Scientists in the working group will  The dominant codes in the Rationale group are disapprove scientific findings coming Policy learning and Compromise when related to from other sectors, and approve actors from different sector, and code Science for finding from her/his own sector the actors from the same sector as the focal actor Relates only to actors from scientific organizations 6. Actors will describe the outcomes of  The dominant code in the Topic → Outcome group the working group as a compromise is the Compromise code 7. Actor use strategically information  Code Strategic in the Information on topic group of from their field of expertise to further codes has high frequency for matching actors certain interests or beliefs (Subject codes) and Topics

8. The topics with most divergent policy  The highest frequency of Contradictory codes is preferences are characterized by related to Topics for which have most pronounced contradictory information dichotomy of +2/-2 codes

9. Procedural elements for decisions  There will be more Rules unknown codes than making will be less known for topics Rules known codes for topics in which the leaders for which the interests of those leading of the policy formulation (SINP) have higher the process is higher interest on

Communicative approach Hypothesis Operationalization 1. The decisions of the working group  At Time 2 distributions of codes in Topic → are based on consensus among its Opinion on topic group of codes are similar among members actors for majority of the topics 2. Changes in opinions of the members  Change in codes in Topic → Opinion on topic of the working group is related to the group of codes from time 1 to time 2 is greater for amount of the information available on topics which have higher frequency of Adequate that topic than Inadequate codes from the Information group of codes 3. Actors in the working group critically  When stating their policy preferences (Opinion on assess the validity of the claims that topic codes crossed with Topics codes) crossed support their interests and beliefs with Science rationale actors will frequently use Inadequate code from the Information on topic group of codes - more frequently than Adequate 4. Members of the working perceive the  The dominant code in the Topic → Outcome group decisions being made as decisions is the code Science based on scientific argumentation 5. Members of the working group had  The Adequate and Inadequate codes in Topic → equal available information on the Information on topic group are equally distributed topics that were discussed across all actors for all topics 6. Members of the working group  Codes Strategic and Contradictory from the perceive that all of them had shared Information on topic group of codes are not understanding of the issues that were dominant for any of the topics. All codes in the discussed at the meetings Information on topic group are equally distributed among the actors 7. No members of the working group had  The influence codes are equally distributed among the dominant influence on the Subject group of codes for all of the topics decisions that the group made 8. No member(s) of the working group  No actor had dominated in the frequency of the had the monopoly over the correct Science code for any of the topics interpretation of the issues that were addressed by the working group 9. The procedural aspects for the decision  In the Process group of codes there are more Rules making are known to the members of known codes than Rules unknown codes for all of the working group the topics 10. Distortions in the communication  The frequency of Impeding communication code decrease with the passage of time from time1 to time 2 has decreased, and the frequency of Facilitating communication code has increased

The operationalization of hypotheses relates to different codes which represent the basis of the content analysis. The names of the codes are written in such a manner that they reflect the meaning of the codes. The entire code book with their meaning (in memos) is presented in Annex I, and without the memos in Figure 14

Figure 14. The coding scheme

According to their operationalizations, the testing of the hypotheses is performed by appropriate univariate (frequencies and central tendencies) and multivariate analysis techniques (regression, correspondence analysis, cross tabulation, and quadratic assignment procedure).

The discussion section reflects upon the results also through narrative coding (Saldana, 2009), where parts of the transcription of the interviews with the members of the working group are related to a concept or a certain hypothesis, and then arranged to form a “story” which is consistent with certain theoretical framework. In this context narrative coding forms a research representation that depicts “how and why a particular outcome came about” (Polkinghorne, 1995, p.19). The elements for the narrative coding come from interviews with the members of the working group and from observations of the meetings of the working group. Two observers were present at the meetings of the working group, and their task was to take detailed minutes on what was happening, with a focus on writing down all important quotations which relate to the normative standpoints of the members of the working group, which provide explanation to their behavior, and the ones which depict the usage of scientific argumentation.

There were eleven meetings of the working group, from March 18th 2010 until October 11th 2012.The list of organizations that were represented in the working group is provided in Table 8.

Table 8. List of organizations that were represented in the working group

Organization Acronym Alliance of private forest owners` APFOA associations Croatian Academy of Sciences and Arts CASA Croatian Forests Ltd. CF Croatian Forest Research Institute CFRI Croatian Forestry Society CFS Croatian Natural History Museum CNMH Croatian unions of private forest owners CUPFOA associations Forest extension service FES Faculty of Forestry, University of Zagreb FOF MA – on several instances separated on the Ministry of Agriculture Department on Hunting (MDH) and Department of Forestry (MDF) Ministry of Culture, Directorate on nature MCDNP protection State Institute on Nature Protection SINP

The working group was composed of representatives from many organizations both from the forestry and nature protection, and it covered state administration (Ministry of Agriculture - MA; Ministry of Culture, Directorate on nature protection - MCDNP), implementing and expert state agencies (State Institute on Nature Protection – SINP; Croatian Forests Ltd – CF; Forest Extension Service - FES), scientific organizations (Croatian Academy of Sciences and Arts – CASA; Croatian Natural History Museum – CNMH; Croatian Forest Research Institute – CFRI; Faculty of Forestry, University of Zagreb - FOF) and several organizations which can be best characterized as stakeholders (Croatian Forestry Society – CFS; Alliance of private forest owners` associations – APFOA; Croatian unions of private forest owners associations – CUPFOA). The collection of the data began with the third meeting, which was held on March 29th, 2011. All the members of the working group (a total of 29) were interviewed by June 2011 and then again after the final meeting of the working group, with the last interview held on the 8th of April, 2013. Following ethical guidelines for qualitative research (Creswell, 2007) a written consent was obtained to interview all the members of the working group. The interviews were also followed by questionnaires, which all of the members of the working group have fulfilled. Majority of data from the questionnaires is analyzed in the subsequent part of the research which applies social network analysis. Both parts of the research use a total of nine topics which reflect the issues that were covered by the working group. These topics were selected on the prior knowledge of the subject matter, on communication with six members of the working group and on communication with four other experts who were not part of the working group, both from the fields of nature protection and forestry. Before the interview a

76 summary of the research was given to them, along with an information letter which describes the ethical considerations of the interview:

 Although full anonymity cannot be provided, anonymization is applied, as their names are coded. The results and discussion focus on the status and the changes on a group level, and not on the individuals  Interviewees can choose not to answer any of the questions, they can stop the interview at any time, and choose to be totally excluded from the research  After the interview the interviewees receive a copy of the interviews` transcript, and no work will be done on them before the interviewees validate it

After all the interviews were made and analyzed a nine-page version of research (with analysis, results and discussion) was send to the interviewees to comment, and it was agreed that the parts which were misinterpreted or could possibly harm the interviewees will be deleted. No such demands by the interviewees were made.

Transcription of the interviews was performed in F4 programme (demo version). The content analysis was performed in MAXQDA, and a total of 2398 codes were assigned to the interviews. The data preparation was done in Excel. The smaller part of the analysis (Quadratic assignment procedure) was performed in UCINET, and most of the visualizations were done in NetDraw.

5. Results

5.1. Normative approach

The existence of advocacy coalitions has been approximated with the grouping of actors according to similarity of their opinions on the topics discussed by the working group. Actors are defined as all members of the working group and all organizations as well as groups discussed about during the interviews. In order to analyze similarity of opinions between the actors, codes from Opinion on topic group of codes have been summed up for each actor and for each of the eight identified topics. Actor-by-topic matrix of opinions has been transformed to actor-by-actor matrix of differences of opinions by adding up the differences between opinions on all of the topics among all the pairs of actors. These values have then been transformed into actor-by-actor matrix of similarity of opinions, expressed as percentage of similarity of opinions. The visualization of this matrix is given in Figure 15, where the proximity between the actors represents the similarity of their opinions (the closer they are to one another, the greater is the similarity of their opinions; multi-dimensional scaling layout, stress 0.169).

Figure 15. Similarity of opinions between actors (See Table 8, page 77 for acronyms)

Only similarities larger than the mean value have been presented. Figure 15 shows the grouping of actors according to sectoral division; with the exception of actor FOF2 all the actors from the forestry sector are on the right side, and all the actors from the nature protection are on the left side. It can also be seen that the sectoral implementing/expert organizations (Croatian forests Ltd. and State institute on nature protection) are close to the central sectoral opinions, and are more apart from the actors of the other sector than the average actor from their own sector. Sectoral state administration (Ministry of Agriculture and the Ministry of Culture, Directorate on Nature Protection) bodies along with the two research organizations (Croatian Forest Research Institute and the Faculty of Forestry, University of Zagreb) are located in the center of the graph, and serve as a “bridge” between the two sectors. Figure 15 also shows that the greatest dissimilarity of opinions between is between actors SINP5 and CF1, both of which are very influential within the working group: Actor SINP5 was one of the two leaders of the working group, and CF1 was the main representative of the Croatian Forests Ltd. In order to supplement the grouping of actors according to their opinions, a “we” actor-by-group, two-mode matrix was constructed, which was accomplished by assigning groups to actors every time the interviewees made a statement in which they had affiliated themselves to an identifiable group. The visualization of that matrix is provided in Figure 16, and as in the previous figure, the proximity between the two points reflects their level of association (multi-dimensional scaling layout, stress 0.193).

Figure 16. Association of individuals and groups (See Table 8, page 77 for acronyms)

Sectoral division is even more pronounced than in the previous figure, where the “bridge” between the two sectors is an employee of the State Institute on Nature Protection (SINP1) who has graduated from the Faculty of Forestry, University of Zagreb. Based on these findings the following analysis assumes grouping of actors according to the division on the forestry and on the nature protection sector, which are in the context of advocacy coalition framework equated to advocacy coalitions.

In order to find out whether or not members of an advocacy coalition demonstrate consensus on key issues (hypothesis 1), codes in Opinion on topic group have been summed up for each actor and topic for time 1 (beginning on the research) and time 2 (after final meeting of the working group). The actors in each sector have been grouped into state administration, actors who are tied to scientific organizations, and other actors (implementing agencies and other stakeholders). The topics have been grouped into policy core topics (designation of sites and management guidelines for forest habitats), general attitude towards Natura 2000, and secondary topics (presence of deadwood, protection in strict reserves, limiting final cut, inclusion of private forests, and inclusion of ‘Spačva basin’ – a highly economically viable sessile oak forest). The differentiation to key and other topics was based on the frequency of codes assigned to each topic. Topics such as ‘site designation’ and ‘management guidelines’ had highest frequencies of all of the topics (n=210 and n=191) and were equally relevant to actors from both sectors. Based on the distribution of Opinion on topic codes, actors` opinions where then scaled in range from 0 to 1, where 0 represents extreme opinions related of the forestry sector (low environmental, high economic value), and the 1 represent the extreme opinion of the nature protection sector (high environmental, low economic value; Glück, 2000a). These relations are presented in Figure 17.

Figure 17. Opinions of different group of actors

It can be seen on Figure 17 that the groups of actors from the forestry sector show more consensus on the secondary topics than it is the case of key topics, while no conclusions on this

80 level can be made for the nature protection sector. The peak in the ‘other’ topics at the nature protection “science actors” which breaks the mild slope of the curve is caused by their strong preference for limiting the final cut in the even-aged forest management regime. These results show that the testing of hypothesis 1 of the normative approach shown lack of support for its predictions. It can also be seen that the implementing/expert groups of actors have more “extreme” opinions than their administrative counterparts, which supports the predictions of hypothesis 5 of the normative approach. As different groups of actors from both sectors show alignment towards the general sectoral beliefs (Glück, 2000a), it can then be concluded that the predictions of hypothesis 6 of the normative approach are supported.

Policy learning has been defined as the greatest change of opinions (cumulative frequency of Opinion on topic codes for an individual topic) per topic from time 1 to time 2 within a sector, which was identified for limiting final cut and the presence of deadwood within the nature protection sector. This is in line with the hypothesis 2 and 3 of the normative approach, and is an expected result as these topics are in the range of expertise of the forestry sector. The expected topic of policy learning of the forestry sector is topic Natura 2000 in general; however the frequency and the distribution of Opinion on topic codes related to Natura 2000 in general has not showed signs of policy learning, as the cumulative negative attitude towards Natura 2000 in general has increased by 42%. The testing of hypothesis 2 of the normative approach supports its predictions as no sector has modified its policy core beliefs, and the nature protection sector has modified some of its secondary policy aspects. With respect to hypothesis 3 of the normative approach the results are inconclusive, as the policy learning was mostly present only in the nature protection sector.

When it comes to the quality of information per topic, all of the Adequate codes have been assigned to the Designation of sites (13) and Management guidelines (7) topics, and only one for Deadwood and the Final cut topics, for which policy learning has been identified. Following this line of thought on policy learning, interviewees were also asked: “Have you learned something from participating in the working group, and if so, what?” Their answers were categorized by sectoral division of the members of the working group, and all actors from the nature protection sector have answered that they have learned more on the forestry practice. In addition, all the actors from the forestry sector answered that they have learned about the general topic of Natura 2000. Although no adequate quantitative information was identified for the ‘Final cut’ and ‘Deadwood topics’, it seems that becoming more familiar with the general forestry practices was sufficient for policy learning. However, with respect to hypothesis 4 of the normative approach (accepted quantitative data as a precondition of policy learning) results are inconclusive.

The usage of compromise, policy learning and scientific argumentation as the rationale for the discussion in the working group was equally represented (106:101:80), with somewhat lesser share of the usage of the code Science. The distribution of these codes according to sectoral division of the actors shows that both nature protection and forestry perceive themselves as equally striving towards a compromise solution (40:43), while the usage of scientific

81 argumentation (45:19) and presence of policy learning (45:30) is much more frequently found in the nature protection than in the forestry sector. This indicates that members of the nature protection perceive themselves more open to adherence to scientific argumentation, and learning about and accepting different claims than it is the case with the forestry sector. The cross-sectoral perceptions of using different rationale for the discussion between the nature protection and the forestry sector is ‘balanced’, as it is similar for the usage of compromise (13:10), science (7:9) and policy learning (12:14). The harsher evaluation of the out-group compared to the in-group is signified by the distribution of codes Strategic (use of information); as all of the codes (n=30) are related to subjects from the out-group, and were more frequently used by the nature protection (18) than by the forestry sector (12). These results point towards support for the predictions hypothesis 7 from the normative approach.

The distribution of the influence related codes (Influential / Not influential) is strongly affected by the sectoral division of the actors; as both the nature protection and the forestry sector perceive the other sector as more influential (n. of the Influential code: NP→NP=12; NP→F=45; F→NP=26; F→F=16), and themselves as the less influential ones (no. of the Not influential code: NP→NP=21; NP→F=6; F→NP=4; F→F=21). It should also be noted that the actors from the nature protection sector perceive actors from the forestry sector to be much more influential (n=45). This is not the case with the opposite relation (n=26). These results support the predictions of hypothesis 8 from the normative approach.

In order to test the level of the “devil shift” the actor-by-actor matrix of differences between opinions on all eight topics has been compared to the actor-by-actor matrices of the Influential and Not influential codes through quadratic assignment procedure, which provides Pearson correlation measures of association for matrices. As the interviewees have identified group and sector level actors the codes assigned to these type of actors have been re-assigned to the individual actors who belong to these groups (e.g. an Influential code assigned to private forest owners has been re-assigned to the members of the working group which represent private forest owners). Results show that there is a weak (r=0.363, p=0.0016) positive association between the dissimilarity of opinions - the distribution of Influential codes, and there is very weak (r= -0.232, p=0.094) non-significant association between the dissimilarity of opinions - the distribution of Not influential codes. The low value of the correlation coefficients indicates that the results are inconclusive with respect to hypothesis 9 of the normative approach.

5.2. Rational approach

In order to test the homogeneity of opinions within and between organizations, the actor-by-actor matrix of similarity of opinions (in percentage of similarity) has been transformed to organization-by-organization matrix of similarities of opinions with respect to organizational

82 affiliation of individuals (e.g. all individuals from SINP have been grouped into SINP). This has been done only for the topics Designation of sites and Management guidelines, as it is assumed that the topics of policy core beliefs also represent the interest topics of actors, while secondary aspects represent means to reach the deeper goals. There is no case where the similarity of opinions within organization is greater than the similarity of opinions between the focal and all other organizations, indicating that the members of the working group have put more emphasis on personal beliefs than on the organizational policy preferences. These results point to the lack of support for the predictions of hypothesis 1 from the rational approach.

In order to test whether the actors` interest change or not, the interclass correlation coefficient (ICC) test (Two-way mixed model, absolute agreement type) has been performed on the topics Designation of sites and Management guidelines for Time 1 and Time 2. The average measure of ICC for Designation of sites is 0.874 (p<0.001) and for Management guidelines is 0.924 (p<0.001). As such, it can be stated that the policy preferences of actors have not changed; which provides support for the predictions of hypothesis 2 of the rational approach. According to the rational theoretical approach it is expected (hypothesis 3) that actors will evaluate decision that are in their favor (decisions based on scientific argumentation), and to evaluate the ones which are not (based on non-scientific argumentation). When asked on the implementation of a certain topic within the actual decisions of the working group (page 153) the implementation of both key issues (designation process and defining of management guidelines) was off-centered towards the positions of the forestry sector (by 22% and 13%). For designation of sites, the dominant rationale form the nature protection sector was scientific argumentation (20), followed by compromise (11) and policy learning (3), whereas from the forestry sector the dominant rationale for decision making was compromise (21), followed by policy learning (5) and scientific argumentation (4). For defining management guidelines the dominant rationale from the nature protection sector was compromise (7), followed equally by scientific argumentation (5) and policy learning (5). From the perspective of the forestry sector this was clearly an issue of compromise (9), as there was only one code Science linked to the topic, and none for the policy learning code. Results show that the designation of management guidelines was reached by compromise, whereas the opinions on rationale behind the designation of protection sites differ. However, the differences in the interpretation of the rationale diverge from the expectations of the rational choice approach, so it can be stated that these results point to the lack of support for the predictions of hypothesis 3 of the rational approach.

In order to find out whether or not actors attempt to restrain the behavior of those actors who have different opinions (hypothesis 4) the actor-by-actor matrix of (both successful and unsuccessful) interruptions in communication (summarized for all of the observed meetings) has been compared with the actor-by-actor matrix of differences in opinions on all of the eight topics. The comparison was done by applying quadratic assignment procedure, and it resulted with r=0.46 (p=0.044), which supports the predictions of hypothesis 4 of the rational approach. Scientists from the nature protection sector perceive their rationale primarily as scientific (code

83 science n=6). No conclusions on the rationale of the scientists from the forestry sector can be made, as the frequencies of policy learning, compromise and science codes is too low (n=1-2). The forestry scientists have equally considered policy learning and compromise as the dominant rationale for scientists both within (11 and 7) and out of the sector (9 and 7), while code Science was seldom used for both within (3) and out (2) of the sector. This indicates that data is inconclusive with respect to hypothesis 5 of the rational approach; as scientists from the nature protection were more concentrated with explaining their own expertise, and the scientists from the forestry sector did not make a sectoral demarcation when commenting the rationale of their colleagues.

The overall distribution of the Rationale codes shows equal frequency of Compromise (106) and Policy learning (101), with Science (80) being less frequently coded. The results indicate that no rationale played the dominant role, which points to lack of support for the predictions of hypothesis 6 of the rational approach. As presented in Figure 18, the distribution of Rationale codes differs between the topics that were addressed by the working group.

Figure 18. Distribution of Rationale codes by topic

In Figure 18 the ‘All decisions’ category relates to the overall activities of the working group. It can be noted that in general the dominant rationale for decision making was policy learning, which was also dominant for the secondary topics, such as limiting the final cut, inclusion of Spačva basin into Natura 2000 protection regime, and the permanent presence of deadwood. However, the two key issues for both sectors – the designation of protection areas and management guidelines, were predominantly seen as a matter of compromise.

In order to find out more on the potential strategic usage of information to further certain policy preferences (hypothesis 7), the code Strategic was intersected with codes in the Topic group and with the codes in the Subject group. The results of this analysis are presented in Figure 19.

Figure 19. Strategic usage of information by actor and by topic

It can be seen that the interviewees perceived Croatian Forests Ltd. and its representatives to have strategically used information on topics that are within their domain of expertise; as the designation process was based on the GIS data that the Croatian Forests Ltd. have provided, and the management guidelines are deeply rooted in the knowledge on the national forestry practices. A corresponding situation is found for SINP, as the interviewees have predominantly seen them to strategically use information on the Natura 2000 in order to further their policy preferences. These results support the predictions of hypothesis 7 of the rational approach.

The presence of contradictory information (code Contradictory) by topic was most pronounced for the issue of management guidelines (n=10), followed by perception of contradictory information for all of the addressed topics (n=6). The code Contradictory has intersected only twice with the Designation process code, and only once with the Natura 2000 in general code. This indicates that the presence of contradictory information is not related to the level of conflict on the policy preferences between the actors and it can be stated that results show a lack of support for the predictions of hypothesis 8 of the rational approach.

In order to find out whether or not the interests of the leaders of the process are related to the transparency of procedural elements for decision making on specific topics (hypothesis 9), the frequency analysis of intersections of codes Rules known and Rules unknown with different Topic codes was created. The first step was to identify the topics of key interests to the State Institute on Nature protection, and by the criterion of cumulative frequency by topic from the Opinion on topic codes, the key topics are management guidelines (40) and site designation process (20), followed by permanent presence of deadwood (11). The codes Rules known code was only assigned to the site designation process (8) and management guidelines topic (2), while Rules unknown code was most frequently related to site designation process (20) and to the topic of management guidelines (10). Topics on permanent presence of deadwood and rules of Natura

2000 had only 2 instances of Rules unknown codes assigned to them, while other topics did not have any of the procedural codes assigned to them. Although this might indicate that there was relation between the specific interests of SINP and the procedural elements of decision making, most of the Rules known (14) and Rules unknown (43) had been assigned to the overall discussions of the working group, with which it can be stated that the data is inconclusive with respect to hypothesis 9 of the rational approach.

5.3. Communicative approach

Looking at the cumulative change in Opinion on topic codes by each topic from time 1 to time 2, it can be seen that the opinions on the management guidelines became less polarized between the forestry (from -29 to -19) and the nature protection sector (from 31 to 19). Slight polarization occurred also for the site designation process (forestry sector from 25 to 32; nature protection sector from -4 to -11), while the strongest divergence occurred on the general attitude towards Natura 2000 from the side of the forestry sector (from -14 to -31). It should also be noted that no actor has changed the general orientation of her/his policy preference on any of the topics. All this indicates that the decisions that the working group made were not based on consensus, and so the results show lack of support for the predictions of hypothesis 1 of the communicative approach.

In the results chapter on normative approach, policy learning was identified from the side of the nature protection sector for the topics of limiting the final cut and the presence of deadwood. From the perspective that the change in opinions is based on scientific discourse (hypothesis 2), there should be more adequate information on these topics, than on the ones for which the opinions became even more polarized (such as management guidelines). As presented on page 79, no Adequate codes have intersected with the topics of limiting final cut and the presence of deadwood, so the results show lack of support for the predictions of hypothesis 2 of the communicative approach.

When providing scientific opinions on the abovementioned topics, actors tended to rely on available data and treat it as adequate (n=14), rather than to critically asses it (n=6). With these results, it can be stated that the findings demonstrate lack of support to the predictions of hypothesis 3 of the communicative approach. And as presented on page 82 (Figure 18: The Distribution of Rationale codes by topic), actors do not see the decisions of the working group as primarily based on scientific argumentation, by which the results show lack of support for the predictions of hypothesis 4 of the communicative approach.

When it comes to availability of information, the distribution of codes Adequate and Inadequate was analyzed by each topic and by each actor. The results show that on the topic of management guidelines both the nature protection and the forestry sector had similar frequencies of Adequate

(3 and 4) and Inadequate (7 and 8) codes assigned to them. The situation with the issue of site designation process is different, as forestry sector hosts most of the Adequate (9) and Inadequate codes (16; and for nature protection its frequencies were 4 and 2). The majority of the Adequate codes within the forestry sector for the site designation topic were assigned to actors from the Croatian Forestry Ltd. and from the Faculty of Forestry, University of Zagreb. This divergence in the availability of information within the forestry sector is caused by the fact that the actors from Croatian Forests and the Faculty of Forestry have participated in the designing of the proposal for the protection of forest habitats, while actors from other forest sector organizations did not. The information regarding Natura 2000 to a large extent belonged to the actors from the nature protection sector (Adequate coded five times), while there was a single mention of adequacy of information on Natura 2000 from the forestry sector. When it comes to distribution of the code Inadequate, for information on Natura 2000 it was coded 28 times within the forestry sector, and only once within the nature protection sector. This clearly indicates that members of the working group did not have equal information on the topics that were discussed, and so the results show lack of support for the predictions of hypothesis 5 of the communicative approach.

Although codes Strategic and Contradictory are not dominant for any of the topics, the actors from the nature protection have seen actors from the forestry sector to strategically use (n=9) information on the designation process, and forestry actors have seen nature protection actors as strategically (n=5) using information on Natura 2000 (there are no Strategic codes for the same topics in the opposite directions). With the results from the previous paragraph showing different levels of information among the actors, it can be stated that the results demonstrate lack of support for the predictions of hypothesis 6 of the communicative approach, i.e. that all of the actors did not have a shared understanding of the issues that were addressed by the working group.

When it comes to distribution of influence among the actors for the site designation topic, the frequency of Influential and Not influential codes is similar for the nature protection (5 and 6) and the forestry sector (6 and 7). The same situation is present for the management guidelines topic as the Influential codes were assigned only once to the forestry and nature protection sectors, and code Not influential were assigned five times to the forestry sector, and 6 times to the nature protection sector. The frequency of Influential and Not influential codes for other topics by actor were too low to formulate any kind of conclusions. These results indicate that no actor had the dominant influence on the decisions made by the working group, and so the results show support for the predictions of hypothesis 7 of the communicative approach.

When looking at the distribution of scientific expertise among actors by topics, it can be seen that no actor or group had a dominance in any of the topics; when comparing forestry and nature protection, the frequencies for Natura 2000 in general (5 and 7), site designation issue (6 and 7), management guidelines (6 and 9) and overall discussion (12 and 9) were similar between the sectors. The frequencies of Science codes for other topics were too low to make any conclusions. These results indicate that no actor or group had a monopoly on the interpretation of expertise on

87 a specific topic, and so the results show support for the predictions of hypothesis 8 of the communicative approach. As previously mentioned on page 84 (hypothesis 9, rational approach), there are more Rules unknown than Rules known codes assigned to all the topics which have and Process codes assigned to them. This indicates that in general the procedural aspects for the decision making were not known to the members of the working group, and so the results show lack of support for the predictions of hypothesis 9 of the communicative approach.

In order to find out if communication was getting more unbound from distortions, the distribution of codes facilitating communication and impeding communication was analyzed by actor (aggregated to sectoral level) for time 1 and time 2. The results show that the code facilitating communication remained relatively constant both for the forestry (10 and 9) and the nature protection sector (30 and 34). The same situation was identified for the impeding communication code (forestry 9 and 6; nature protection 12 and 15). Although no trends can be observed in the distributions of these codes, the three times higher frequency of code facilitating communication assigned to the actors from the nature protection sector indicates that they had contributed more to the cross-sectoral communication than did the actors from the forestry sector. The absence of clear trends in the communication related codes indicates that the results demonstrate lack of support for the predictions of hypothesis 10 (improvement of communication) of the communicative approach.

5.4. Deductive falsification of hypotheses

A closer look at the hypotheses from all of the three theoretical frameworks depicts that many of them are contradictory to other hypotheses from different theoretical approaches both in their content and in their operationalizations. These contradictory relations between all of the hypotheses are presented in Table 8 (a detailed explanation of contradictions is provided in Annex V).

Table 9. Contradictory hypotheses Normative (N) Rational (R) Communicative (C) No. of hypothesis Contradictory to hypothesis 1 R1, C1, N1, C1, N6, N1, R1,N6 2 C2 C2, N2, R2, N3, 3 C2 4 5 6 C1, R1 R7, R 8 7 C6 N8, N9 8 C7 C6 9 C7 C9 R9 10

The Advocacy coalition framework is deeply rooted in explaining the actors` beliefs and their change of beliefs, where that change is explained by a series of causal variables. With this relation in mind, the ACF for analytical purposes is regarded as a deterministic theory. The Rational choice however, sees a process of decision making as “different groups pulling in different directions produce a result, or better a resultant - a mixture of conflicting preferences and unequal power of various individuals - distinct from what any person or group intended” (Allison, 1971, p.145). This makes Rational choice a non-deterministic theory. The same logic applies to the theory of communicative action; as the meaning is shaped by and negotiated through interaction among individuals (Torfing et al, 1999), in this context discourse can be seen as communication through which meanings are constructed (Jones, 1995). The outcomes of such a discourse cannot be predicted; only the elements that distort it can be identified.

Choosing a deterministic and a non-deterministic theory may provide some insights of the explanatory power of the non-deterministic theory if the two theories have mutually exclusive assumptions. In a case when the predictions of the deterministic theory are correct, then the predictions of the non-deterministic theory would be superfluous, as the much more compelling evidence is provided by the deterministic theory. Although this kind of qualitative case-study design does not allow the process of falsification (Popper, 1968) of the non-deterministic theory, if the predictions of the deterministic theory are disproved than a strong argument can be made against the rival explanation(s) of the non-deterministic theory. Following this line of thought a falsification procedure (Popper, 1959) has been applied, where contradictory valid arguments have been identified for numerous hypotheses. These arguments are hypotheses from other theoretical approaches, where data-based approval of their predictions leads to falsification of the focal hypothesis. The outcome of this falsification procedure is presented in Table 10.

Table 10. Results of falsification with contradictory hypotheses Normative (N) Rational (R) Communicative (C) No. of Testing of hypothesis / Testing with contradictory hypotheses hypothesis (options are “Supported”, “Lack of support” and “Inconclusive”) Lack of support / Lack of Lack of support / Lack of 1 Lack of support / Lack of support support support 2 Supported / Supported Supported / Supported Lack of support / Lack of support Lack of support / Lack of 3 Inconclusive / Inconclusive Lack of support / Lack of support support 4 Inconclusive / Inconclusive Supported / Supported Lack of support / Lack of support 5 Supported / Supported Inconclusive / Inconclusive Lack of support / Lack of support Lack of support / Lack of 6 Supported / Supported Lack of support / Lack of support support 7 Supported / Supported Supported / Supported Supported / Inconclusive Lack of support / Lack of 8 Supported / Inconclusive Supported / Supported support 9 Inconclusive / Inconclusive Inconclusive / Inconclusive Lack of support / Lack of support 10 Lack of support / Lack of support

The results yield similar explanatory power of the normative and the rational approach; whereas only one hypothesis of the communicative approach has been supported. The domain of validity covered by each approach is further addressed in the discussion chapter.

6. Discussion

The results (Figure 15: Similarity of opinions between actors and Figure 16: Association of individuals and groups) have clearly identified two advocacy coalitions which overlap with the sectoral division of the members of the working group. This division was felt by the members of the working group, as they describe the meetings as “it was forestry on the one side, and nature protection on the other; and between them a battle ground (CASA1), and as “a dialogue between forestry and its beliefs on one side, and nature protection and its beliefs on the other” (MCDNP1).

The policy core beliefs of the forestry sector are in line with the “wake theory” (Glück 1982), where all non-timber products and services of forest are provided “… in the wake of regular forestry for timber production (Glück, 1997). Accordingly, the role of forestry in the working group should be “… to keep the forest management as we have it now. Why do we have all this biodiversity in the first place? The answer lies in the sustainable forest management that we have been doing for the last 200 years” (MA1). The same view is shared by scientists from the forestry sector, as “the current forest management regime is good, and we should basically keep it as it is in order to preserve the forest habitats” (FOF1). The policy core belief of the nature protection sector is in accordance with the “environmentalist paradigm” (Glück, 2000a), as “we are …biologists, and we support sustainable development, which means acknowledging economic functions of the forests, but that means doing it with minimum harm to all of the organisms that live in it” (CNMH1). The high level of divergence between these beliefs is evident from the cross-sectoral perceptions, by which forestry is an “…activity where the goal is to create logs and convert them to money. This is the reason behind forestry, and there is no mention that they are here to protect the biodiversity” (SINP3), or that “the forests are priceless, but instead the goal of the forestry is to put a price tag on it – the logs” (CNMH1). The forestry sector has a complementary perception of the nature protection sector, where “…they just want to place Croatia in one big national park or a zoo, and ask for charity for conservation biology” (MA). In all the cases when actors used theoretical concepts to explain their preferences, conservation biology and sustainable forest management where the ones that were used. This basic difference in opinions “…can be traced to the fact that you have one group which has graduated from the Faculty of Forestry, and you have another group which has graduated from the Faculty of Sciences (Biology Department)” (MA1). In this context the forestry education of actor SINP1 explains why he is depicted as a link between the two sectors on Figure 16

(Association of individuals and groups). The same Figure shows that scientists (FOFX, CFRIX, CNMHX, CASAX), identify themselves primary as members of the forestry of the nature protection sector, and not as scientists. This also relates to the reason why their expertise is mostly seen as biased; as they have primarily training in conservation biology or sustainable forest management. This underlying concept from which their expertise stems influences the identity of the focal actor and the perception of others to which of these groups does the focal actor belong to.

Furthermore, in accordance with the predictions of hypothesis 5 of the normative approach, the cross-sectoral perceptions of the state administration agencies were less “extreme” in comparison to the corresponding implementing/expert agencies. One should note that the view of the Ministry of Culture, Directorate for Nature Protection is that “Croatian Forests Ltd. are already managing forests sustainably, and with very little change in the management practices they will comply with all the rules that Natura 2000 entails.” (MCDNP1). The view of the Ministry of Agriculture shows the same pattern in differentiation of opinions within the nature protection sector, as “…when MCDNP, and sometimes even SINP present the findings of those sub- specialists, well in general they talk more mildly, and when they present the findings of those specialists they present them more placidly …a different situation is when these specialists come in person”. (MA2). These differences in presentation of scientific data depending on who is presenting them are in accordance with the previously discussed views of sociology of knowledge (Brickman et al., 1987).

When commenting in general regarding the activities of the working group, the dominant argumentation was policy learning. To explain such scenario, “… in the beginning everyone had an attitude “I have to defend my sector, so I will be aggressive”; but as the time went by we learned that we need to work together, and gradually through hours and hours of discussion we have definitely learned a lot on forestry practice; and I believe that the forestry colleagues have learned plenty on the entire notion of Natura 2000” (SINP5). The setting of the working group provides an explanation of the policy learning – as it represented a “professional forum” where cross-sectoral dialogue was institutionalized and it had strong commitment of its members to make binding decisions. The process itself latest two and a half years – much more than what is usual, it has focused on empirical issues, and no alternative venues for policy formulation were available. The presence of a ‘hurting stalemate’ was also apparent, as the SINP was tasked to come to an agreement with other sectors and make the expert proposal on Natura 2000 before the EU accession; the forestry sector was compelled to cooperate, as SINP would have to make the proposal with or without them. And although this policy learning was identified for nature protection on issues that concern forestry practice, no policy learning occurred on Natura 2000, as “the general position of the forestry was that Natura 2000 and of us implementing it will be the end of the forestry sector. Some progress was made, but very little” (SINP3). One of the reasons for low presence of policy learning on Natura 2000 from the forestry side was the fact that the role of the policy broker (working group leader) was taken up by employees of the State

Institute on Nature Protection, who were regarded by the forestry sector more as stake-holding actors than as policy brokers. Since both the site designation and the management guidelines were priority topics for both of the sectors, the high level of conflict on these issues has decreased the effectiveness of the professional forum; which is in line with the findings of previous research (Sabatier and Jenkins-Smith, 1999; Liftin, 2000). However, the support to normative explanation of policy change (hypothesis N2) is actually complementary to the rational explanation to policy change (hypothesis R2) – as it has occurred only on secondary topics which were means to reach deeper goals. Such outcome places equal weight on the normative and rational explanation to policy change.

Each of the theoretical frameworks had its predictions on the alignment of the actors` policy preferences: from the position of advocacy coalition framework all the members of a coalition would have the same central policy preferences, from the perspective of rational choice all the members of the same organization would have similar policy preferences, and according to the perspective of communicative action the opinions of the members of the working group would be more similar for topics which have more adequate information available. None of the above predictions were confirmed by the data; this greatly diminishes the domain of validity of all theoretical approaches. The explanation of the situation might be found within the rational choice perspective. Vast majority of actual communication (page 144) occurred among the few senior actors, who were also designated by the distribution of Influence codes as the most influential actors. Given the fact that members of the working group have recognized general uniformity of policy preferences on the sectoral level and with the power imbalance in mind, a rational action of an average member of the working group would be to unilaterally transfer the representation of her/his interest to the more influential actor, as “…the argumentation that won was the argumentation of the more influential, more authoritative actors” (CFS1). In this manner a single representation of sectoral interests would be made, and the policy preferences that diverge from the central position within a sector would be kept out of the policy formulation process. These findings also come from the interviewees themselves, as the only actors from the forestry sector who did not say that forestry interests are unanimous. In addition, they are under the assumption that the Ministry of Agriculture and the Croatian Forests Ltd. are not speaking on behalf of the entire sector where one can find the representatives of private forest owners, whose` interests are farthest away from the “central” interests of the forestry sector. A similar logic is applied for actors affiliated to a same organization; the most senior member in the working group acts as a corporate actor and represents organizational interests, while the “junior” ones transfer their activity to the senior ones, and are more free to express their personal policy preferences out of the formal setting of the policy formulation process (i.e. out of the meetings of the working group). Following this logic the argumentation used within the policy formulation process follows the interests of the dominant organizations, and as such, it is not susceptible to change depending on the availability of precise data on the topic.

Decision making on most prominent topics (site designation and management guidelines) was most frequently viewed as a matter of compromise, which goes against the predictions of the rational choice approach that actors will tend to justify their interest by appealing to public interest or to scientific argumentation. Although scientific rationale on these topics was used more by the nature protection rather than by the forestry sector, the director of the State Institute on Nature Protection stated that,

“…compromise is the only right way. You and I know that this situation has to be resolved on the basis of the science, which is conservation biology. So we as SINP and I personally as its director have insisted to act cooperatively towards the forestry sector, to do all the compromises that we are allowed to, because in real life that is the only way how policies are made”.

His view was also shared by the leader of the working group, by stating that,

“…as the representative of SINP it was in my interest to reach a compromise. I am not happy about it. The outcome was a compromise and in some cases it was taken up before the science and expertise” (SINP5).

From the rational choice perspective topic-specific expertise was identified as a valuable resource in the decision making process; as members of the working group have strategically used it to secure their interests. The only two decisions which were “skewed” towards one side of a group were the site designation process and the defining of the management guidelines, both of which fall within forestry expertise. And these are the topics on which actors from the nature protection sector have almost exclusively commented on the strategic usage of information by the actors from the forestry sector. For the issue of defining the management guidelines the “…foresters have recognized our weaknesses early on in the process, and have interpreted forestry definitions in their own selective way, like final cut, forest edge, and other silvicultural definitions, in a way that supports their interests” (CNMH1). “… I was amazed by the argumentation of forestry practice – as they were very confident to make strong argumentation which actually does not hold water” (SINP2). The outcome was that management guidelines for forest dependent species were defined, but for forest habitats they were not. From the point of SINP it was a rational course of action to push for decisions in an area where nature protection has a prevailing expertise (biology of species), and to move to non-decision making in an area where they do not have the advantage (forest habitats). Since it is obligatory to define the management guidelines for birds prior to the accession to the EU, leading the process on defining management guidelines for all groups of forest related species was an easy task for SINP. From the perspective of nature protection the designation of management guidelines was more problematic, as “… time is passing, and EU accession will soon come. There is simply no time to get adequate information to form specific management guidelines for each habitat type, like we did for the species” (MCDNP1). In the case of the site designation process the key resource of the forestry sector that SINP was interested in was the GIS data base of the Croatian Forests Ltd. The best information on forest habitats that SINP had was a map made within the CRO-NEN

93 project in a 1:100 000 scale, which is inadequate for designation of Natura 2000 sites. The data base of Croatian Forests Ltd. contains information from which a much more detailed map of forest habitats could be constructed, which would later on enable SINP to justify the validity of the national proposal of Natura 2000 in the future steps of the designation process. After several months of negotiation, the Croatian Forests Ltd. has agreed to share their GIS information with SINP. As interpretation of this data requires extensive forestry expertise, this situation provided an opportunity to the Croatian Forests Ltd. and to the Faculty of Forestry, University of Zagreb, to form on behalf of the forestry sector their own proposal of forest habitat sites for the protection within the Natura 2000 network. Further development of the site designation process can be best characterized as a negotiation process within the “20-60-80%” practical rule of minimum coverage of protection, as “… it was like playing a chess game, sometimes they won, and sometimes we did” (CUPFOA1). Such perspective was shared by both sectors, as from the nature protection side “…there was a clear trade of an area for an area, and there were no objections to that. All the areas that were chosen were relevant and preserved forest habitats. This can be attributed as one of the successes of the working group, as we were able to reach a compromise within the existing rules for designation” (SINP2). From a political perspective, SINP also had its boundaries of activity set, as

“…. the demand that was placed on us was not to have more than Slovenia did, which was set to 36%. Such are the criteria of our decision makers” (SINP5). This opened an opportunity for policy trade, as “…they have given us the right to say what is what on forest habitats, and that our opinion should be taken up as the relevant one. If this is something that the SINP has given us, well then it is only natural that we should accept their opinion on the sites for large carnivores and birds, I mean the inclusion of areas XXXX and YYYY” (MA2).

Most of the Rules unknown codes came from actors from the forestry sector who had more divergent opinions regarding the nature protection sector than an average forestry actor had, and the codes were mostly related to the overall activities of the working group. Although the “devil shift” was not identified for a specific topic, this indicates that it is present on an individual level from the forestry sector. Such is the case as it is directed towards nature protection and is characterized by perception of SINP as changing the procedural elements of the policy formulation in order to further their interests. This view was shared for all the parts of the forestry sector. In addition, the view of the forestry administration was “…we went there to participate, but I do not expect anything out of the process, because it was organized so that we would talk, but we would not be listened to” (MA2). Comparable points were made by the implementing agency, as “… to put it bluntly, this was just a show, and it will be just as they have previously decided” (CF2). Similar view was shared by the members of the scientific organizations from the forestry sector, as “…rules were not set clearly enough, and a lot of things were not defined properly. The questions that we posed to SINP were unanswered, not answered completely, or not answered in an appropriate way” (FOF1). Following this logic of thought the argumentation of the forestry sector that was accepted is attributed to the agency of the members

94 of the working group from the forestry sector, as …”the whole process began as if there was no political argumentation, but everyone knew that the whole story is political. It seems that things are getting better, because our argumentation was also getting accepted; however this was done under our pressure and not by the ones that have led the process…they had the interest of us nodding our heads to their starting argumentation” (CFRI3). Even the more moderate position of the state nature protection administration is seen as strategic action as

“….this is the way they do it…. the Ministry looks like they hate SINP for being extreme, say that they do not agree with their opinions; but SINP is just their expert extension, and they do what the Ministry tells them, and the Minister signs. SINP does their dirty work, which is the way it works” (MA3).

However, since majority of the hypotheses of the rational approach were not validated by the data, perhaps it is more prudent to look at them as a part of a broader division of values and beliefs, as when it comes to key issues

“…a compromise has been made, and no one is happy about it. That is the reason why all this tension remains. Foresters still think that nature protection is rushing into something they do not understand, do not want to listen, nor do they want to look at the consequences. Nature protection still thinks that we will do as we like, and that they cannot change anything in practice. And in a broader picture, nothing changes in the long run” (SINP3).

As stated on page 80, the usage of scientific rationale as basis for decision making was more frequently coded in the nature protection than in the forestry sector, within which it was least frequently used among its “stake-holding organizations” (Croatian Forests, Forest Extension Service, Croatian Union of private forest owners` associations, Alliance of private forest owners associations). This is an expected finding as the site designation process has to be made exclusively on scientific argumentation, and SINP is responsible for the implementation of the Natura 2000. The decisions were not based on consensus (hypothesis 1), the actors did not have equal availability of information (hypothesis 5), members of the working group did not have shared meaning on the topic of discussion (hypothesis 6), and all of the abovementioned was enabled by unclear procedural aspects of decision making (hypothesis 9).

Although decisions were not based on consensus, with the explanation from the rational choice approach that a part of the members of the working group have transferred their agency to a smaller group of more influential actors, it was not needed to ask for consent from all the members of the working group; the newly created norm of decision making requires it only from a limited number of its members. This rule originates “…from the manner by which nominations were given – all organizations will have a representative and his deputy/deputies. Under such condition, every organization would have one senior, and the acceptance of the working group by the forestry sector is reflected in the high-ranking people who they have sent” (SINP5). General agreement with the decisions that were made is reflected in the fact that there was only

95 one instance when an actor (Ministry of Agriculture) has not formally agreed on a decision (management measures for Western Capercaillie). This situation where “…there was almost no formal separate opinions shows that all of the claims have been harmonized and that we went for a compromise” (SINP5).

The differences in the availability of information between the members of the working group for a certain topic are most pronounced with the lack of information on Natura 2000 among the members of the forestry sector; as from their perspective “…we did not know that the site designation should be based on scientific criteria. We found this out only after more than half of the discussion has passed. Someone should have said that” (CF2). This lack of information on Natura 2000 is contradicted with the finding that overall scientific expertise on Natura 2000 (hypothesis 8) was marginally different between the sectors. An even more compelling contradictory argument was the fact that most of the senior members of the working group have previously participated in projects related to Natura 2000:

“…a lot of material on Natura 2000, even translated, was sent by-email to all the members of the working group before the first meeting; so they have been informed, especially since we repeated many things during the meetings. How much were they reading and listening…. I am not getting into that. And now they are saying that they became aware of the rules somewhere after the middle of the talks…. I think they were aware of the rules much before and that this is a matter of human nature” (SINP7).

Another contradictory finding in regards to the lack of information on Natura 2000 is that the frequency of socio-economic argumentation on the site designation topic was not reduced at the second round of interviews, after they had learnt that the decisions should be based on scientific argumentation. This indicates the strategic behavior of the members of the working group coming from the forestry sector. However the dominant comment on the “rules” of Natura 2000 at the second round of interviews with the members of the forestry sector was not the availability of information; rather it was “….the way SINP was interpreting the information on Natura 2000, and I am afraid of that interpretation as it is not Natura 2000… they are interpreting just one part of it, and that is protection that just limits. Natura 2000 allows sustainable usage of natural resources, and they are no seeing that” (MA1). The background, either conservation biology or sustainable forest management, has led to a lack of shared understanding on what Natura 2000 stands for, and these differences in values and the norms that actors have internalized during their professional development have systematically distorted communication within the working group. When commenting on the communication during the meetings, the interviews have recognized these elements as,

“…the main problem in communication is that it is not sincere enough. I would, personally, love… if the representative of the Ministry of Agriculture or of the Croatian Forests Ltd, would say to us: look, I am on the market. I need to keep 10 000 people employed, and I bring money to the state. I understand that we need to preserve some forests, so let us see how much it costs, and

96 see what we can do. But that is not the position that they bring to the table… they are saying that there would be none of these birds and your protection areas if it was not for us, who have been doing all of this protection for hundreds of years now” (SINP7).

The position of nature protection is similar as “…understanding between foresters and us is difficult, because we, like foresters, miners and others, know what we know and we keep on defending too eagerly and without proper argumentation the arguments that we should not be defending” (SINP3).

And if for the site designation topic the only admissible argumentation can be the scientific one, then how can the majority of arguments be characterized as biased? The reason behind this is that,

“…if we accept that all that we have done is based on science, then from which science did it come from? And what is scientific argumentation? Well, no one has explained that to me. Everyone had different definition of what science is, how it can be used, and which one should be used….we have talked a lot about this in the meetings, but these things were never properly defined” (CF1).

Similar perspective comes from the nature protection sector as “…what does science means? There is no one science in nature protection. There is a range of science, coming from the Faculty of Agronomy, Faculty of Forestry, and Faculty of Science, and they cannot agree among each other…it is very difficult to look at more things at once” (SINP3). The conflict on the management guidelines for the Western Capercaillie was also rooted on the definition of what is adequate scientific argumentation as,

“…usually, each side had its own interpretation from its own professors; and we had ours from the faculty professor who did a lot of research on the Western Capercaillie. However, it was just disregarded as invalid, and the reason is that they do not like his attitude on the mouflon management… how can we converse in such a manner when they defeated our research without scientific argumentation. What is more, in parallel they take as relevant scientific information the estimation of bird populations from the Academy, that just looks up in the sky and says that the estimate is 100 000 – 500 000” (MA5).

There are numerous statements like the one above, all of which are characterized as non- scientific argumentation which is contrary to the opinions of the focal actor, and which justify the non-acceptance of confirmatory findings in an off-topic argumentation. It is beyond this research to analyze the validity of different claims on the management of Western Capercaillie; nevertheless, it was also something that the working group did not do. Accepting the limitation of a “real-life” policy formulation process (Lindblom, 1959) and having eleven meetings is not nearly enough to formulate any decision in a rational comprehensive way, where the validity of all claims is checked, and all the important values, alternatives and outcomes are addressed. However, the focus of the discussion was not on finding a common ground of expertise; instead

97 it was aimed at compiling additional information which supports the original claims. The outcome of such discussion can only be a compromise solution, and not a consensual decision based on mutual understanding of the issues. As argued in the section on the normative approach, a joint understanding (policy learning) was only made possible on specific secondary topics (limiting final cut and presence of deadwood) after many hours of discussion on forestry practices. On more complex issues such as site designation an understanding would require much more discourse than a working group could provide. Given the fact that the working group is only one small step in the implementation of Natura 2000 in Croatian forestry, in the long run, a series of successive cross-sectoral collaborations may lead to such a development.

This chapter has demonstrated that the most prominent argumentation comes from the “more central” organizations, and that the most important decisions were based on compromise. It also showed that the more “influential” actors played a bigger role in the formulation of decision than the “junior” actors did. However, none of the theoretical approaches could completely explain the alignment of policy preferences. Other important issue is the same level of validity of the normative and the rational explanations to opinion change (hypotheses 2). The explanation of the rational approach on alignment of policy preferences suggests the importance of organizational power. Different mechanisms of opinions change, the role of power relations, meaning of “more central” organizations and individuals, their roles, and the precise conditions that led to the compromise decisions are all addressed in detail in the following chapter.

CHAPTER IV NETWORK PERSPECTIVE ON THE FORMULATION OF NATURA 2000 FOREST POLICY

1. Summary

Analysis of Natura 2000 transposition processes in many EU member countries from Chapter II has shown that they were not based just on science; rather they were more characterized as a policy formulation processes, where stakeholders’ power relations and interests play an important role. Chapter III has demonstrated the same pattern in Croatia, as the expert working group on Natura 2000 in forestry has based its most important decisions on a compromise between different stake-holding actors. This chapter focuses on the power and influence relations between these actors, both on inter-personal and inter-organizational level.

Inter-organizational relations are framed in the resource dependence perspective, and the inter- personal relations are examined through network models of social influence. The impact of these two levels on the dynamics of the working group is analyzed by the application of the social network analysis.

The results show strengthening of cross-sectoral ties within the working group, but also show that most of these relations occurred between members of the administrative and the scientific organization, whereas the role of actors from more typically stake-holding organizations was less constructive for the cross-sectoral dialogue. Significant impact of inter-organizational power relations onto the inter-personal relations within the working group was evident. Results also indicate that the inter-personal influence relations have affected decisions of the working group. However the co-evolution model of influence relations and the opinions did not show a significant effect of influence relations on opinion change, which provides an opportunity for alternative explanations as the drivers of the policy formulation. Several segments of the research point to alignment of actors in the working group according to their general policy beliefs, and to the usage of scientific argumentation.

2. Introduction

The results of the working group on forestry represent the current level of transposition of Natura 2000 in the forestry of Croatia. Chapter III has shown that their decisions were mostly based on compromise, and that the most prominent argumentation came from “more central” organizations. Alignment of policy preferences could to a certain extent be explained by the actors` normative standpoints, but no theoretical approach could provide clear explanation of the change in policy preferences; however both the normative and the rational perspective stipulate the importance of “actors more central in the coalition” and the “more powerful” organizations and individuals. These findings are the basis for the formulation of a (sub) research question for this chapter, which will contribute to answering the overall research question. The question for this chapter is:

What is the role of power and influence relations in the formulation of Natura 2000 forest policy in Croatia ?

This study follows the activities of the working group from the position of social network analysis (SNA), where a methodological overview of the Chapter is presented by Figure 20.

INPUT NETWORKS OUTPUT MODELS

THEORY TIES NODES MODEL OF TYPE

ORGANIZATIONAL CONTEXT Resource dependence Resource flows perspective & power Organizations (Pfeffer and Salancik, 1979)

Friedkin and Opinion change Johnsen`s (1997) model of Comparison from time 1 to time 2 opinion change Comparison between levels

Stochastic actor- Dynamics of network / based models network and behavior (Snijders et al, WORKING GROUP 2010)

Friedkin`s view Influence & (2011) communication Individuals on social influence

Figure 20. Methodological overview of Chapter IV

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Figure 20 shows how the working group is seen as a network of inter-personal relations between its members, embedded in a larger network structure of inter-organizational relations. Principal data was gathered by the use of questionnaires at two time points (network panel data), while supplementary data was gathered by non-participant observation of seven working group meetings. The first data collection point represents the beginning of the research, and the second data collection occurred after the working group ended its decision making process. Corresponding to these two network levels, the influence of inter-organizational relations and the influence of inter-personal relations on the policy formulation were analyzed.

The inter-personal relations are primarily seen as networks of inter-personal influence and communication, following the work of Friedkin (2011) on social influence processes. The inter- organizational relations are primarily seen through theoretical framework of resource dependence (Pfeffer and Salancik, 1979) and its power relations. The inter-personal and inter- organizational level intersect at the level of the working group which is the primary unit of analysis, and the social influence theories and organizational power relations have their theoretical intersection on the decision-making power (Dahl, 1957) over the formulation of Natura 2000 forest policy in Croatia.

Firstly, the inter-personal and inter-organizational relations have been analyzed separately by cross-sectional network analysis. Secondly, the changes from the first to the second data collection point for both network types have been analyzed, as well as the relations between the two network types. Furthermore, both networks on individual and organization level have been utilized in the Friedkin and Johnsen`s (1997) model of opinion change, by which their relation to the policy formulation (i.e. outcome opinions) has been determined. As a final step of the analysis, longitudinal SIENA network models (Snijders et al, 2010) have been constructed to assess whether influence and opinion changes have their own internal dynamics, how they interact with one another, and how they respond to external variables, such as division of organizations that have members in the working group on the forestry and nature protection sector. These models are based on inter-personal relations, and the organizational context in them is presented through several variables.

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3. Conceptual basis

3.1. Social network analysis

There are many definitions for social network analysis. According to Marin and Wellman (2011) “[s]ocial network analysis is neither a theory nor a methodology. Rather it is a perspective or a paradigm. It takes as its starting point the premise that social life is created primarily and most importantly by relations and the patterns they form”. The defining properties of this research paradigm are (Freeman (2004):

 It involves the intuition that links among social actors are important  It is based on the collection and analysis of data that records social relations that link actors  It draws heavily on graph imagery to reveal and display the patterning of these links  It develops mathematical and computational models to describe and explain these patterns

SNA can be also defined as “… (1) a method for analyzing the volume and patterns of social relations linking individual actors to each other and (2) a way of theorizing social structure and its effects on behavior” (Bond and Harrigan 2011). This definition stipulates the importance of social structure and of its impact on individuals, which coupled with focus on middle-range theorizing and usage of empirical testing can put to some extent SNA close to the Mertons` view of structural functionalism (Merton, 1996). Social structure is also important in Wellmans` (1988:20) definition of SNA, by which it is ”… a comprehensive paradigmatic way of taking social structure seriously by studying directly how patterns of ties allocate resources in social system”. This definition also emphasizes the focus on relations; in SNA at least one important variable must be described in relational terms (Marin and Wellman, 2011). The notion of relation as a fundamental unit of social analysis was later on described as the “anti-categorical imperative by Emirbayer and Goodwin (1994). This puts SNA to close relation with “The New York School of Relational Sociology” and its critique of the dominants “substantialists” approaches to social analysis (Mische, 2011). According to its manifesto (Emirbayer, 1997), the relational analysis on macro-level views society (or its macro structures such as nations states) as “…a patterned matrix of institutional relationships among cultural, economic, social, and political practices”. On a meso-level the interactions among individuals are conceptualized as series of recurrent mechanisms and patterns, which is in line with what Goffman (1967) calls “copresence”. On a micro-level the individual is defined by its “circles of recognition”, which can be cultural, fantasized and social (Pizzorno, 1991). The manifesto explicitly states SNA as the best way to study social structure from a relational perspective. Accordingly, the macro-level analysis can define states through their position in global trade networks (Snyder and Kick, 1979), world polity can be defined as a two-mode matrix of states and inter-governmental organizations (Beckfield, 2008), or a city`s capacity to affect community policies can be analyzed through the power structure of multiple elite networks (Laumann and Pappi, 1976). On a meso-level the

102 distribution of decision-making power within a clan can be observed through kinship and economic networks (Greif, 1994), a group-decision making can be viewed as multiple networks of interpersonal influence (Friedkin, 1993), or animal population can be characterized as differentiated social organization, with multiple forms of social behavior in each layer (Blumstein and Armitage, 1998). On a micro-level a persons` social capital can be defined by her/his multiple ego-networks (Lin, 1999), identity change can be attributed to characteristics of brokerage, homogeneity and prominence of an ego in a larger network of peers (McFarland and Pals, 2005), and similar causal mechanism may explain the emergence of deviant behavior (Warr, 1993).

By taking into account network positions, rationality is longer the dominant causal factor of social action; rather it is on the differences in the available opportunities to define what rational action entails. In this context network positions form commitments that alter the calculus of rationality (Granovetter, 1985; Uzzi, 1996). Social network analysis has also been seen as a preferred way to deal with “macro” sociological concerns in symbolic interactionism (Fine and Kleinman, 1983), or the analytic solution for relational realism, which rejects the agency/structure dichotomy (Somers, 1998).

There is also a strain of social network analysis that uses qualitative approach (Hollstein, 2011), which is in line with the “interpretative paradigm” (Hollstein and Ullrich, 2003). The postulates of this paradigm are that social reality is constructed, that it is shaped by social meaning and is tied to a social location (depends from a certain point of view), and that it is always dynamic. The methodological positions that relate to the interpretative paradigm are symbolic interactionism, sociology of knowledge, phenomenology, ethnomethodology and constructivism. These kind of approaches are used when little is known on the object of inquiry, such as embeddedness of firms in a network (Uzzi, 1995), networks of migrants (Wong and Salaff, 1998) or mobility of junior researchers (Scheibelhofer, 2009). These approaches are also used in analyzing network practices, such as cooperation and interaction patterns in innovation networks (Franke and Wald, 2006), cultural practices among the Italian renaissance nobility (McLean, 1998), or the communication mechanisms in Brazilian youth organizations (Mische, 2003).

The origins of social network analysis can be traced to Simmel`s “formal sociology” (Simmel, 1896; Coscer, 1977), and Moreno`s (1934) “sociometry” and “sociograms”, that visually represented social networks with points and lines. A major advance for SNA was marked by Harrison White (1963) and his initial usage of algebra to represent kinship structures, who later focused on algebraic representations of social positions and roles (Lorrain and White, 1971, Boorman and White, 1976, White et al, 1976). Other important applications of SNA at that time were Bearden`s (1975) development of centrality to explore power and influence of banks in the American corporate world, and the investigations of Fischer (1975) and Wellman (1979) on the community structure. Since then SNA has spanned into many different fields, such as policy

103 networks (Bond and Harrigan, 2011; Knoke, 2011), criminality and terrorism (Carrington, 2011; van der Hulst, 2011); the world political economy (Kick et al, 2011), cultural, scientific and scholarly networks (DiMaggio, 2011; White, 2011); economics (Goyal, 2011), geography (Johnston and Pattie, 2011), the impact of peers on attitudes and behavior (An, 2011), and even animal networks (Faust, 2011).

Social network research has its own theories, such as network exchange theory (Cook et al, 1983; Markovsky et al, 1988; Borgatti and Everett 1992 ), strength of weak ties theory (Granovetter, 1973), Burt`s (1992) structural holes theory of social capital and the small world theory (Milgram, 1967; Milgram and Travis, 1969). The work of Jacob Levy Moreno on sociograms had inspired developments in graph theory (Harary and Norman, 1953; Harrary et al, 1965), which is the formal basis of SNA. Graph theory is a set of axioms and deductions, and in a context of SNA social actors are represented by points, and the relations between them are presented by lines. Every sociogram has its corresponding square matrix (sociomatrix), in which cells represent presence or absence of a social relation between the actors. Sociomatrices can be analyzed through matrix algebra, which is of great importance especially to large networks. Social relations between actors can be recorded as a non-directed or directed, dichotomous (present/absent) or valued, they can be positive or negative, and even multiple. Actors can be all of the same type, or they can be of two-different types (two-mode network –i.e. individuals and the companies they work for).

Basic parameters that network analysis can measure are the overall “density” (Hanneman and Riddle, 2011) of the network, and various measures of relative “centrality” (Freeman, 1979; Bonachich, 1987) of points within it. Centrality is usually used as an indicator of power (Mizruchi and Potts, 1998), influence (Ibarra and Andrews, 1993), popularity (Farmer et al, 1996) and prestige (Russo and Koesten, 2007). Other analytical techniques include grouping of actors into different cohesive subgroups (Moody and White, 2003), and of these groups’ relations to each other which allows for the analysis of brokerage roles (Gould and Fernandez, 1989).

Another important mathematical input is the matrix based algebraic positional approach, so called “blockmodelling” (Breiger et al, 1975; Batagelj, 1997), by which social positions of network actors are identified based on similarities in their structural properties. In addition collecting network data has its unique validity (Tracy et al, 1990), reliability (Feld and Carter, 2002; Borgatti et al, 2006) and ethical issues (Kadushin, 2005; Borgatti and Molina, 2008). Other approaches include the straight-forward (random) sampling and statistical procedures relying on random samples which cannot be employed, as the assumption of independence of observations does not hold true. The sampling (Laumann et al, 1983; Frank, 2011) and statistical procedures (Marsden, 1990) have to be adjusted to network data, where the assumption of the interdependence of the data is the basic reason for doing SNA. The well-developed statistical

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procedures include the so called exponential random graph (also: p*) models (Wasserman and Pattison, 1996; Lusher, Koskinen and Robins, 2013), which resemble logistic regression models, and they explain global network structure from prevalence of local structures. An overview of the types of ties to which all these analyses were applied to is presented in Table 11.

Table 11. Typology of ties studied in social network analysis. (Borgatti et al, 2009)

Similarities Social Relations Interactions Flows Location Membership Attribute Kinship Other role Affective Cognitive e.g., e.g., e.g., e.g., e.g., e.g., e.g., e.g., e.g., Sex with, Information, Same spatial Same clubs, Same Mother of, Friend of, Likes, Knows, Talked to, Beliefs, and temporal Same events, gender, Sibling of Boss of, Hates, Knows Advice to, Personnel, presence etc. Same Student of, Etc. about, Helped, Resources, attitude, Competitor Sees as Harmed, etc. etc. of happy, etc. etc. As

The 1990s were marked by strong entrance (or invasion) of physicists in SNA, which began with Watts and Strogatz` (1998) inputs on dynamics of “small world” networks and by Barbási and Albert`s (1999) examination of “power law” distributions of degree centralities; however, these scientists and the ones inspired by their work did not join the SNA collective deriving from the field of social sciences (Scott, 2011). Another stream of recent developments in SNA are the computational models which explore the structural transformation of network based on individual decision making (Snijders 2001, 2005) and tackle the issue of agency in network analysis, which is one of the challenges of SNA (Emirbayer and Goowdwin, 1994). These models are elaborated in the subsequent chapters.

3.2. Inter-organizational relations

The purpose of this chapter is to provide an introduction into prospective theoretical frameworks that guide inter-organizational research, with a focus on resource dependence perspective. Since organizations typically constitute policy networks, the chapter also provides an overview of formal network decision models that are applicable to policy research.

A good overall indication on the inter-organizational studies was provided by Oliver and Ebers (1998), who performed a meta-analysis on 158 articles in the field. They found that most dominant theory guiding papers employed the resource-dependence perspective (28%, followed by network theory – 25%), that 89% of the papers used empirical and 74% quantitative methods, that most of the studies (62%) used multiple organizational ties, that majority of the studies analyzed flow of immaterial resources (65%, followed by flows of material resources-47%), and that the most frequent outcome of the analysis was power (31%), followed by success (23%).

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According to Mizruchi and Galaskiewitz (1993) there are three dominant perspectives for the study of inter-organizational relations:

 The resource dependence framework The first usage of the resource dependence framework was in a series of articles edited by Zald (1970), but the most important contribution to the development of the framework was by Pfeffer and Salancik (1978). The framework sees organizations operating in an uncertain environment, and in order to reduce that uncertainty they attempt to control critical resources from the parts of environment that they can perceive. These critical resources are controlled by other organizations, and there are three main strategies to secure them: cooptate the source of dependence, create leverage ties, or make alterations dependent on the focal organization. Pursuing these strategies changes the network status and thus may constrain subsequent behavior of the focal organization. Although early studies have focused on an individual organization, most of the later research has focused on interorganizational networks (Rogers, 1974; Benson, 1975; Stern, 1979; Boje and Whetten, 1981).

 The social class framework The framework stems from the work of C. Wright Mills. He was one of the few exponents of Marxists sociology in the USA of his time, and his book The Power Elite (Mills, 1956) depicted how the United States were dominated by a small group of businessmen, politicians and military leaders. The framework focuses on linkages between companies, foundations, policy-making groups and country clubs and governmental agencies, as well as on their influences on shaping public policies that focus on securing the interest of the upper class. The perspective was further developed by Domhoff (1967) and Zeltin (1974), where subsequent studies focused on disproportionate power of banks (Mintz and Schwartz, 1985), influence of class-based groups on corporations (Ratcliff, 1980), and on the role of interest groups and family holdings (Scott, 1987).

 The Institutional framework The Framework was developed by DiMaggio and Powell (1983), and places emphasis on the cultural systems, where institutions and organizations apply normative, mimetic and coercive isomorphic activities to comply with dominant laws and traditions. In this way the power of the state and dominant subcultures permeate organizational decision making, thus resulting in increasing homogenization of organizational behavior. These arguments were further on addressed by Carrol et al (1988), Galaskiewicz (1985) and Flingstein (1990).

In the 1970`s the resource-dependency model based on exchange relations was a prospective theoretical framework on inter-organizational relations (Thompson, 1967; Aldrich, 1974; Benson, 1975), where Cook (1977, p.64) has defined exchange relation as: “…voluntary

106 transaction involving the transfer of resources between two or more actors for mutual benefit”. The same article defines an inter-organizational field (Warren, 1967) as a network of exchange relations among its member units or organizations, and defines inter-organizational power as imbalance in exchange relation. The basic premise of the perspective is that due to “…scarcity of resources, organizations seek to reduce environmental uncertainty by creating “negotiated” environments” (Cook, 1977; p.5). Organizations that are in the same category in a negatively connected network typically compete for resources (commensalistic competition) when there exists scarcity of resources in the environment. Actors in different exchange categories (when their resource needs are complementary) are more likely to form cooperative exchange relations in positively connected networks (symbiotic cooperation).

The main contribution to the perspective is the book ‘The external control of organizations’(Pfeffer and Salancik, 1978), according to which organizational effectiveness is challenged by its environment. Organizational environment is basically everything outside the organization, but the organization may perceive only a part of it. Organizational environment constrains the behavior of the focal organization, and it is a cause of uncertainty. Organizations try to decrease the uncertainty of their activities by securing intake of critical resources, which usually leads to increasing organizational interdependencies and thus similarity in behavior and in goals (a similar mechanism to institutional isomorphism). Effectiveness is a construct external to organizations, and it relates to how much the focal organization is meeting the needs of other social actors; it is proxied by social legitimacy from the account of its external stakeholders. An imbalance of inter-organizational resource dependencies does not equate the usage of the full potential of power, as its direct usage (influence) is affected by the visibility of the focal organizations` behavior to the influencing organization. Moreover, it is affected by the discretion possessed by the focal organization and by the influencing organization over non-compliance to the demands being made, which is based on affecting legal or other social constraints. Organizations apply different strategies to avoid resource dependence. These strategies are:

 Buffering; with unstable input they develop big inventories, and with unstable output they develop long-term contracts  Control the input/output stability; by controlling rules of the trade (regulation, cartels)  Control (take over) the organization related to the input/output  Diversification of organization; in the long run the best strategy

Other organizations also attempt to constrain the behavior of the focal organization for their purposes. An organization may apply several strategies to counter these control attempts, and they are: antitrust suits, cooptation, acquiring countervailing control or otherwise regulating control, and limiting usage of inter-organizational power by socialization of executives. Although resource dependence perspective draws heavily on Emerson`s (1962) exchange theory it does not differentiate between power imbalance and mutual dependence, which might have

107 opposite effects on the adsorption of constraints (Casciaro and Piskorski, 2005). Main usages of resource dependence framework include:  Studies of effects of environmental constraints on organizational decisions and how organizations manage these environmental constraints (Pfeffer and Salancik, 1974; Salancik, 1979; Christiansen and Bower, 1996; Mizruchi and Stearn, 1988; Finkelstein, 1997; Schuler, Rehbein and Cramer, 2002)  Effects of environmental constraints on internal dynamics of organizations (Ocasio, 1994; Hambrick and Mason, 1984)

Despite the popularity of the perspective, “…there is a limited amount of empirical work explicitly extending and testing resource dependence theory and its central tenets” (Pfeffer and Salancik, 2003: xvi), and due to a high level of ambiguity, it might be stated that the perspective is “…more of an appealing metaphor than a foundation for testable empirical research” (Casciaro and Piskorski, 2005). The basic critique of RDP is that it does not take into account geography, i.e. the physical location of inter-organizational relations (Kono, Palmer, Friedland and Zafonte, 1998:865), that it does not take into account social class (Palmer, 1983), or even that it is no more relevant due to the power structure of financial markets and an increasingly boundaryless production process (Davis and McAdam, 2000). Given the fact that up to the printing of the second edition of “The external control of organizations” in 2003, it was cited 2321 times with a growing trend of citation the resource dependence framework is still a mainstream inter- organizational theory.

Although all of the three mentioned frameworks have different foci, there is a sizable overlap between them; the studies on the political interest groups (Laumann and Knoke, 1987; Mizruchi, 1989; Clawson and Neustadtl, 1989) which take on the perspective of resource dependencies, are strongly influenced by the social class perspective, and also could be seen from the institutional perspective as organizations co-opting political actors which represent generalized belief systems. It could also be stated that inter-organizational networks operate to influence social definitions which then shape the organizational behavior, which is an underlying mechanism both in the social class and in the institutional perspectives (Mizruchi and Galaskiewicz, 1993). All three approaches also put emphasis on power relations.

In organizational research, power has been defined as the ability of an actor to overcome resistance in achieving a desired outcome (House, 1988; Pfeffer, 1981), or as the ability to affect outcomes (Mintzberg, 1983; Salancik and Pfeffer, 1977). This is to a certain extent different from the position of Wong (1968) who differentiates potential power and actual power, but according to the more salient perspective on the general decision making “first face of power” (Dahl, 1957), power is equated with influence, stating that unused potential power is not power. Cook (1977) relates centrality to organizational power, especially closeness (for avoiding the

108 control of others) and among centrality (for possibility of increasing the dependence of others on the actor). Regardless of the specific operationalization on power, Pfeffer (1981) argues that complete understanding of it in organizational analysis requires attention to both micro (behavior) and macro (structure) level of analysis. The same author advises the usage of the term “influence” rather than “power” as “power” frequently has negative connotations. Following this line of thought was used by Cook (1977), Brass (1992) and by Burkhardt and Brass, (1990).

Network of formal organizations often may be fruitfully regarded as a policy network, which is a bounded set of actors and one or more sets of relations that connect these actors (Knoke, 2011). A closely related concept is a policy domain, which is socially constructed by the mutual recognition of its actors who take into account each other’s preferences and actions (Laumann and Knoke, 1987). Examples of policy domain are agriculture, education and welfare. A policy domain “…delineates a bounded system whose members are interconnected by multiple policy networks” (Knoke, 2011, p.211). However, the theoretical rigor in policy network analysis is not as developed as the formal methods for its data analysis (Raab and Kenis, 2007). These formal network decision models mostly use matrix algebra and assume that collective outcomes involve exchange of resources among its actors. They also focus on power relations among its actors, where the more powerful actors use their political resources to affect the actions of the less powerful actors. Some of the formal network decision models are (Knoke, 2011):

 Social influence models The purpose of these models is to show how actors mutually shape each other`s beliefs and actions. Friedkin (1984, 2004) developed a deterministic, discrete-linear model in which actors` preferences are altered based upon the interpersonal influences of other actors in which he/she is in direct contact with. All changes in opinions occur simultaneously, and are partly based on the network of interpersonal influences, and party on the factors that formed the initial position.

 Collective action models Developed by James S. Coleman (1973), and they describe legislative vote trading, where legislators trade their votes on an open market, and they have perfect information on the policy preferences of other legislators. The legislators trade in their support to another legislator on a policy that is more important to the other legislator and vice versa. All exchanges happen simultaneously, and the model yields prices (power) of actors over event outcomes.

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 Network access models Marsden (1983) modified the Coleman`s model by restricting the scope of exchanges from all legislators to its subset, which is defined by the compatibility of interest between legislators on a dyadic level. The compatibility is based on trust, ideology and party loyalty. Simulations of the model reveal redistribution of power to the actors in most advantageous network positions and possible shifts to a more efficient system.

 Dynamic policy models These models are designed to address the mechanisms by which interest groups influence the collective decision making. The models differentiate actors (e.g. interest groups) from agents (e.g. public authorities with decision making rights) in a national policy domain, with network structures built into the interest component (Pappi and Kappelhof, 1984). The power of actors comes from its ability to gain access to effective agents, either by deploying their own policy information or by mobilizing the agent`s information. Application of the model on the U.S., German and Japanese labor policy domain networks (Knoke et al, 1996) found the model fitting to the empirical data. This study also depicted large power being held by public authorities who played both the roles of actors and agents; the power stemmed from their high level of self-control over policy relevant information sought after by other policy actors.

 Dynamic access model The model describes decision making as a two-step process; first actors define their preferences on a policy event, which are influenced by the preferences of other actors to whom they have network ties, and secondly public officials vote based on the policy preferences that were defined in the first step. Variables that affect the event outcomes are control over events, actors` resources, access to other actors, interest in the event, salience of event decision and the voting power of the public officials (Stokman and Van den Bos, 1992, Stokman and Van Oosten, 1994, Stokman and Zeggelink, 1996; Thompson et al, 2006). In application of the model on 10 policy decisions in Amsterdam (Stokman and Berveling, 1998), it was found that the chosen strategy among actors was to focus their attention to influence other actors which they find most similar to themselves; as in this manner they would have high chance of influencing others, and would not risk changing their own preferences while trying to influence relatively inaccessible, powerful actors.

This research utilizes as theoretical framework the resource dependence perspective, within which decision making process of the Natura 2000 is analyzed through the Friedkin`s formal models of social influence. Overview of both the theory and the formal models of social influence are presented in the subsequent chapters.

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3.3. Network models of social influence

The first contribution to the social influence network theory (Friedkin and Johnsen, 2011) was done by Friedkin (1986), where he built on French`s (1956) formal theory of social power. According to French`s theory, opinions are mainly consequences of interpersonal influences. Actors are embedded in a static power structure (represented by an adjacency matrix) that describes dyadic opportunities for communication which influences opinions of individuals (influential communication). The communication is also described by a static influence structure and the outcome opinion of a focal actor is the mean value of the actor`s own opinion and of all the ones who he/she was communicating with (governed by opportunities to communicate, i.e. by the power structure). French did not examine the power-influence relation in detail, and have just stated that the power structure constrains the opportunities for influential communication. According to French’s model the opinions in each connected component of the network must converge to one joint opinion over time; the model does not allow opinion differences to remain, unless in disconnected parts of the network. By excluding possibilities of influence without direct communication and direct communication without influence, Friedkin (1986) in his linear model had focused on social influence, and had attributed weights to opinions of alters, where all actors simultaneously change their opinion at each point in time. The process ends where future influential communication does not have any additional effect on opinion change. This first Friedkin`s model was embedded in social power structure, where the possibility of influential communication was described in probability terms. At that time there was no conceptualization of the weights of alter`s opinions. The weight that would represent the strength of an interpersonal tie was conceptualized later on (Friedkin, 1990), as a three-step Guttman scale consisting of discussion, help seeking and friendship. The basis of a network model in which opinion is influenced by weighted exogenous conditions and endogenous influences was formally presented by Friedkin and Johnsen (1990) and in a simplified form it was for the first time experimentally applied the same year by Friedkin and Cook (1990). The application consisted of three increasingly complex models subjected onto 50 groups of students, each of which had four members and controlled flows of communication; and depending on the discussed issue, the correlations between the predicted and the observed values were between 0.45 and 0.76. The model was formally expanded by Friedkin and Johnsen (1997), where it was used to conceptualize structural equivalence in influence networks. However, this model used referencing to Blau-Space (McPherson and Ranger-Moore, 1991) for exogenous variables, and there was no explanation on the operationalization of endogenous interpersonal influence.

The variables of the social influence network theory have been previously operationalized by Friedkin (1993) when he applied a longitudinal model of interpersonal influence to analyze opinion change among 23 elementary school teachers who had to develop criteria for the evaluation procedure of the schools` performance. However the analysis was done on the dyadic

111 level, where independent variables were regressed against interpersonal communication and influence. This model had two waves; it used the previously developed Guttman scale (of friendship implied in advice seeking and frequent discussion, advice seeking implied in frequent discussion, and of frequent discussion; Friedkin, 1990), as a structural base of interpersonal influence together with French and Raven`s (1959) bases (reward, coercive, legitimate, referent and expert) of social power. It also had issue-related interpersonal communication as the intervening variable. The most fitting model explained 47.5% of the variance in interpersonal influence. The same model was used by Freidkin and Johnsen (2002) as a generalization of Williamson`s (1971) model of control loss in hierarchical chain-of-command within organizations, where orders and information get increasingly distorted with the length of the chain (Fayol, 1949). The next year social influence network theory was in a similar vein linked to the affect control theory and the expectation states theory by Friedkin and Johnsen (2003), where the network influence theory was extended with feedback loops from the positions of group members onto the network. All these papers have contributed to the Friedkin and Johnsen`s (2011) book Social influence network theory, which sums the findings from all of the above mentioned body of knowledge. However, none of these studies have jointly applied the full Friedkin and Johnsen`s (1997) model of inter-personal influence combined with its longitudinal operationalization (Friedkin, 1993). Details of longitudinal operationalization of social influence, basic formal elements of the Friedkin and Johnsen`s (1997) model as well as an example of its application are presented in the chapter Methodological approach.

Inspired by social influence network theory, Moody (2001) has developed recursive neighborhood mean algorithm to search for dense regions in large simulated and empirical networks, which show a structure of small world networks. However, his model is a simplification of the Friedkin and Johnsen`s model which is very similar to the French`s (1956) formal theory of social power, with the difference of being longitudinal and accommodating multiple opinions. Costa and De Matos (2002) have also simplified the Friedkin and Johnsen`s model by allowing just ±1 values of attitudes for an issue within organizational formal and informal communication channels in order to analyze how the attitudes change in relation to initial attitudes, network of interpersonal influence and the degree of participation.

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3.4. Models of network dynamics

Practically all models on network dynamics require some variation of the Markov property (defined for stochastic processes) which expresses that the future depends on the past only via the present; i.e. situation at T3 is conditional from the situation at T2, situation at T2 is dependent of the situation of the network in T1, but the situation at T3 is independent on the network at T1. In these models, networks are seen as random variables in the outcome space of all possible networks, and network evolution is expressed as a stochastic process on this space. If there are a finite number of time steps then it is a ‘discrete time’ - Markov process (Wasserman, 1987, Wasserman and Iacobucci, 1988). This research focuses on actor-oriented models, which implies that actors have control over their outgoing ties. All the changes in the state of the network can be split onto a series of probability-based changes, called ‘ministep’. In a single ministep only one network change can be made, one tie at a time. This process implies that actors react to the state of the network and to observed attributes (covariates) of the actors, and do not coordinate their activities (Snijders, 1995 and 1996; Snijders and van Dujin, 1997; Snijders, 2001). The state of the network (i.e. number of ministeps) usually changes faster than it can be observed; and so the number of observations (waves) is smaller than the number of ministeps. As these ministeps are unobserved, the models of network dynamics simulate them for the periods between two observations of the state of the network.

First Markov chain model of Katz and Proctor (1959) assumed independent tie variables, where this assumption was later on loosened to independence of dyads (Wasserman, 1987). Introduction of triadic and higher-order dependencies was made by Snijders (1996), and then later on by Snijders and Van Dujin (1997) and Snijders (2001). The probability of change of a tie can depend on numerous “mechanisms” (tendencies or effects) that can be used to describe certain properties of the network dynamics. Depending on the focus of modeling they can be further separated onto tie-based and actor-based models. Tie based models are closely related to the exponential random graph models (Frank and Strauss, 1986; Wasserman and Pattison, 1996; Lusher et al. 2013). In actor based models actors have control over their outgoing ties under the constraint of one change at a time and the probability of change defined by the overall network characteristics. The principle development of longitudinal network analysis of stochastic actor based models is the development of the SIENA (Simulation Investigation for Empirical Network Analysis; Ripley et al, 2011) computer programme.

The actor based models have been first proposed by Snijders (1996) for ranked data and by Snijders and Van Dujin (1997) for binary data. The model is defined by two functions: the rate function and the objective function. The rate function is defined as λi(x;α) where actor i has a certain frequency in unit of time at which it can change its outgoing tie in the network state x, and α reflects the strength of different network parameters that influence the rate function. The

113 objective function is defined as fi(x;β), where actor i has a higher probability of changing its ties to a network state of x in which the value of the objective function is higher, and the β represents the strength of different network parameters that influence the objective function. For now only ordinal discrete variables can be analyzed into the model. The most frequently used network effects in the objective function are reciprocation (Moreno, 1934), transitive closure (Rapoport, 1953a, b) and the “The Matthew effect” (Merton, 1963, Barbarasi and Albert, 1999 – but they have called it “preferential attachment”).

Significant early empirical research on longitudinal networks were Newcomb`s (1961) study on college fraternity friendship, Coleman`s (1961) study on friendships among students from ten schools, Sampson`s (1969) study on relations among eighteen monastery monks and Kapferer`s (1972) study on the interactions in a Zambian tailor shop. Kapferer’s data set is also used as illustration of the SIENA software, which is available as a contributed package to the R statistical system, called RSiena. This programme is freeware and comes with an extensive manual (Ripley et al, 2011) which is best used in combination with an introduction paper on the models (Snijders et al, 2010).

The stochastic actor-based models can also accommodate dependent variables that are individual characteristics of the actors. Such variables are called behavior variables, for which it is assumed that it is recorded on an ordinal discrete scale. The dependence of behavior dynamics on the network is called social influence, and the dependence of network dynamics on behavior is called social selection (Steglich et al, 2010; An, 2011). Both processes can lead to similarity between connected actors, called network autocorrelation. The separation of selection and influence process is statistically challenging, and simple approaches may lead to wrong conclusions about social mechanisms (Steglich et al, 2010). Models for co-evolution of network and behavior have been specified by Snijders et al. (2007) and by Steglich et al. (2010), and they hold the assumption that actor, within the restrictions of the network, controls its outgoing ties and its behavior. Both network and behavior have their separate rate and objective functions, and at one point in time only one change may occur, either in the network or in the behavior; one point up or one point down on the ordinal scale.

In stochastic actor-based models the researcher has to define the objective function depending on the subject matter. As in generalized linear modeling, the objective function is expressed in linear form as (Snijders, 2011) 푓푖 = ∑푘 훽푘푠푘푖(푥) where Ski(x) are functions of the network as seen from the point of view of actor i, and they are called effects. In order to increase the value of the objective function actors may choose to make or to dissolve a tie, or to make no change in their network position. An overview of the main effect used in RSiena is presented in Table 12.

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Table 12. Overview of effects in RSiena (Sources: Snijders et al, 2010; Ripley et al, 2011; Steglich et al, 2010)

Effects of network evolution Effect Description Outdegree Tendency to have ties; included by default Reciprocity Tendency towards having reciprocal ties ; should be included almost always Also called transitive closure or clustering; friends of friends become friends; Transitive triplets or if i → j → h a tendency to form i → h tie, by counting j and h actors to which i has a transitive tie Similar to transitive triplets effect, but does not count the number of Transitive ties intermediaries (h), as it considers that additional intermediaries will not contribute to transitive closure Same as structural equivalence (Burt, 1982) with respect to outgoing ties; i.e. a Balance tendency to form ties with other actors who make the same choices as the focal actor. Number of actors at distance Negative expression of transitivity, i.e. for strong network closure there is two negative tendency to have actors at geodesic distance of 2 Generalized reciprocity, i.e. if i → j → h, it is the tendency to form h→i tie. Three-cycles effect Negative three-cycle effect can be interpreted as tendency towards local hierarchy Tendency of actors to position themselves between other actors who are not Betweenness directly connected; represents brokerage Tendency of actors with high in-degrees to attract more incoming ties; leads to In-degree popularity dispersion of in-degrees Tendency of actors with high out-degrees to attract more incoming ties; leads Out-degree popularity to higher correlation between in-degrees and out-degrees Tendency of actors with high in-degrees to send out extra outgoing ties; leads In-degree activity to higher correlation between in-degrees and out-degrees Tendency of actors with high out-degrees to send out extra outgoing ties. Leads Out-degree activity to dispersion of out-degrees Tendency of actors with high in-degree to form ties to other actors with high In-in degree assortativity in-degree Tendency of actors with high in-degree to form ties to other actors with high In-out degree assortativity out-degree Tendency of actors with high out-degree to form ties to other actors with high Out-in degree assortativity in-degree Tendency of actors with high out-degree to form ties to other actors with high Out-out degree assortativity out-degree Effects of behavior evolution Effect Description Indicates tendency towards higher values of behavior. Zero value indicates Shape tendency toward midpoint value The effect of behavior on itself. Indicator of “addictive” behavior. Negative Quadratic shape coefficients reveal preference for unimodal function

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Interaction effects of network on behavior Effect Description Preference of actor to being similar to their alters, where total influence of Average similarity alters is the same regardless of their number Preference of actor to being similar to their alters, where total influence of Total similarity alters is proportional to their number Tendency of actors to have higher values of behavior if their alters have higher Average later values of behavior Tendency towards higher values of behavior by actors who have higher Indegree effect indegrees Tendency towards higher values of behavior by actors who have higher Outdegree outegrees Degree-related effects can also be expressed as square roots of the normal effects, where the ‘square-root’ effects model the ‘additive’ tendency of actors which have high value of that effect to have it at even higher values (e.g. a tendency of actors which nominate many friends to nominate even more friends). Degree-related effects can represent global network hierarchy (entire network), whereas triadic effects represent local hierarchy (ego and all the alters to which he is connected to, including ties between alters). In a network with hierarchical structure negative sign of three-cycle, out-degree popularity and in-degree activity effects is expected, as well as a positive sign of the transitive triplets, transitive ties, in-degree popularity and outdegree activity effects. Actors` variables (exogenous effects) can have the following effect:

 Ego effect – a tendency of an actor to send ties if its value of the variable is higher  Alter effect – a tendency of an actor to send more ties if the value of the variable in its alter is higher  Similarity – a tendency of an actor to send ties to other actors with similar value of a variable  Same - a tendency of an actor to send ties to other actors with same value of a variable

For dyadic covariates there is only one effect which expresses the tendency for forming a tie between actors by increasing the value of the dyadic covariate. Rsiena also includes interaction effects between structural and exogenous effects, e.g. reciprocity-same education effect.

Three methods exist for the estimation of parameters in actor-based models; the method of moments (Snijders, 2001), Bayesian estimation (Koskinen and Snijders, 2007) and maximum likelihood estimation (Snijders et al, 2010b). In the method of moments the values of the parameter`s estimates are determined so that there is a perfect fit between the observed and the average simulated values over many simulations of the model. The method of moments is the default method in RSiena, and it is the only one which is available for non-constant rate functions. The Bayesian estimation and the maximum likelihood estimation require much more computing power, and are more appropriate to be used at smaller data sets with relatively

116 complicated specification of model. It should be also stated that for a not too small data set and with a strong goodness of fit, all three methods produce similar estimations (Snijders, 2011). A straightforward way of testing hypotheses about the parameters is to perform a t-test by dividing parameter estimates with their standard errors, which are part of the model`s output.

The assumption of gradual change between the waves is tested by the Jaccard index. It measures a similarity between two sets, and is defined as the size of the intersection divided by the size of the union of the sample sets, and not taking into consideration the “locations” in which there are ‘zeros’ in both sets. It ranges from 0 to 1, where higher values reflect higher similarity of the two sets. As a practical rule values greater than 0.3 are acceptable, whereas values lower than 0.2 mean that the assumption of gradual change is not adequately respected (although it is sometimes possible to perform analysis using actor-oriented model where Jaccard values is lower).

One way of interpreting the parameter estimates is that when actor i makes a change in a 푛푒푡 푛푒푡 ministep and x and x are the two possible outcomes of a ministep, then f (x ) - f (x ) is a b 푖 b 푖 a the log odds ratio for choosing between these two alternatives; so that the ratio of the probability 푛푒푡 푛푒푡 of an x and x as next states is exp (f (x ) - f (x )) (Ripley et al, 2010). Practically that b a 푖 b 푖 a means that if the parameter estimate is 0, than it does not have influence on the formation of the next state as its probability is 0.5 (i.e. e0=1, and odds ratio of one yields binary probability of 0.5). Another example would be if actor i had two potential or actual partners h and j to which he could send a tie to, and h and j have exactly same network position and all variables except for one in which h has value which is one point higher on the ordinal scale than the variable at actor i. If the parameter estimate for that variable is 0.3, then the odds ratio (i.e. e0.3) would be 1.35 (or binary probability of 0.5745) in the favor of sending a tie to actor h (Ripley et al, 2010). It should be noted that actors are never in a situation to make binary decisions as they have more opportunities to make or dissolve a tie, and this is a very simplified example of the calculations. An example of a very basic (more) realistic situation is presented in Figure 21.

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Figure 21. Network change opportunities for ego

It can be seen in Figure 21 that in the current situation, ego has three out-going ties (only one of which is reciprocated) and with no transitive ties. If the parameter estimates for reciprocity was 1.82, for out-degree -1.45, for and for transitive ties 1.03, then the current value of the objective function for the ego would be -1.45 x 3 + 1.82 x 1 + 1.03 x 0 = -2.53. The values of the objective function for all the options that ego has are presented in Table 13.

Table 13. Values of objective function for ego`s network change opportunities

Option Description No. of No. of No. of Value of the out-degree reciprocated ties transitive ties objective function 1 Keep current position 3 1 0 -2.53 2 New tie to A 4 2 2 -0.1 3 Drop a tie to B 2 0 0 -2.9 4 Drop a tie to C 2 1 0 -1.08 5 Drop a tie to D 2 1 0 -1.08 6 Make a tie to E 4 1 1 -2.95 7 Make a tie to F 4 1 1 -2.95

In this case the probabilities for the options 1 to 7 would be 0.043, 0.496, 0.030, 0.186, 0.186, 0.028 and 0.028 (or e-2.52:e0.1:e-2.9:e-1.08:e-1.08:e-2.95:e-2.95), where there is almost fifty (0.496) percent probability that ego will make a tie to actor A.

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4. Methodological approach

Case study research design has been chosen, as the form of the research question is “how”, as there is no control of behavioral events required and the research focuses on a contemporary event (Yin, 2009). Further argument for the case study design is that this research follows the formation of a decision within a formal working group, and “the essence of a case study, the central tendency among all types of case study, is that it tries to illuminate a decision or a set of decisions: why they were taken, how they were implemented and with what result” (Schramm, 1971).

The single case study design was chosen as the Natura 2000 forest policy represents a typical case of a step within the process of forest policy formulation in Croatia, where first a working group drafts an expert proposal of a legislation which is further on discussed at the governmental level. It also provides a revelatory test for the social influence network theory as this is the first time that this theory will be used on an ongoing national policy formulation process. The third reason for choosing a single-case study is the longitudinal aspect of research, which enables the analysis of change of opinions in relation to changes in inter-personal and inter-organizational relations. This relates to gathering most of the data on two different time points (waves) by using network panel data design.

The power and influence relations are analyzed on the level of the working group, where the units of observation are inter-organizational and inter-personal relations. The research is performed from the perspective of social network analysis. The following sections elaborate the methods which have been used to analyze the power and influence relations from the inter- personal and inter-organizational level onto the working group.

4.1. Modelling interpersonal relations

The overall setting of the interpersonal relations is within Friedkin and Johnsen`s (1997) model of social influence for small group dynamics. This model has been chosen among its alternatives (Knoke, 2011) as unlike Coleman`s (1973) and Marsden`s (1983) models, it is designed to focus a study on a single decision making process. The Dynamic policy models (Pappi and Kappelhof, 1984) and dynamic access models (Stokman and Van den Bos, 1992) were also ruled out due to the fact that they differentiate between stakeholders and those with voting power. In this case study, they are all in one group.

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Friedkin and Johnsen`s model can be described by two equations, where the first one describes the initial opinions,

y1=Xb

Where y1 is the initial opinion for n x 1 vector of individuals, X is an n x k matrix of variables of endogenous variables that formed the initial opinion, and b is a k x 1 vector of coefficients which determine the relative weight of these endogenous variables. The second equation describes subsequent change from the initial opinions,

yt=αWy(t-1)+(1-α)y1

t for t=2, 3…., where y is a n x 1 vector of individual opinions at time t, and where W = [wij] is an n x n matrix of endogenous interpersonal influences where the total sum of interpersonal 푛 influences upon an individual totals 1 (i.e. 0 ≤wij≤1, ∑푗 푤ji =1), and α - the coefficient of social influence, is a scalar weight which determines the relative contribution (0 ≤α≤ 1) of the exogenous and endogenous effects to the formation of an opinion. The model assumes long-term equilibrium of opinions, where

y∞=y1 + Vy1 and where V = αW + α2W2+ α3W3+ α4W4 +…+ α∞W∞ (Friedkin and Johnsen, 1990). On an illustrative case let the network be defined by two cliques {1,2,3,4} and {5,6,7,8} connected with a reciprocated tie between actors 4 and 5. This network is presented in Figure 22.

Figure 22. Illustrative case of social influence network (Source: Friedkin and Johnsen, 1997)

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The numbers related to the lines represent the relative share of actors` received influence, and with self-weights the matrix of interpersonal influences (W) is

With an initial opinions (y1) being vector [0 25 45 50 50 55 75 100] its transformation through W with α=0.5 for all actors yields vector [6 21.5 31.5 37.75 62.25 68.5 78.5 94] at y2. Accordingly, the equilibrium vector for y∞ is [6.9 21.2 31.2 37.8 67.2 68.8 78.8 93.1]. If α=0 for all actors than the opinions in the subsequent step would not have changed at all, whereas if change in opinions was almost totally attributed to inter-personal influence (e.g. α=0.99) then all opinions of the actors at y∞ would be close to the middle opinion (i.e. it would result with vector [48.8 48.9 48.9 49.2 50.8 51.1 51.1 51.2]). This long-term equilibrium (Friedkin and Johnsen, 2003) can also be seen as a way of reconciling social influence explanations of network autocorrelation with the previously mentioned models of co-evolution of networks and behavior. The usage of Friedkin and Johnsen`s model in this research is based on the data derived at the beginning of the research (T1) with goals of predicting outcome opinions (T2). Actual outcome opinions of the members of the working group were also collected and compared to the predictions of the Model. The Model in this research is used with no self-weights allowed; rather the alpha coefficients have been set for each actor differently, based on the pressure they felt to reach a consensual decision (data received through questionnaires on a five point ordinal scale). Social power is taken as an alternative operationalization of the alpha coefficient, with the assumption that the more powerful actors will be less prone to being influenced by other actors. Following the literature on social power all the members of the working group have been interviewed twice, and all these interviews have been coded through a total of 16 different codes which are associated with powerful/powerless actors. In this context each code associated with a powerless actor has been given -1 mark, and codes associated with powerful actors have been given +1 mark. The range of all -1/+1 marks has been rescaled to 0-1 range in order to represent the alpha coefficient, where 0 is attributed to the most powerful actor, and 1 is attributed to the least powerful actor. The code book for social power with memos and references to scientific literature are provided in Annex II.

Variables of the social influence network theory have been operationalized according to Friedkin`s (1993) longitudinal model of interpersonal influence, which is presented in Figure 23.

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Figure 23. Longitudinal model of social influence (Source: Friedkin, 1993)

Following Festinger`s theory of social comparison (1954) the interpersonal influence was operationalized as salience of alter`s opinion on ego and visibility of alter`s opinion to ego, where the operational measure of influence was constructed by adding up the “salience” and the “visibility” scores. French and Raven see social power as a relational concept, where the strength of power of O over P is the maximum potential ability of O to influence P (in a psychological system) in spite of the resistance of P towards O, so that “…influence is kinetic power, just as power is potential influence” (French and Raven, 1959, p.63). This is closely related to “the first face of power” by which “power is the ability of A to get B to do something he or she would otherwise not do” (Dahl, 1957, p.202).

One item for each of these variables has been administered on a 0-4 ordinal scales (from 0 - “no relation” to 4 – “very strong”), same as for the item on issue-related interpersonal communication. The independent variables are structural bases of social power operationalized as three point Guttman scale of discussion, (help seeking and friendship), and the French & Raven (1959) bases (reward, coercive, legitimate, referent and expert) of social power.

The French and Raven`s (1959) power bases have been operationalized following the definitions of Hinkin and Schriesheim (1989), who have developed their own definitions and scales as a response to Podsakoff and Schriesheim`s (1985) strong critique of previous scales. These definitions are (Hinkin and Schriesheim 1989):  Reward power is the ability to administer to other things he or she desires or to remove or decrease things he or she does not desire.  Coercive power is the ability to administer to other things he or she does not desire or to remove or decrease things he or she does desire.  Legitimate power is the ability to administer to other feelings of obligation or responsibility.  Referent power is the ability to administer to other feelings of personal acceptance or approval.  Expert power is the ability to administer to other information, knowledge, or expertise.

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Informational power was also discussed by French and Raven (1959), but was not originally classified as one of the primary bases of power. Information power (Raven, 1965) was used following the argumentation of Raven et al. (1998), and in this research was defined as “...information is used in its broadest sense to include any different perspective or knowledge” that may be conveyed by a person to you (p.308).

One item per power base was used, where the respondents were asked a question on a dyadic level (e.g. “How much do you consider a person X to be an expert?”) followed with an explanation of the wording related to the power base (e.g. “Expert is a person with the ability to administer to other information, knowledge, or expertise”). Podaskoff and Schriesheim (1985) recommend usage of rating scale to avoid some of the problems of the ranking scales, which show that the scales on different power bases are not methodologically independent of each other, and they tend to force negative correlations between some of the measures of social power. For this reason, a five point ordinal rating scale was used with single item per power base. Although the same authors have held strong reservations on the validity of research with one-item per power base, each item per-power base includes the formulation of the concept of that power base, thus diminishing the bias of construct validity. The pre-testing of the questionnaire on the students and staff at the Faculty of Forestry, University of Zagreb and on 13 members of 4 other organizations from the analyzed network, showed that the question on sources of social power are cumbersome to the respondents and strongly diminish their willingness to participate (especially among the senior respondents). This was another reason for one item per power base, and why also a separate, shortened version of the questionnaire was developed for respondents who found the entire questionnaire too lengthy and time consuming. The shortened version of the questionnaire does not have items on structural as well as French and Raven`s bases of social power. Pretesting also revealed that respondents have different preferences on the administration of the questionnaire. In order to increase the response rate multiple questionnaire administration techniques were employed: computerized questionnaire administration, face-to-face and paper-and-pencil questionnaire administration.

In order to apply data sources triangulation (Yin, 2009) direct observation was conducted as a supplement to the questionnaires. The variables that have been observed during the meetings of the working group were:

 Successful / failed conversation intrusion Following Keltener et al. (2003) powerful individuals display less behavioral inhibition than powerless individuals and have the capacity to resist the influence attempts of others (Brauer and Bouhoris, 2006). Ng and Bradac (1993) have also found that speech interruption is an element of social influence in verbal communication. On a dyadic level successful conversation intrusion is regarded as a sign of higher social power, and failed conversation intrusion is regarded as a sign of lower social power.

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 Gaze direction of the listener in a dyadic Looking more while speaking and looking less while listening is related to high social status and French and Raven`s bases of social power (Aguins et al, 1998; Brown et al, 1990; Dovidio et al, 1988). Following this line of thought, issue-related interpersonal influence per meeting has been operationalized as a normalized difference (details on p.133) between the number of dyadic conversations where a listener was looking at the speaker with the number of dyadic conversation and when the listener refrained from making eye contact with the speaker. Dyadic communication was regarded as every communication that lasted longer than ten seconds.

 Usage of scientific/expert and political argumentation Instances when members of the working group used these two kinds of argumentation were counted. Scientific and expert argumentations is defined as arguments in which evidence and alternatives were weighted, all based on evaluation of the potential viability of scientific claims, with claims being defined as established facts or “modalities that highlight generality of available evidence” (Latour and Woolgar, 1986). Political argumentation is defined as statements which relate to choice of values that should guide (public) policy formulation (i.e. employment, financial, etc., and any other values than scientific facts), (Jackman and Sniderman, 2006). Political argumentation is also characterized by the following traits (Taber et al, 2008): actors spend time and cognitive resources denigrating and counter-arguing attitudinally incongruent arguments (Ditto and Lopez, 1992; Taber and Lodge 2006), biases in information processing which promote more extreme attitudes among actors which have processed the same information (Taber and Lodge 2006), and biases where actors evaluate arguments and evidence that support their priors as stronger and more compelling than contrary arguments (Redlawsk 2002; Rudolph 2006; Taber and Lodge 2006).

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4.2. Modeling inter-organizational relations

The overall setting of the inter-organizational relations is within Pfeffer and Salancik`s (1978) resource dependence framework which was described previously. This research assumes that inter-organizational relations are steered by purposeful decisions of their management which is aware of the positions of other organizations in the analyzed network. Only strategic inter- organizational relations are taken into account. The research also assumes that members of the working groups are acting as agents of their organizations, which are aware of their organizational interests and opinions on the discussed issues, and that they are aware of the relations of their organization to all other organizations in the observed network.

The focus of the institutional framework (DiMaggio and Powell, 1983) on the cultural systems and organizational change is more fitting to a qualitative data oriented research design with longer time frame of analysis, both of which diverge from the research design of this study. The institutional framework also introduces ambiguity on the operationalization of inter- organizational power relations. The social class framework (Domhoff, 1967; Zeltin, 1974) provides more focus on the power-interest relations. Moreover, in the lineage of the critical theory`s line of thought it differentiates the elite class between organizations and within organizations by looking at many different types of relations on different levels. This again is not fitting to the design of this research, as research following this theoretical framework would sway the focus away from the working group, which covers a relatively small time frame and a limited formal setting.

Pfeffer and Salancik (2003) see network analysis as complementary to the resource dependence perspective, but although “this book is filled with network and relationship imagery, even though there was almost no attempt to explicitly employ network methodology to analyze the studies summarized therein” (p.xii). Social network analysis shows linkages to the resource dependence perspective, as in both previous ties that organization had determined the subsequent ones (Piskorski and Anand, 2002), as in both the network structure provides opportunities for brokerage (which is related to Burt`s (1982) theory of structural holes). In addition, the status of the focal organization is determined by status of the organizations to which it is connected to (Podolny, 1993). As the resource dependence perspective is partially based on Emerson`s (1962) exchange theory, where “power is a property of the social relation; it is not an attribute of the actor” (Emerson, 1962: 32), the operationalization of inter-organizational power relations is, compared to the alternative frameworks, which are relatively straightforward.

According to Thompson (1967; p.31) – an “organization is dependent….in proportion to the organization’s need for resources…and inverse proportion of the ability of other elements to provide the same resource…”. Based on the overview of resource typologies by Kraaijenbrink and Groen, (2008), the typology of Pride et al. (1991) has been chosen, which consist of

125 material, human, financial and information resources. This research power has been operationalized as the sum of actor i`s dependence on actor j and vice versa, total for all resource types. The flow of resources from actor j to actor i is used as a proxy for dependence of actor`s i dependence on j, as the inter-dependence is characterized by actors “…transacting in the same environment, with the connection being through the flow of transactions” (Pfeffer and Salancik, 2003, p.42). Emerson’s (1962) and Thompson`s (1967) arguments that power-dependence relation is also inversely proportional to the availability of alternatives was not followed due to the fact that the boundaries of the studied network do not represent complete organizational environment of the organization within the network. Pfeffer and Salancik (1978) see inter- organizational power as the misbalance in resource dependencies on a dyadic level. This kind of operationalization incorporates mutual dependence which might have different consequences on behavior of organizations (Casciaro and Piskorski, 2005), and may “hide” important network features from the analysis, most importantly reciprocity, which is closely related to mutual dependence. The discretion of organizations on the legal and wider social constraints that might give an organization possibility to resist inter-organizational power has not been studied and for analytical purposes is assumed not to exist. The research also assumes that organizational behavior is visible to other organizations in the network. With these two conditions inter- organizational influence is equated to its potential, the inter-organizational power (Pfeffer and Salancik, 1978). Questions on inter-organizational relations were administered on a 0-4 ordinal scale, ranging from “No resource flow (0)” to “Strong resource flow” (4), where the respondents reported on the receiving flows of resources for their organizations.

In an empirical study of accuracy and reliability in inter-organizational networks, Colloway (1993) found the self-reported data quire reliable; nevertheless, he also pointed to a relatively small but significant systemic error: there is better recall for strong ties and more central actors, than for the peripheral ones. This poses a problem for research where the network is large and there is a broader range of interactions to consider, but does not pose a threat to the studies with relatively small networks and for the studies which apply snowball sampling. These findings are consistent with the ones of Kossinets (2006) and Freeman et al. (1987, p.315), where respondents from more central organizations have frequently been included in ego networks of organizations to which they have no relation. However, as respondents are more likely to accurately report on routinized relations than on specific time and content references, the issue of over-representation of strong ties is more salient in inter-personal studies than in inter-organizational ones (Marsden, 1990, p.447). These statements, in the small network of 13 organizations with frequent interactions and simple operationalization of inter-organizational relations provide arguments for the validity of the collected inter-organizational data.

A total of nine statements have been chosen to reflect the issues that have been addressed by the working group. Statements were selected based on the prior knowledge of the subject matter, on communication with six members of the working group and on communication with four other

126 experts out of the working group, both from the fields of nature protection and forestry. Eight statements reflect specific issues between nature protection and forestry related to Natura 2000, and one statement was defined in order to assess the general inclination of the respondents towards Natura 2000 in forestry. Respondents were asked to mark on a nine-point Likert scale to which extent they agree or disagree with the statements. The scale ranged from “Totally disagree” (-4), across “Neither agree nor disagree” (0) to “Totally agree” (4). According to the interviewed experts there is a demarcation between the general positions of the forestry and nature protection sectors on agreeing or disagreeing with these statements. The statements related to the general positions of nature protection and forestry are shown in Table 14.

Table 14. Stakeholders ` statements on the Natura 2000 forest policy GROUP OF ACTORS STATEMENT NATURE FORESTRY PROTECTION In order to reach favorable conservation status of forest related Natura 2000 species it is necessary that forest habitats always have a minimum of disagree agree 3% (or 10-15 m3/ha) of dead and decaying woody biomass. In order to reach favorable conservation status of Natura 2000 forest related species it is necessary to prescribe general guidelines for nature agree disagree protection that stipulate sustainable forest management. In order to reach favorable conservation status of forest habitats from the ‘Habitats’ directive it is adequate to define Natura 2000 forest habitats agree disagree within nationally protected areas. In order to reach favorable conservation status of forest habitats from the ‘Habitats directive’ it is necessary to put some forest habitat sites in the disagree agree category of a special reserve. In order to reach favorable conservation status of forest habitats from the ‘Habitats directive’ it is necessary to include ‘Spačva basin’ forests in the disagree agree national proposal of Natura 2000. In order to reach favorable conservation status of Western Capercaillie and Hazel Grouse interventions in populations of other strictly protected species should be allowed, with the condition that it is scientifically agree disagree proven that these other species endanger populations of Western Capercaillie and Hazel Grouse. In order to reach favorable conservation status of forest related Natura disagree agree 2000 species it is necessary to limit the area of final cut on 60 ha. In order to reach favorable conservation status of forest related Natura 2000 species it is necessary to leave up to 5 ha of uncut area within the disagree agree final cut area. Natura 2000 will improve the current system of forest management in disagree agree Croatia.

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4.3. Questionnaire design and data collection

Following Marsden (1990) the questionnaires (Annex VII) were pre-tested during January and February 2012 on students and staff of the Faculty of Forestry, University of Zagreb, and on employees from four other organizations in the networks. The instruments had a shared meaning among the respondents and several smaller wording and formatting changes have been made. As the questions related to bases of social power were regarded as excessively minute, a shorter version of the questionnaire was prepared without such contents.

Following the ethical guidelines for organizational network research (Borgatti and Molina, 2005) organizational approval for interviewing was gained prior to the data collection process. Written consent for interviewing was granted from the members of the working group, where the request was an item for discussion at the third meeting of the working group. Before every interview and questionnaire a letter was provided in printed and in electronic form, in which the anonymity of their responses was addressed, along with assuring them that at any point they can refrain from answering any question, and may fully cease to provide an answer, and may choose to be totally excluded from the research. Following the ethical guidelines of network analysis by Kadushin (2005) it was also stated that given the limited size of the group, total anonymity could not be guaranteed; rather, their names will be coded, variables will be presented in a manner that maximizes anonymity and the analysis will be focused on the group and its dynamics, and not on individuals.

A ‘nominalist fixed list sampling’ (Laumann et al, 1983) was used, according to which network boundaries are defined by the researcher for analytical purposes. The boundary was set to include individuals who were present at the meetings of the working group and to include organizations which nominated their representatives to attend these meetings. Following the argumentation of key informants on issues of different interest of forestry and hunting administration within the Ministry of Agriculture, these two departments have been presented as two different actors in the majority of the analysis. First the questionnaires regarding inter- personal relations were administered by e-mail in excel format. The questionnaire regarding inter-organizational relations was administered following the questionnaire on inter-personal relations. In this manner partial system fallacy was avoided (Laumann et al, 1983) as the data collection method was such that all respondents were able to comment on all other respondents and on their organizations. All the members of the working group have completed all administered questionnaires.

A ‘fixed list collection technique’ has been used since it produces more ties and weaker ties than the ‘free recall’ technique. Thus it is more suitable for groups in which are acquainted with each other fairly well (Ferligoj and Hlebec, 1999), which was the situation in this case. As the same

128 research showed that in comparison to binary choices and to visual analogue the ordinal scale demonstrated most reliable results and that is the reason why the ordinal scale was chosen. In order to improve the reliability of the responses informative example questions were given prior to the real questions with guidelines on how to answer them. The questionnaires on inter- personal and inter-organizational level were administered twice - to capture the change that had occurred in the meantime, i.e. from the onset of the data collection until the end of the meetings of the working group.

There were a total of eleven meetings of the working group (March 18th, 2010 - October 11th, 2012). The organizations that had their representatives in the working group are: State Institute on Nature Protection (SINP), Alliance of Private Forest Owners and Forest Owners Associations (APFOA), Croatian Academy of Sciences and Arts (CASA), Croatian Forests Ltd. (CF), Croatian Forestry Society (CFS), Croatian Natural History Museum (CNMH), Croatian Union of Private Forest Owner`s Association (CUPFOA), Forest Extension Service (FES), Faculty of Forestry, University of Zagreb (FOF), Ministry of Culture, Directorate for Nature Protection (MCDNP), and the Ministry of Agriculture, with members from the Department for Forestry (MDF) and the Department for Hunting (MDH). The organizations that had their members in the working group range from state administration, (e.g. MCDNP, MDF, MDH), scientific organizations (e.g. FOF and CFRI) expert and implementing agencies and companies (SINP, FES, CF), to some organizations that can be described as typical stakeholders (CFS, APFOA, CUPFOA) of the process. As the approval for administering questionnaires was granted at the third meeting of the working group, on March 29th, 2011, a total of 29 questionnaires on inter- personal level were administered by e-mail and in printed, hard-copy format. Three printed out questionnaires were filled by respondents and submitted at the subsequent meeting. Two questionnaires were completed by face-to-face method, and 24 were returned by e-mail. Three respondents did not complete the questionnaires until the onset of the next (fourth) meeting, but they have been competed before the fifth meeting. Their responses have been added to the network of inter-personal influences for the first wave. For this reason there are three more actors in the non-participant observation from the number of participants at the second wave of questionnaires. Four persons who were not present at the final meetings did not wish to fulfill the inter-personal questionnaire in the second wave, stating that their inter-personal relations have not changed since the first wave. They were asked questions on their opinions on the nine issues addressed by the working group, and their opinions have marginally changed. A similar procedure was repeated subsequently for the questionnaires on inter-organizational level, as four printed versions of the questionnaire were returned to the fifth meeting, seven were administered face-to-face and 18 were returned by e-mail. In order to secure the external validity of inter- organizational relations, the questionnaire was also sent to 18 key informants out of the working group, 14 of which fulfilled and returned the questionnaire by e-mail. Following Marshall (1966) and Kumar et al. (1993) there was also a selection process for choosing key informants based on

129 their position in the hierarchical structure of the organization, interactions with other organizations in the network and on their willingness for communicating information. They were also asked on their knowledge on the subject matter, and well-informed key informants nominated other knowledgeable key informants. The second wave of questionnaires was administered after the last, eleventh meeting (October 11th 2012). For both questionnaire types, four printed versions of the questionnaire were delivered to respondents and collected afterwards, 12 were administered by face-to-face method, and 26 were received by e-mail. During the administration of the first wave of questionnaires on inter-organizational relations, feedback from the respondents was enquired on the questionnaire on inter-personal relations. Most of the respondents commented that the questions relating to power bases were too tedious, and as a response to that issue, the second wave of questionnaires on inter-personal relations did not include those questions. Feedback on the questionnaire on inter-organizational relations was almost completely positive and it received no alternations in the second wave. Two researchers participated in the administration of the questionnaires.

Non-participant observation produced a total of seven waves of data that was collected from the fourth until the eleventh meeting, where no data was collected for the sixth meeting. Two researchers participated in the data collection process, either alternating or jointly observing the meetings of the working group. In order to decrease the bias, researchers made no gestures and no verbal communication during the meetings, and sat at different corners of the table or in the corner of the room. Before and after the meetings, the researchers made an attempt to not engage in communication with the members of the working group, and in the cases when communication occurred, no normative judgments on the subject matter were made.

4.4. Data analysis techniques

The first step of analysis is a cross-sectional inquiry into the relations between the items that are theoretically bound to same variables, such as the link between salience and visibility of alter`s opinion on ego, the relation between French and Raven`s bases of social power and interpersonal communication, or the differences in the observations of the meetings between the researchers. This kind of analysis will be performed in appropriate network statistical tests, such as QAP (Quadratic Assignment Problem) and the multiple linear QAP.

The next step is the cross-sectional inquiry with an exploratory purpose of examining the network structure. To that end, the existence of cohesive subgroups, distribution of centrality measures, brokerage and role algebra will be analyzed in all three types of networks.

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For the analysis of groups, different tests are applied, such as factions routine or the core- periphery routines. The factions routine classifies actors in a predetermined number of cohesive sub-groups, where the ideal type classification of actors would consist of having all possible ties within the group and no ties out of it. The components routine for valued ties identifies cohesive sub-groups at increasing levels of the strength of a tie without paying respect to the direction of the tie. The categorical core-periphery routine classifies actors onto two groups; one is maximally interconnected (the ‘core’) and the other one is minimally interconnected (the ‘periphery’). Structural equivalence routine groups actors with the criterion of having “same ties to same others”, and regular equivalence groups actors with the criterion of “having similar ties to similar others”. To use the analogy of parents and children, “structural equivalence would place together parents of the same children. Regular equivalence would place together all parents” (Everett, 1985, p.355). As explanation of network concepts beyond this superficial level would significantly increase the volume of the manuscript, readers unfamiliar with network analysis are suggested to find more comprehensive explanations of the concepts which interest them. Such can be done within the introduction-level texts, like the free online textbook by Haneman and Riddle (2005) or Analyzing Social Networks by Borgatti et al. (2013). For more advanced texts on SNA, the textbook by Wasserman and Faust (1994) and the textbook edited by Scott and Carrington (2011) are recommended.

The next step of analysis is the application of Friedkin and Johnsen`s (1997) model on the network of inter-personal influences and on the network of inter-organizational resource flows. The purpose of analysis is to find out to which extent the predictions of all these models fit to the observed outcome opinions, where the rival explanations lie in the inter-personal influences and in the structural setting within which the decision making process is embedded.. Alignment of the observed with the predicted values would indicate the importance of power relations on the policy formulation process, either on the inter-personal, or at the inter-organizational level.

The final and most comprehensive type of analysis is the usage of actor-based models for longitudinal network analysis (Snijders et al, 2011), where the models of network evolution (i.e. influence) and models of network and behavior (i.e. opinions) are constructed. The purpose of the longitudinal influence models is to assess the internal dynamics of influence relations, to test to what extent actors` attributes (like seniority) affect influence relations, and to test how the organizational level affects the inter-personal relations through organizational power and mutual dependence of their organizations. The purpose of the co-evolution model of influence and opinions is to assess the causal relations between influence and opinion change. In addition, it serves the purpose to verify the assumption of Friedkin`s model that influence relations affect opinion change.

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5. RESULTS

5.1. Networks of interpersonal relations

5.1.1. Internal validity of the Friedkin`s (1993) model

As stated in the previous chapter, before commenting on the structure of the networks of inter- personal influence, an analysis of the internal validity of the French and Raven`s (1959) bases of social power and of Friedkin`s (1993) model is needed. The relations between the first set of variables in the model, the French and Raven`s (1959) bases of social power, are presented in Table 15.

Table 15. QAP correlation between items on French and Raven`s (1959) power bases

Reward Coercive Legitimate Referent Expert Information Reward 0.50*** 0.14+ 0.10+ 0.10+ 0.10+ Coercive 0.20*** 0.07* 0.11 0.19*** Legitimate 0.57*** 0.62*** 0.56*** Referent 0.49*** 0.49*** Expert 0.77*** Information +p<0.1 * p<0.05 **p<0.01 ***p<0.001

It can be seen that there is a moderate correlation between reward and coercive power, both of which are not related to the other bases of social power. Inspection of the data reveals that in the vast majority of cases, reward and coercive power were related to the actor`s superiors in the organizational hierarchy. A grouping between legitimate, referent, expert and information power is present, while the strongest connection is between expert and referent power.

The next step is a test of items related to the dependent variable – the inter-personal influence. QAP correlations between three items on inter-personal influence have been performed; the previously mentioned salience and visibility of alter` opinion on ego, and the direct measure of influence. The third item was gained by asking respondents “How much has X influenced your opinion on the issues discussed at the working group?”, where the question was administered also on a five point ordinal scale. The results of this analysis for time 1 (T1) are presented in Table 16.

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Table 16. QAP correlations among items on interpersonal influence

Visibility Salience Influence Visibility 0.72*** 0.62*** Salience 0.63*** *** p<0.001

It can be seen that there is a strong correlation between salience and visibility of alter`s opinions on ego, while the relation of these two variables to “influence item” is of somewhat lesser strength. At T2 salience and visibility of opinion item showed even greater QAP correlation of 0.86 (p<0.001). Based on these results operational measure of inter-personal influence was gained by adding the scores on inter-personal visibility and salience of opinions. Friedkin was correct to model the issue-related inter-personal communication as the intervening variable for the inter-personal influence, as the QAP correlation between these two items (influence as joint scale of visibility and salience of alter`s opinion on ego) is 0.56 (p<0.001) at T1.

Although these relations among the bases of social power are in accordance with its other application (see Podaskoff and Schrirsheim, 1985 for a review), it should be noted that during the pre-testing there was a common understanding among the respondents that questions related to expert and information power were not sensitive, while the questions on all other power bases were considered sensitive and personal. The same applied for the dependent variable, where the question on inter-personal influence was regarded as sensitive. Development of different items on power bases in the pre-testing (following Hinkin and Schrirsheim, 1989) did not change their sensitivity, and it only increased the length of the questionnaire. The SNA equivalent to the multiple regression, the Double Dekker Semi-Partialling MRQAP, was used to test the relation among all variables in the Friedkin`s model of inter-personal influence. The results of this analysis are presented in Table 17.

Table 17. MRQAP of Friedkin`s (1993) model of interpersonal influence.

Interpersonal influence as dependent Communication as dependent variable variable Adjusted R2 = 0.39*** Adjusted R2 = 0.54*** Standardized p-value Standard Standardized p-value Standard coefficient error coefficient error Intercept 0.000 0.000 0.000 0.000 0.000 0.000 Reward 0.114 0.014 0.135 0.037 0.243 0.324 Coercive 0.086 0.040 0.151 -0.021 0.348 0.327 Legitimate 0.010 0.437 0.072 -0.034 0.362 0.188 Referent -0.091 0.062 0.100 0.029 0.333 0.234 Expert -0.066 0.147 0.056 0.233 0.002 0.126 Information 0.493 0.001 0.072 0.099 0.060 0.136 Structural 0.252 0.001 0.080 0.369 0.001 0.199 Communication 0.252 0.001 0.107 *** p<0.001

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The effect of reward and coercive power on issue-related interpersonal communication is marginally significant, as their p values are between 0.01 and 0.05. Both information and structural base of power have significant positive effect on communication, while the effect of other independent variables in not significant. Expert power and structural base of power along with communication have significant and positive effect on inter-personal influence. The difference between the level of coefficients of the information power and communication on one side and the structural base of power can be explained by the fact that information and communication items were administered on a five-point scale, where the item on structural bases of power was administered on a three-point scale.

The adjusted R2 values of the model are larger than they were in its original application (Friedkin, 1993), where the difference of R2 in the models with influence as dependent variable is marginally larger (0.47 to 0.54), and the difference of R2 in the models with communication as dependent variable is significantly larger (0.20 to 0.39). Due to the sensitivity of many variables in the model, strong correlation between items on influence and between communication and influence, this research suggest that within the same context a similar validity of results would be achieved by applying a simplified model consisting of one item on inter-personal communication and two items on inter-personal influence (i.e. visibility and salience of alter`s opinion on ego).

Previously, it was stated that two researchers performed the non-participant observation. The validity of their observation is indicated by the fact that the QAP correlation between their observations of dyadic communication is 0.86.

5.1.2. Whole network characteristics

The first step in the cross-sectional network analysis is to analyze the general characteristic of all networks under research. These basic parameters are presented in Table 18.

Table 18. Basic parameters of the inter-personal influence networks

Questionnaire Non-participant observation T1 T2 T1 T2 T3 T4 T5 T6 T7 No. of actors 29 21 13 16 19 14 17 13 15 Mean normalized 32.27 55.51 23.42 18.28 3.51 12.50 18.08 18.73 15.13 outdegree Density 0.62 0.78 0.45 0.48 0.13 0.32 0.44 0.29 0.22 Reciprocity (%)* 0.50 0.68 0.50 0.30 0.46 0.33 0.25 0.53 0.45 (dyad based)

*percentage of all actual ties that are reciprocated

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The whole network characteristics derived from the questionnaires show that that the network became denser, and that on average, the strength of influence relations has grown more than the network density did. Overall, the densities are high, which indicates that the closed formal setting of the working group, where everyone was sitting at a conference table, has created interaction opportunities between majority of its members. The reciprocity has also increased, which is a whole-network indicator of non-hierarchical structure. However, initially large share of transitive ties have increased by the final meeting of the working group, indicating local hierarchical structures. The increase of transitivity is even more pronounced for stronger ties (i.e. x> 3 on a 0-8 scale), where it has grown from 75% to 92% of all triads where one tie is missing from completing a transitive link. This indicates that although, generally the network became denser and relations became more reciprocated, the share of influence spread by more influential actors within sub-groups has increased.

The inter-personal influence derived from the non-participant observation has been operationalized in the following way: the raw scores on communication when the listener was looking at the speaker and the communication when the listener was not looking at the speaker were transformed to Z-scores. As Z-score transformation enables comparison of scores measured with different units or on different populations (Abdi, 2007), the difference between these two Z- scores has been scaled to 0-1 range, and has been taken as the operationalization of interpersonal influence. The QAP correlation between the “raw” influence scores and the transformed ones is 0.83 (p<0.001).

In comparison to the questionnaire data, in the influence networks derived from direct observation there is the opposite general trend of decrease in the mean value of normalized outdegree, and also an opposite trend in the decrease in network density. As this operationalization of interpersonal influence is directly derived from dyadic communication patterns, it can be said that although in the end actors became familiar with and influenced by opinions of an increasing number of actors, the actual number of actors who engaged in communicating with and on influencing other actors decreased. The third wave of non- participant observation diverges from all these trends, and is characterized by very low normalized outdegree, low density and high reciprocity. This observation was made at the seventh meeting of the working group. At that meeting the proposal for the protection of forest habitats made by the members of the forestry sector was presented. The presentation lasted half of the meeting and was made mostly by one person who then provided answers to the questions posed by other members of the working group. This presentation made communication patterns in the sixth meeting significantly different from the communication patterns in other meetings, and since it represents a unique case, it is discarded from future analysis. When asked on the observed changes between the meetings of the working group, the respondents replied that the first couple of meetings were dominated by general discussion on political aspects of Natura

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2000 in which the majority of participants were engaged, and that agenda of the meetings was not followed. They also commented that as the meetings progressed, the discussion became more focused and more argument based. This content-related trend is in accordance with the network- based trends. The correlations between the influence from the Friedkin`s model (salience and visibility) and the elements of influence from the non-participant observation are presented in Table 19.

Table 19. QAP correlations between different items related to interpersonal influence

Communication from non-participant observation Reciprocated ”Raw” influence Z normalized dyadic influence communication

Questionnaire Influence 0.19*** 0.33*** 0.30*** (T2) (V&S) *** p<0.001

It can be seen that the QAP correlation of Z-normalized values of inter-personal influence (from the difference of Z scores of reciprocated and non-reciprocated communication) and the influence from the Friedkin`s model, is actually not any greater than the correlation of influence from the Friedkin`s model with the “raw” difference of reciprocated and non-reciprocated communication, which is actually mathematically an invalid measure. It can also be stated that the level of reciprocated communication is not a good predictor of issue-related inter-personal influence, but that it is the reported perception of issue-related communication.

5.1.3. Centrality measures

As previously discussed in the introduction to SNA, centrality is one of the basic characteristics that is studied in network analysis, and is often related to the concept of power. The two measures of centrality that are appropriate for valued and directed networks (Borgatti et al, 2013), the degree and beta centrality, are presented in Table 20. The values of β+ and β- are calculated with positive and negative levels of eigenvalue.

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Table 20. Normalized centrality measures for interpersonal influence networks

Normalized centrality measures of interpersonal influences Influence Friedkin T1 Influence Friedkin T2 Influence observation sum Out- In- β+ β- Out- In- β+ β- Out- In- β+ β- degree degree degree degree degree degree CF1 67.4 12.9 1.8 1.9 86.8 31.2 1.4 1.5 52.0 41.5 1.5 1.9 SINP5 66.5 55.3 1.8 1.9 73.7 71.8 1.2 1.3 45.2 41.9 1.3 1.6 MDF2 58.0 47.7 1.5 1.6 84.3 63.1 1.4 1.4 46.8 40.1 1.6 1.3 FOF1 54.4 45.9 1.4 1.6 70.6 55.6 1.2 1.1 48.7 31.6 1.6 1.5 SINP7 54.4 18.7 1.4 1.6 77.5 82.5 1.3 1.3 51.8 50.8 1.6 1.7 FOF2 45.5 24.1 1.2 1.3 31.4 24.1 1.0 0.9 CASA1 37.5 5.3 1.2 0.9 MDH1 36.6 44.6 1.0 0.9 58.1 53.1 0.9 1.0 30.9 32.8 0.9 1.1 SINP2 36.6 42.8 1.1 0.9 60.0 71.2 1.0 1.0 10.0 25.1 0.3 0.2 CFS1 35.2 49.5 0.9 1.0 66.2 42.5 1.1 1.1 7.8 19.7 0.4 0.0 SINP3 35.2 77.6 1.0 0.9 48.1 86.2 0.8 0.8 49.9 34.9 1.4 1.8 CFRI3 30.8 11.1 0.8 0.8 56.8 56.2 1.0 0.9 7.8 5.2 0.4 0.0 MCDNP2 30.3 19.2 0.8 0.8 57.5 41.8 0.9 1.0 32.9 24.9 1.0 1.0 CNHM1 29.9 11.1 0.9 0.7 SINP4 27.6 24.1 0.8 0.7 41.2 77.5 0.7 0.6 25.4 21.3 0.8 0.8 CFRI2 27.6 22.7 0.7 0.8 46.2 35.0 0.8 0.7 12.5 19.8 0.4 0.4 MDH3 25.4 25.8 0.6 0.7 7.7 7.3 0.2 0.1 MDF1 25.0 44.6 0.7 0.6 49.3 89.3 0.8 0.8 15.5 32.6 0.6 0.3 FES1 24.5 36.1 0.7 0.6 12.9 15.0 0.6 0.1 MCDNP1 24.5 9.3 0.7 0.6 45.0 55.0 0.7 0.7 19.8 5.03 0.6 0.6 MDF3 23.2 49.5 0.6 0.6 45.0 70.0 0.7 0.7 20.5 40.4 0.7 0.4 APFOA1 20.9 53.5 0.6 0.5 22.5 27.5 0.4 0.3 12.5 17.5 0.5 0.2 SINP6 20.9 51.7 0.6 0.5 CF3 20.5 17.8 0.5 0.6 51.8 33.7 1.0 0.8 35.7 22.0 1.2 1.0 SINP1 17.8 17.4 0.4 0.5 34.3 50.0 0.6 0.5 10.0 28.9 0.4 0.1 CF2 16.0 35.7 0.3 0.5 55.6 40.6 1.0 0.8 10.2 25.3 0.4 0.1 CFRI1 15.6 23.6 0.3 0.4 39.2 10.0 1.3 1.2 MDH2 13.8 7.5 0.3 0.3 34.3 31.2 0.6 0.5 5.2 24.5 0.1 0.1 CUPFOA1 12.9 49.1 0.4 0.4

At T1 the more influential actors were also less prone to being influenced and vice versa. Same pattern exists at T2, but with one big variation; while influential actors CF1 (lead representative of the Croatian Forests Ltd.) and MDF2 (lead representative of the Ministry of Agriculture) have large differences between their outdegrees and indegrees, actors SINP5 and SINP7 have almost the same values of their outdegrees and indegrees. This can be interpreted as the openness of actors SINP5 and SINP7 to influence many different actors, as one actor followed the other in the position of the leader of the working group. On the contrary, the outdegee/indegree ratios found at actors CF1 and MDF2 indicate that they were more focused on influencing other actors. Both positive and negative beta centralities have linearly decreased with the decrease in outdegree, indicating similarity between these two measures of centrality, and that influential

137 actors have equally influenced other influential and not-so-influential actors. Actors from both sectors have been equally distributed across all scales of centrality.

Differences between the centrality measures of influence networks gathered from questionnaires and observations have been tested through the application of Spearman's rank correlation coefficient. The correlations between out-degrees, β+ and β- centralities range between 0.511 and 0.545 (all p<0.05), while for in-degrees they are 0.326 (for T1, p=0.11) and 0.420 (for T2, p=0.048). With the low (0.33) QAP regression scores between the two approaches, all comparisons of networks from these two operationalizations of influence should be taken with caution.

From the Friedkin`s model outdegree centralization has remained relatively constant (from 38% to 35%), whereas the indegree centralization has decreased from 49% to 37%. This indicates that actors` focus of activity has remained relatively constant, but the acceptance of other opinions has spread to a larger group of actors. This is in line with the increase in network density from T1 to T2, and with the overall decrease of normalized outdegree centralities between the same two waves.

5.1.4. Analysis of sub-groups

The purpose of the analysis of sub-groups is to determine the cohesive parts of the network, which can provide indication on whether division of actors by sector of seniority is justified, or to determine grouping patterns that emerge from the data itself. The first step is to look at densities among different grouping criterions. The densities (average strength of ties across all possible ties) according to sectoral division criterion are presented in Table 21, both for the data derived from questionnaires and observations.

Table 21. Density and average tie strength ratio among sectors in different influence networks

Density Questionnaire T1 Questionnaire T2 Observation Nature Nature Nature Forestry Forestry Forestry protection protection protection Forestry 2.48 1.88 4.39 4.62 0.32 0.20 Nature 2.43 3.40 3.10 6.75 0.21 0.22 protection

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The table of network densities by sector reveals that from T1 to T2 the overall densities have increased, and in this context, actors from nature protection are a more cohesive sub-group than it is the case with the actors from the forestry sector. It can also be seen that in the beginning, the actors from nature protection were more influential towards the actors from the forestry sector than vice versa, whereas by the end of the meetings of the working group the nature protection actors became less influential towards the actors from the forestry sector. The operationalization of inter-personal influence from communication patterns shows no differences in the mutual relations between nature protection and forestry sectors, and it shows denser patterns within forestry in relation to influence patterns of the nature protection sector.

The analysis of densities by organizations shows that in absolute terms (number of ties / sum of tie strength) the most pronounced influence was in the direction of the State Institute on Nature Protection towards Croatian forests Ltd. and vice versa, and that in relative terms (proportion of ties / average tie strength) the highest densities of influence relations are found within organizations, both for T1 and T2. The analysis of densities by organizations on influence derived from communication shows similar patterns, with the exceptions that actors from SINP are relatively much less connected within the group (0.2) than it was the case with CF (0.6), and in absolute terms, most inter-personal influence and communication that occurred among organizations was between the members of the State Institute on Nature Protection, Croatian forests Ltd. and the Ministry of Agriculture – Department of forestry.

As reciprocity is on average 0.5 for all observed networks, without dichotomizing and symmetrizing the data, only top-down approaches, components and factions routines have been used (Borgatti et al, 2013). The components routine at T1 shows a single weak component of eleven actors at level six (out of 8), which are also the most influential actors by their outdegrees. The only exception to this is actor FOF1 who is not a member of the group, and had the fourth largest outdegree. At T2 the weak component has increased to incorporate two thirds of actors at the same level. Similar to T1, the components routine on the influence based on communication patterns shows one weak component at level 0.7 (range 0 to 1) made from seven actors, six who have the highest values of outdegrees according to the Friedkin` operationalization of influence.

The factions routine for T1 with two factions produces two groups where one (with 11 actors) has very dense (3.63) network ties within the group, and the other one (with 18 actors) is much more sparse (1.42). The “well connected group” also seldom makes ties to the other group (1.29), which in turn made more connections (2.54) to the well connected group. The categorical core-periphery routine shows very similar results to the factions routine, as it displays same pattern of densities and it removes four actors from the “well connected group” to the periphery (CFRI1, CUPFOA1, FES1 and CFRI2) and moves one to the core (SINP7), thus producing the following core-periphery structure:

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 Core actors: FOF1, APFOA1, MDH1, MDF1, FOF2, SINP2, CF1, MDF2, CFS1, SINP3, MDF3, SINP5, SINP6 and SINP7  Periphery actors: SINP1, CASA1, CFRI1, MDH2, CF2, CNHM1, SINP4, CUPFOA1, FES1, MCDNP1, CFRI2, MCDNP2, CF3, CFRI3 and MDH3

The core group at T1 is equally composed of actors from both sectors and contains majority of the senior actors. The factions routine at T2 for two groups provides different grouping from T1. The first identified group has seven members all from the forestry sector, and it has similar in- group (4.24) and out-group (4.74) densities. The second group comprises of all actors from the nature protection sector, three actors from the Ministry of Agriculture and two from the Croatian Forest Research Institute. The second group has very high in-group density (5.32), and very low out-group density (2.59). All the senior actors except one are in the first group. The categorical core-periphery routine identifies a large 15 member core and a six member periphery where five actors are from forestry and they are also members of the “all-forestry” group from the factions routine. The core periphery density (3.4) and the periphery-core density (3.8) are quite close, which diverges from the findings of the factions routine. Both the factions routine and the categorical core-periphery routine applied at the network of communication based influences, show similar results by identifying one “dense” group (0.40 and 0.52, ) and one “sparse” group (0.19 and 0.07), with sparse connections between them. Both of these groups have representatives from both sectors, but the ‘sparse group’ has only one senior actor. For the network of communication-based influence, the factions and the categorical core-periphery routine place same 18 actors in the same group.

The regular equivalence via REGE algorithm shows similarities in profiles of actors MDF2 and SINP5 (level 96.1), and actors CF1, CASA1 and CNMH1 (level 94.5). Similarity in profiles of actors CF1, CASA1 and CNMH might be regarded as unexpected results, as CF1 is a very influential actor from forestry who has been at all meetings, and CASA1 and CNMH1 are topic- specific nature protection experts. An inspection of their ego network reveals that they have been influenced by few other senior actors, and their out-neighborhood shows that they have influenced almost all other actors. Out-neighborhoods of actors MDF2 and SINP5 shows similar traits, but their in-neighborhoods reveal that they have been influenced by many other senior actors.

As displayed by the factions routines, at T1 there was one group with seniors, and one group with juniors, but at T2 seniors from the nature protection sector joined actors from the forestry sector in one group, whereas majority of the actors from nature protection were marginalized at T2. This kind of behavior actually had negative effect for the nature protection sector, as their relative influence towards the forestry sector has decreased from T1 to T2, which might explain strong increase of in-group density for the nature protection sector. Regular equivalence showed that actors from the State Institute on Nature Protection and actors from the Ministry of

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Agriculture, Department of Forestry play the same role, and that is to connect both sectors; by influencing them and by accepting influence. This constructive role of the State Institute on Nature Protection and of the Ministry of Agriculture is contrasted by the role of the Croatian Forests Ltd. and the scientific organizations of the nature protection sector, both of which act as stakeholders. They have focused on influencing the entire working group, but have accepted inputs only from other actors who share similar opinions. The pronounced role of the representatives of the Croatian Forests Ltd. in communication did not assist them in spreading their arguments in the working group, as with the passage of time their arguments were becoming less accepted by the nature protection sector and more accepted by the forestry sector. The response of the representatives of the Croatian Forests Ltd. was to accept influence just from the actors from the forestry sector, which goes against the general inclination of strengthening ties across sectors.

5.1.5. Network visualizations

Several networks of interpersonal relations have been visualized in NetDraw program, through which many previously analyzed network features can be seen. Visualization of the networks used in this research with fixed positions of actors are presented in Annex VI. The first visualization is Figure 24, which depicts the inter-personal influence relations among the members of the working group at T1, following Friedkin`s (1993) operationalization of influence. Squares (■) represent actors from the forestry sector, and triangles (▲) represent actors from the nature protection sector. The size of squares and triangles reflects the outdegrees (i.e. outgoing influence) of the actors. Lines represent influence relations, and only relations above its mean strength have been presented. The width and color as well as the size of the arrow heads (↕) reflect the strength of the ties (levels 6, 7 and 8). Metric multi-dimensional scaling is used for the layout of the network, where distances between two nodes represent similarity of paths (geodesic distances) that these actors have to all other actors in the network. Orientation of all visualizations has been rotated in such a manner that there are more actors from the forestry sector on the left side. The stress level of the layout is 0.31, which is above the threshold level (i.e. 0.2; Borgatti et al, 2013), so interpretations of distances between nodes should be made with caution.

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Figure 24. Interpersonal influence relations at time 1 (See Table 8, page 76 for acronyms)

It can be seen in Figure 24 that more influential (senior) actors are grouped closer to the center of the graph, whereas less influential (junior) actors are situated in the outer parts of the graph; this is in line with the results of the categorical core-periphery analysis. Figure 24 also places actor SINP3 at the center of the graph, which has not been commented so far. His position is caused by high indegrees coming from both sectors. In the first interview actor SINP3 characterized his role as a mediator in the working group; however, he has only two outgoing ties stronger than the mean value. From his organization at T1 the most prominent role was of SINP5, who was also the leader of the working group. With the exception of SINP3 actor SINP5 is closer to the forestry actors than other actors from the nature protection sector, and has been almost equally influenced by actors from both sectors, which indicates his openness for cross-sectoral dialogue. The actors MDF2 and FOF1 hold similar positions, while actor FOF2 is closer to nature protection than to the forestry sector. This is in line with the previous comments on close ties between the state administration from both sectors and openness of the forest sector`s scientific organizations for cooperation with the nature protection sector. In addition, it can be seen that the most influential actor CF1 has no incoming ties stronger than the mean value, and that most of their influence was disseminated among actors from the forestry sector.

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The state of the inter-personal influence network at the end of the working group (T2) is presented in Figure 25 (MDS layout, stress 0.27).

Figure 25. Interpersonal influence relations at time 2 (See Table 8, page 76 for acronyms)

Actor SINP3 has moved more towards the nature protection sector which has become an even more cohesive sub-group, which is in line with the previously discussed analysis of densities. The new leader of the working group SINP7 is nearly in the same position as the previous leader, SINP5; they have influenced and have been influenced by members of both sectors, and their similarity is in line with the hierarchical clustering of regular equivalence. The role of SINP3 from T1 has passed to another non-senior actor MDF1, who also has high indegrees coming from both sectors (i.e. is strongly influenced by actors from both sectors), and has low outdegrees. With the exception of actor FOF1 who has moved to the right, the “split” of the forestry sector from the structural equivalence onto its “stakeholding” part (CF, CFS, APFOA) and scientific- administrative part (MDF, MDH, CFRI) can be seen. And although CF1 is still the most influential actor and has accepted influence from the nature protection sector (SINP7 and MCDNP2), his outdegrees are at T2 spread mostly within the forestry sector.

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The changes in actors` positions are presented in Figure 26, which shows correspondence analysis of the influence networks from T1 to T2. Correspondence analysis is here used as a network change visualization technique, and it uses singular value decomposition of normalized versions of the data matrices to represent proximity (or “similarity”); of actors, or look at patterns in the data (Borgatti et al, 2013). Figure 26 is not centered. The white squares represent actors from the forestry sector, and the black squares represent actors from the nature protection sector. The lines represent changes from T1 to T2 for senior actors. Actors at T2 have added “2” to their marks (e.g. CFRI1→ CFRI1_2).

Figure 26. Correspondence analysis of influence networks from time 1 to time 2 (See Table 8, page 76 for acronyms)

Correspondence analysis shows that most of the actors from both sectors became closer to each other at T2, which is a constructive argument for cross-sectoral dialogue. It can also be seen that there are only two seniors who diverge from this trend (CF1 and APFOA), whose “stake-holding role” was discussed previously.

A more centralized image of influence relations is derived from communication, where influence has been operationalized as the normalized difference in z-scores between dyadic (speaker and listener in direct eye gaze) and “failed” (listener not looking at the speaker) dyadic

144 communication influence attempts. These influence relations are presented in Figure 27, also in MDS layout (stress 0.29). Only relations above the mean value are shown, and are scaled in three categories (thin grey, thin black and thick black), based on the tie strength. As in previous visualizations squares represent actors from the forestry sector, triangles represent actors from the nature protection sector, and the size of the squares and triangles reflect the total outdegree of actors.

Figure 27. Influence relations derived from communication patterns (See Table 8, page 76 for acronyms)

It can be seen that senior actors CF1, SINP7, MDF2 and FOF1 are placed in the center of the graph and have strong ties between them. Actors CF3, SINP3 and SINP5 are close to the central actors, and all of them have high outdegrees. These are also the actors identified by the factions routine to be part of one group. It can also be seen that although outdegrees of SINP5 and SINP7 are very similar, the new leader of the working group (SINP7) has focused much more on the key actors from the forestry sector than SINP5 did. Actor CF3 holds a unique position of influencing many different actors and having small indegree. This stems from his position of a habitat mapping expert, where there was very little communication directed towards him; rather other actors commented on his findings among themselves (this issue was previously covered on

145 page 133). As the density analysis has previously shown, communication-based influence relations are equally strong within as well as across sectors. Similar to the network of Friedkins` (1993) influence relations at T2 from Figure 25, the communication based influence shows wider group of actors having similar outdegrees. For communication based influence distribution of degrees is determined by treating dyadic reciprocated and “failed” dyadic communication equally, e.g. actor CF1 has communicated much more that CFRI1 did, but as CF1 had much more “failed” outgoing communication than CFRI1, their outdegress are similar. More information is gained by looking at both elements of the communication separately.

Figure 28. Reciprocated dyadic communication (See Table 8, page 76 for acronyms)

Figure 28 demonstrates total “successful” dyadic reciprocated communication from the observations of the meetings of the working group. Layout is metric MDS, with stress 0.37. Communication is in 0-63 range, which marks the number of dyadic reciprocated communication flows. Only levels higher than five are shown and the width of the line and the size of the arrow heads reflect the strength of ties. Although same actors are centrally positioned as in the network of communication-based influence, there are differences in the distribution of degrees. These differences are caused with the level of “failed” communication, which is for

146 example more pronounced for actor SINP5, who has higher outdegree in influence based communication, than in the communication pattern themselves. The same trend is also observed for actor FOF1, whose lower outdegree in communication has placed him farther away from CF1 and MDF2. The position of CF3 is the same in both networks.

The only part of communication and influence relations that is missing thus far is the visualization of communication when the listener was not looking at the speaker (failed communication attempts), which is regarded as an indicator of filed influence attempts. These relations are presented in Figure 29. Layout is also metric MDS (stress 0.36), but unlike all the visualizations so far, it is based on distances, i.e. stronger relation means that the two actors are further apart. Relations are in 0-87 range and are reflected with the width of the lines and size of the arrow heads. Only relations greater than 4 are shown. As in the previous graphs, squares and triangles mark the actors from the forestry and nature protection sector, respectively and their size reflects their outdegrees.

Figure 29. Failed communication attempts (See Table 8, page 76 for acronyms)

It can be seen that with the exception of SINP6 and CFRI3 all other actors have experienced failed communication – based influence attempts, but this kind of communication is strongly

147 focused on the relation between actors from the State Institute on Nature Protection on one side, and actors CF1 and MDF2 on the other. Actors SINP3, SINP5, SINP7, CF1 and MDF2 were also most engaged in the overall communication, but several differences between them can be observed. Actor CF1 has the overall largest outdegree (87), and actor MDF2 has a much smaller one (19). High overall level of communication and low level of instances when his alters were not accepting his arguments have kept actor MDF2 almost equally influential at both sectors in the Friedkin`s (1993) operationalization of influence at the end of the meetings of the working group (Figure 25). The opposite development was with actor CF1. Although he has communicated frequently with members of the nature protection sector and at T2 (partly accepted their arguments), his frequent failed influence attempts towards SINP have made him less influential among actors from the nature protection sector. This resulted more with his re- positioning within the forestry sector at T2 (Figure 25), which is opposite of the general trends in the network (Figure 26; correspondence analysis). Moreover, Figure 29 also shows that SINP5 had declined more influence attempts from CF1 and MDF2 than SINP7 did. As seen in Figure 28 (reciprocated dyadic communication) SINP7 has also focused his communication more than SINP5 did, which in the end resulted in SINP7 being more influential towards key actors from the forestry sector than SINP5. Given the fact that hierarchy is strongly present in both sectors (as seen in the categorical core-periphery analysis on Friedkin`s influence networks) and the large differences in the distribution of outegrees, actor SINP7 was more responsive to the power relations in the working group than actor SINP5. It can also be seen that FOF2 had failed communication influence attempts towards CF1 and MDH2, which is in line with his positioning within the nature protection sector in the network of interpersonal influences (Figure 24).

5.2. Organizational analysis

Data on inter-organizational relations was gained from two waves of questionnaires that have been administered to a total of 43 respondents in the first wave, and 35 respondents in the second wave. The values used in analysis represent the mean values on the level of organization. As was the case in the analysis of inter-personal relations, the basic network parameters for resource flows among organizations in both waves are presented in Table 22.

Table 22. Whole network characteristics of resource flows for T1 and T2

Resource flows All resources Information Human Financial Material

T1 T2 T1 T2 T1 T2 T1 T2 T1 T2 Mean outdegree 22.76 21.32 12.64 11.64 4.84 4.04 2.51 3.05 2.75 2.95 Density 0.67 0.66 0.62 0.62 0.44 0.40 0.22 0.25 0.21 0.20 Reciprocity (%)* 0.66 0.68 0.68 0.67 0.32 0.27 0.07 0.11 0.06 0.05 (dyad based) *percentage of all actual ties that are reciprocated

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Due to the small number of respondents per organizations (2-7) majority of the analysis will focus on the summarized flows of all resource types. Although some differences exist between the two waves of data collection, due to the small number of respondents per organization, these differences can be attributed to the respondent error. For this reason the inter-organizational relations are regarded as stabile within the time frame of this research. Data from the first wave will be used for further analysis, as this data showed more consistency among the responses from the same organization. This can be attributed to the fact that the first wave of questionnaires on inter-organizational relations was administered separately from the questionnaire on inter- personal relations to the members of the working group, whereas the second wave was administered jointly, where respondents had less time for completion. Although before the eleventh meeting of the working group the jurisdiction on nature protection had passed from the Ministry of Culture to the Ministry of Environmental and Nature Protection, for analytical purposes, the Ministry of Culture (MCDNP) remains present in the second wave.

The whole network characteristics shows high density of information flows in comparison to all other types of resources, and there is an emphasized decrease of reciprocity with the decrease in network density, which points to very sparse and hierarchically structured networks of financial and material flows. As the misbalance is more pronounced in hierarchical structures, this highly hierarchical structure indicates a higher validity of results related to power relations (misbalance of resource flows) for a specific type of resource than is the case with results related to other network parameters.

For the network of summarized resource flows the densities (proportion of ties /average tie strength) within forestry sector (F) (2.71) and within nature protection sector (NP) (2.98) are much higher than the ones for forestry to nature protection (0.75) and from nature protection to forestry (1.18). Higher densities within sectors (F 1.30; NP 1.90) and similarly low densities between sectors (F→NP 0.60; NP→F 0.74) are found for the network of information resources and for the network of human resources (F 0.75; NP 0.58; F→NP 0.29; NP→F 0.33). Higher densities within sectors are also found for the financial (F 0.44; NP 0.27) and material resources (F 0.36; NP 0.6) then between sectors, where there are no relations from the forestry to nature protection sector for both resource types. All the flows of financial (0.09) and material resources (0.07) that occur from the nature protection to the forestry sector are related to the Croatian Forest Research Institute and the Faculty of Forestry, University of Zagreb.

The hierarchical clustering of structural equivalence via profile similarity with correlations on the level of 0.234 differentiates the network on two groups which correspond to the sectoral division of the network. On the level 0.607 of profile similarity, the private forestry organizations (CUPFOA, APFOA and FES) are seen as separate entities from the rest of the forestry sector. CUPFOA and FES are also grouped together in the hierarchical clustering of regular equivalence via REGE algorithm on the level of 90.9. The same level groups CFRI and

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FOF, both of which are scientific organizations of the forestry sector. The components routine identifies two weak components at the level of 3.5 (maximum 10.5): APFOA, CUPFA and FES in one component, and SINP, MCDNP, CFRI, CFS, FOF, CF and MDF is in the other component. The grouping of associations of private forest owners with their administrative counterpart in the first component is an expected finding. The factions routine with two components separates the network on one sparsely interconnected (1.10) group (CFS, CASA, MDH, CNHM and MCDNP) and one strongly interconnected (2.73) group (CUPFOA, SINP, CFRI, CF, MDF, APFOA, FES and FOF) with intermediate densities of intergroup relations (1st → 2nd 1.44; 2nd →1st 1.57). With the exclusion of association of private forestry organizations (APFOA, CUPFOA and FES) the remaining members of the group constitute the highly-dense (3.87) core in the categorical core-periphery test. These organizations are also in the intersection of the second group from the components analysis and the strongly interconnected group from the factions analysis. Based on these tests, the network can be split into “core” organizations (SINP, CFRI, CF, MDF, FOF), organizations of private forestry (APFOA; CUPFOA and FES), and the “peripheral” organizations (CASA, MDH, MCDNP, CNMH, CFS).

When power is operationalized as the misbalance in resource dependencies on a dyadic level (to a 0-1 scale; Pfefer and Salancik, 1978) the density-by-sector analysis shows relatively higher relations among sectors (F 0.40; NP 0.50; F→NP 0.28; NP→F 0.33) then it was the case in the density analysis of all resource flows. Other categorizations of organizations on cohesive subgroups (factions, components) and roles (structural and regular equivalence, categorical core- periphery analysis) show similar results and point to the same final grouping of organizations. The degree centralities for both operationalizations of interorganizational power are presented in Table 23.

Table 23. Centrality measures in organizational network

Power as resource dependence Power as difference in r.d. Out- In- Norm. Norm. Out- In- Norm. Norm. ORGANIZATIONS degree degree β+ β- degree degree β+ β- CF 50.3 18.0 1.9 1.9 5.9 2.1 1.2 1.3 FOF 35.6 35.0 1.4 1.3 5.0 4.9 1.1 1.0 MDF 34.4 25.6 1.3 1.2 6.1 4.8 1.2 1.4 SINP 30.1 33.8 0.9 1.3 5.7 6.2 1.1 1.3 CFRI 28.9 37.5 1.1 1.1 4.8 5.1 1.0 1.1 MCDNP 24.9 18.0 0.8 0.9 5.5 4.4 1.2 1.1 FES 20.3 34.5 0.6 0.9 3.4 5.5 0.8 0.6 CFS 20.0 39.5 1.0 0.4 3.5 6.4 0.8 0.7 MDH 16.2 16.5 0.6 0.5 4.4 4.5 1.0 0.8 CNHM 10.4 2.0 0.3 0.3 3.6 2.3 0.8 0.6 CUPFOA 9.5 15.5 0.3 0.3 2.0 2.9 0.5 0.3 CASA 8.3 9.0 0.3 0.3 2.9 3.0 0.6 0.6 APFOA 6.7 11.0 0.2 0.2 3.6 4.3 0.8 0.7

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When power is operationalized as resource dependence CF, FOF, MDF and SINP are the most powerful organizations with respect to outdegrees, while CF also has low in-degrees in comparison to other powerful organizations. Decrease in normalized Bonachich`s β+β- centralities follows the decrease of outdegrees, with exceptions of SINP which is more connected to the not-so-powerful organizations, and CFS who is more connected to the powerful (CF) organizations.

When power is operationalized as the difference in resource dependencies (“net resource flows”) it can be seen that a large portion of resources distributed in the network by Croatian Forests Ltd. was within inter-dependent relations. The Ministry of Agriculture, Department of forestry however has distributed most of its resources within relations that have low reciprocity, and thus has highest net-score of resource dependencies (i.e. highest outdegree). The State Institute on Nature Protection comes close to the outdegree score of Croatian Forests Ltd., and in terms of resource dependence operationalization of power (“total resource flows”), it has balanced outdegrees and indegrees. Although being the central organization in Croatian forestry with 9000 employees and managing 1.9 million ha of forest land, CF is not very resource-dependent on the network, which can also be interpreted as an attribute of its inter-organizational power.

Following Brass and Burkhardt (1993) and Borgatti (2005) different centrality measures have been used for different types of resources. All three types of centralities were analyzed for information and financial resources, while for human and material resources closeness and betweeness centralities were analyzed. All closeness and betweeness centrality scores were based on networks that have been dichotomized on the level of the mean strength of ties.

The degree based centrality of information resources does not diverge from the overall network of resource flows. Closeness centrality (geodesic paths), as a measure of avoiding control of others in the context of resource dependence framework (Brass and Burkhardt, 1993), shows that information shared by Forest extension service (FES) can most easily reach all other organizations in the network. On the contrary, the path for information to reach the APFOA and CNMH from the rest of the network is long (10% of maximum in-closeness). Betweeness centrality, as an indicator of increasing dependence of others on the focal actor (Brass and Burkhardt, 1993), shows that SINP and MDF have high potential for increasing their power, but overall network centralization is low (17%), which gives little weight to the results. When centrality is observed as “net-resource flows” (Pfeffer and Salancik, 1978) the high out-closeness of FES decreases (to 19%), indicating that most of the information flows that FES has are with mutually dependent organizations. The degree centralities of “net-resource flows” follow the distribution of degree centralities of overall resource flows, while conclusions on betweeness centrality cannot be made due to low overall centralization of the network (11%).

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Human resources of the Ministry of Agriculture with its two departments (MDH and MDF) will not easily reach all other organizations in the network, as their in-closeness (23%) and out- closeness (26%) is lower than it is the case of other organizations. Closeness centrality on “net resource flows” shows high centrality of actors who have high overall degree centralities, and it also marginalizes the Croatian Academy of Sciences and Arts and the Croatian Natural History Museum, which have very low in-closeness (10%) and out-closeness (10%) centrality. The network centralization of net flow of human resources (32%) is higher than all other analyses, and it shows strong centrality of CF and CFS (32%). Since the Croatian Forestry Society (CFS) is an association of engineers and technicians of forestry and wood processing with majority of its members being employed in the Croatian Forests Ltd., it can be stated that CF is the most central organization in the network of human resource flows.

The degree distribution of overall financial resources and net financial resources follows the distribution of the degree centralities of overall flow of resources, where CF has highest outdegree. Financial resources are also where most of the dependencies of FOF and CFRI are situated, as they have a ratio of 1:4 of their out and in degrees, both for the overall and net financial resource flows. CF and MDF have highest out-closeness centralities, while CFRI has highest in-centrality, both for overall and net flows of financial resources. No conclusions could be made on the betweeness centrality due to very low centralizations (1% and 2%) of the networks of overall and net flows of financial resources.

Both overall and net flows of material resources show that CFRI and FOF have highest in- closeness centralities, and that MDF, CF, MCDNP and SINP have highest out-closeness centralities. No conclusions could be made on the betweeness centrality due to very low centralizations (1% and 1%) of the networks of overall and net flows of material resources.

The analysis of flows of specific resource flows shows that MDF and SINP are most central in the network of information flows, while FES can disseminate information most easily within the forestry sector (mainly due to its connections with the associations of the private forest owners). Network of human resource flows is where CF is most powerful, but it is also where the Ministry of Agriculture is marginalized. Centrality patterns in flows of financial and material resources are quite similar, and they show very high dependence of FOF and CFRI, both of which draw their resources from many sources. As expected the flows of financial and material resources show the dominance of state administration and its expert/implementation counterparts, i.e. MDF, CF, MCDNP and SINP, as central in the overall flow of resources.

Figure 30 shows the network of overall inter-organizational resource flows. Resource flows with lower than mean strength are represented with grey line, and above the mean strength resource flows are presented with black lines. Size of the arrow head represents the strength of the resource flows. Grey squares represent the organizations of the forestry sector, while the grey

152 triangles represent the organizations of the nature protection sector. The size of squares and triangles reflects the total outdegree of organizations. Metric multi-dimensional scaling is used for the layout of the network, where distances between two nodes represent similarity of paths (geodesic distances) that these organizations have to all other organizations in the network. The stress level is 0.23, which is somewhat above the threshold level (i.e. 0.2; Borgatti et al, 2013), so interpretations of distances between nodes should be made with caution.

Figure 30. Network of inter-organizational resource flows (See Table 8, page 76 for acronyms)

It can be seen that organizations of private forestry (FES; CUPFOA and APFOA) are closely related in mutual dependent relations. Although all three have ties to similar others, due to its connection with SINP Alliance of Private Forest Owner`s Associations which plays a different role and is less embedded in the forestry sector, is consistent with the analysis of structural and regular equivalence. Although factions analysis has split the network according to sectors, Figure 30 places MDH between the two sectors. It can also be seen that the powerful Croatian Forests Ltd. (CF) is strongly embedded within the forestry sector, and has ties with mutually dependent organizations, which is consistent with the large difference between outdegrees in two operationalizations of inter-organizational power. MDF on the other hand has ties to all other organizations in the network; however, none of its ties with the nature protection sector are of higher than average strength. A strong one-directional tie between sectors exists from SINP to

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CFS, which has much higher overall indegrees than outdegrees and thus qualifies to the previously identified “periphery” group. It can also be seen that if the relation of ties is set aside, the “core” organizations of the forestry sector (MDF; FOF; CF and CFRI) form a clique with over-the average strength of relations. A high level of mutual inter-dependence between state administration and its expert / implementation counterparts can be seen between MDF and CF from one side and between MCDNP and SINP on the other. This relation is in accordance with the assumptions of resource dependence framework (Pfeffer and Salancik, 1978), and is most visible in the flow of information resources.

It was previously stated that this research assumes that members of the working group act as agents of their organizations. This assumption was tested by using QAP correlation between different inter-personal relations of senior members of the working group and two operationalizations of inter-organizational power. Table 24 provides the results of this analysis, all of which are significant at level 0.01.

Table 24. Correlations between inter-personal and inter-organizational relations

Influence Influence Influence Inter-personal Friedkin Friedkin observation sum communication sum T1 T2 Overall flow 0.43 0.46 0.27 0.19 Net flow 0.32 0.12 0.09 0.12

It can be seen that there is a moderate correlation between network of the overall flow of inter- organizational resources and the networks of inter-personal influence. An unexpected finding is that the correlations between inter-organizational and inter-personal level on the first and the second wave are very close, indicating that most of the inter-personal relations have been pre-set in the first wave. The correlations in all other relations are low, indicating that there is little or no association of net resource flows among organizations with inter-personal level, and that there is little association of overall resource flows among organizations with communication patterns of the working group. However, results do point to association between Friedkin`s (1993) operationalization of inter-personal influence and overall inter-organizational resource flows, both of which are going to be used in the Friedkin and Johnsen`s (1997) model of opinion change.

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5.3. Modeling opinions change

5.3.1. Individual level

Different networks of inter-personal influence and of inter-organizational power have been used to model the change of opinions from the first to the second wave of data collection, all within the Friedkin and Johnsen`s (1997) model. The model is based on the data derived at the onset of research (T1) and used to predict the outcome opinions (T2). Actual outcome opinions of the members of the working group are also collected and compared to the predicted ones. The alpha coefficient of social influence, which determines the relative weight of exogenous and endogenous factors on the formation of opinion, is not equal for all actors. Rather, respondents were asked “How much do you feel pressure to reach a consensual decision?” on a five point ordinal scale. The answers were scaled to 0-1 range, which represents the individualized alpha coefficients. Alpha coefficient is the same for most actors, as the mode and median value is 0.75, and the mean is 0.65. Outdegree values of inter-personal influence which have been used in the Friedkin and Johnsen`s (1997) model are presented in Table 25 (where value of 1 represents the total value of influence that one individual receives).

Table 25. Inter-personal influence values for the Friedkin and Johnsen`s model

Influence Influence Actor Actor value value SINP5 3.047 FES1 0.707 CF1 2.334 MCDNP1 0.676 FOF1 2.133 MDF3 0.667 SINP7 2.025 SINP6 0.636 MDF2 1.900 MDF1 0.614 FOF2 1.354 CFS1 0.588 MDH1 1.240 APFOA1 0.543 SINP2 1.212 MDH3 0.518 CASA1 1.191 CF2 0.440 SINP3 1.124 CF3 0.373 MCDNP2 1.084 CFRI1 0.358 SINP4 0.932 CUPFOA1 0.344 CNHM1 0.869 SINP1 0.247 CFRI2 0.830 MDH2 0.192 CFRI3 0.819

Reciprocal values of scores from several questions have been used in analysis, where now 0 represent “extreme forestry opinions”, and 1 represents “extreme nature protection opinions” for all questions. There is a significant difference (p<0.001 at Mann Whitney U test) between the

155 opinions of forestry and nature protection members of the working group, both at T1 and T2. Differences between opinions in T1 and T2 have been tested with usage of the Spearman's rank correlation coefficient, which for comparison of opinions on all topics is 0.535 with p=0.000. The median and the mode change from T1 to T2 is 0.125, which is one point in the ordinal scale by which the answers were achieved.

Changes of opinions from wave 1 were tested on the network of interpersonal influences (Friedkin, 1993) through the Friedkin and Johnsen model for the long-term equilibrium opinions. Differences between actual opinions at T2 and the ones defined by the Friedkin and Johnsen model have been tested with usage of the Spearman's rank correlation coefficient, which for comparison of opinions on all topics is 0.713 with p=0.000. This indicates that the modeled opinions are better predictors of the outcome opinions than are the initial opinions. The median difference between actual opinions and the predicted ones is 0.11. The biggest differences between the actual and predicted opinion lies with the most influential actors (0.32; 0.23; and 0.23), which implies that the alpha levels for influential actors have been set too high, as they have to a large extent kept their initial opinions. In order to improve the predictions of the Friedkin and Johnsen model alternative operationalization of the alpha coefficient has been constructed. This operationalization is based on social power attributes of members of the working group. Following the review of Brauer and Bouhoris (2006) a total of 16 codes related to social power have been constructed, and all the interviews with the members of the working group have been re-coded based on these social power codes, which have been assigned a total of 1295 times. They have been rescaled to 0-1 range where 0 represents the most powerful actor. When this alternative operationalization of the alpha coefficient was used in the Friedkin and Johnsen model the mean difference between the predicted and the observed opinions for the most influential actors has decreased to 0.14, the median difference was 0.19 and the Spearman's r was 0.499. This made the primary operationalization (pressure for consensus) of the alpha coefficient more appropriate for further analysis.

When asked for their opinions on the discussed issues, the respondents were asked after each of these questions the following question: “To which extent is the issue addressed by this question implemented as a result of the working group?” The mean answer of all the respondents was regarded as the level of implementation of that issue. As the documentation which the working group has produced does not provide a clear-cut way to operationalize implementation for all the issues, this respondent-driven approach to defining implementation was taken. An example of this ambiguity is question 1 – the presence of deadwood in forest habitats. Although management measures for forest habitats have not been defined by the working group, the working group has defined management measures for insect species Rosalia alpina, Morimus funereus, Morimus asper funereus, Lucanus cervus and bird species Strix uralensis, Dendrocopos medius, Picus canus, Ficedula albicollis, Strix uralensis, Aegolius funereus, Dryocopus martius, Picus canus, Ficedula albicollis, Picoides tridactylus, Dendrocopos leucotos

156 and Glaucidium passerinum, all of which require presence of deadwood in their habitats, and the Natura 2000 areas (pSCI`s) set for these species cover large portion of forest habitats in Croatia. The mean answer of the respondents on the level of implementation of this measure was 0.47, which is approximately in line with the actual situation. On question 4 (protection in the category of special reserve) respondents` mean answer was 0.14 – and there is no mention of this measure in the outputs of the working group. Regarding question 5 (protection ‘Spačva Basin`s’ forest habitats) the mean respondents` answer was 0.34; the actual situation is that about 15% of Spačva`s forest habitats have been selected as Natura 2000 sites, whereas the entire Spačva Basin was selected as (SPA) area for the protection of numerous bird species. In reference to question 6 (interventions into populations of strictly protected species) the mean answer was 0.5; this is an actual match to the actual situation as in the outputs of the working group both opinions (it is allowed / it is not allowed) are written. These examples show that although a respondent bias is present, it does provide an approximation of the actual level of implementation. Mean opinions by sector at T1, calculation of T2, actual opinions at T2 and opinions of sectoral “leaders” (two actors per sector with highest influence outdegrees) are presented in Figure 31.

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Figure 31. Change of opinions within the working group

The opinions of sectoral leaders were presented for T2. For questions 1-8 the same vertical line marks (with the dot) the level of implementation of issues addressed by the respective questions within the working group. It can be seen that there exists a general trend of change of opinions from the ends of the scale to its center, although the opinions of the two sectors never meet. The

158 opinions came very close at question 6, which was the only question related to management of specific species and thus it was not of great interest to the majority of the members of the working group. It can also be seen that the predicted outcome opinions are too consensus- oriented, which indicates that the overall alpha coefficients have been set too high. Figure 31 also demonstrates that in eight out of nine questions forestry leaders had more “extreme” opinions from the rest of the members of their sector, and that in the case of the nature protection sector the same situation occurred only three times. Bearing in mind that the majority of the communication within the working group took place between several influential individuals and the fact that forestry leaders at T2 had higher outdegrees than the nature protection leaders did, these relations in opinions and influence might explain the fact that the implementation level is for five issues (Q1, Q3, Q4, Q5, Q7) closer to the forestry position, on two issues it is in between sectoral positions (Q2, Q8) and on only one issue (Q6) it is closer to the position of the nature protection sector.

It can also be detected that the opinions on “more important” questions (Q3, Q9) are more diverse between sectors and have altered less from T1 to T2 than it is the case of “less important” (Q1, Q6) questions. This is in line with the Advocacy coalition framework (Sabatier and Jenkins- Smith, 1993), according to which “An actor or coalition will give up secondary aspects of a belief system before acknowledging weaknesses in the policy core” (Hypothesis 3; Jenkins- Smith and Sabatier, 1994).

5.3.2. Organizational level

The network of inter-organizational resource flows has been used to assess the change of organizational opinions on the issues discussed by the working group. The objective of the analysis is to assess to which extent the organizational opinions are aligned to the equilibrium opinions with respect to inter-organizational relations, and to find out to which extent the opinions of the representatives of influential organizations in the working group are aligned with the central opinions of their organizations. Analysis is performed on the data from the first wave (T1-ORG), which is drawn from responses of 29 members of the working group and from 14 key informants, who are high-ranking members of their organizations. Data from the second wave was received by just six key informants out of the working group, which is a marginal increase of data. As the focus is on the working group, just the opinions of the members of the working group at T2 have been taken into consideration (marked with T2-WG in Table 26). The key informants were reluctant to complete the same questionnaire in the second wave; the majority of cases provided an explanation that there was very little change from the previous questionnaire

159 conducted the year before. This issue was previously addressed in detail in the section Methodological approach.

The differences and correlations of the opinions from T1-ORG with its equilibrium calculations and the outcome opinions within the working group are presented in Table 26.

Table 26. Differences between various opinions at organizational level T2-ORG CALCULATIONS T2 - alpha WG 0.25 0.5 0.75 1 T1-ORG Correlation* Spearman`s rho 0.977 0.965 0.908 0.686 0.597 T2 - WG Correlation* Spearman`s rho 0.539 0.567 0.419 0.293

*all correlations are significant at 0.001 level

It can be seen that the correlation between opinions of central organizational opinions at T1 and the outcome opinions of the members of the working group is 0.597. This is a significant result, but not as explanatory as the inter-personal model (correlation of 0.713) from the previous analysis. It can also be noted that, until the inter-organizational relation are at their full effect with α=1, there is very little difference between T1-ORG and the equilibrium opinions. In addition, the equilibrium organizational opinions are actually less explanatory than it was the case with the organizational opinions in the first wave. When analyzed more closely, a pattern in the error can be noticed; the more respondents per organization were interviewed at T2, the lesser was the deviation of that opinion from the calculated equilibrium opinion. Examples of that pattern with α=0.5 are: SINP with six respondents has mean deviation of 0.08, CF with three respondents has 0.1, MDH with two respondents has 0.18, and APFOA with one respondent at T2 has mean deviation of 0.23. As the same pattern emerges with other α values, the further application of Friedkin and Johnsen`s model on the organizational level is focused on just four influential organizations that also had the biggest number of their representatives at the working group: MDF, CF, MCDNP and SINP. Focusing just on these four organizations brings more validity to the results, which in Figure 32 are presented in summarized form for all nine questions.

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Figure 32. Changes in organizational opinions by Friedkin and Johnsen`s (1997) model

With the minor exception of MCDNP and SINP at T1-ORG it can be seen that the opinions of the state administration (MCDNP and MDF) are more moderate than the opinions of their expert / implementation counterparts (SINP and CF). This difference is in accordance with the propositions of the Advocacy Coalition Framework (Sabatier and Jenkins-Smith, 1993). It can also be seen that the equilibrium organizational opinions in the forestry sector are closer to the stated opinions at T1 than it is the case of organizations in the nature protection sector. Moreover, the change from T1-ORG to T2-WG is smallest for Croatian Forests, Ltd, similar for the State Institute on Nature Protection and the Ministry of Agriculture, Department of forestry, and is strongest for the Ministry of Culture, Department for Nature Protection. This rate of change follows the distribution of the organizational outdegrees from Table 23.

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5.4. Longitudinal network models

Longitudinal network models of inter-personal influence have been designed in order to analyze which factors led to the change in influence relations, and co-evolution models of influence (network) and opinions (behavior) have been designed to analyze the interaction between influence and opinions. Analysis has been performed with the RSIENA program. The data for the analysis originates from the questionnaires given to the members of the working group, which were collected at the time of the third meeting (T1) and after the eleventh, final meeting (T2). As members of the working group have been meeting out of its formal setting in smaller groups with different compositions to discuss the same issues as in the formal meetings, the attendance to formal meetings does not reflect a valid composition change in the network. Following this line of thought, for analytical purposes the composition of the network is regarded as constant.

As stohastic actor oriented network models assume that actors have control of their outgoing ties, the influence networks from Friedkin`s (1993) model have been transposed so that the outgoing tie represents alter`s influence over ego, and not vice versa. The same approach was followed in the data collection; as the actors have control whom they are influenced by and not whom they influence. This is analogous to the networks of friendship ties, where people can nominate whom they consider a friend, and not who considers them as a friend (e.g. Cheadle and Schwadel, 2012; Cheadle and Williams, 2013; Preciado et al, 2012; Gesell et al, 2012).

As influence relations from the Friedkin`s model are valued (0-8) range, the first step in the analysis is the dichotomization of data. Figure 33 shows histograms for influence relations at T1 and T2.

Figure33. Histogram of influence values (0-8 range) at time 1 and time 2

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It can be seen on Figure 33 that at T1 distribution of influence relations resembles a normal distribution, and that at T2 it becomes negatively skewed. At T2 it can also be seen that there is a transition in the frequencies between tie strengths 3 and 4, and again between tie strengths 6 and 7. The findings of the section 5.1.4 (Analysis of subgroups, p.136) and the visualization of the influence network at T2 (Figure 25, p.143) indicate that influence ties of strength 7 and 8 are mostly distributed between influential actors. With these arguments two dichotomization thresholds are selected; first where values larger than three represent a tie (Model 1), and second where values larger than six represent a tie (Model 2). Dynamics of influence networks in Model 1 and in Model 2 have been analyzed using the same set of effects which represent different structural characteristics and attributes. Sectoral division of organizations from which members of the working group come from has been included in the models, where 1 was used to mark the forestry sector and 2 to mark the nature protection sector. Senior actors were coded with one, while other actors have been marked with 2. As inter-organizational relations are considered to be constant for the analytical purposes, the model for the dynamics of inter-personal and inter- organizational networks has not been constructed; rather the organization-related variables have been included in the inter-personal model. Each actor has been marked with the code of its organization, and the “organizational power” of its organization, which was operationalized as the sum of all outgoing resources in the network (outdegree) of that organization, scaled from 0- 100. This simplified proxy of the organizational power was added to the model as a constant actor covariate. The outdegree is not adequate to represent inter-organizational relations on its own due to the fact that the majority of resource flows in the network have been reciprocated, and mutual dependence may cause different inter-organizational relations from the sum of resource flows (Casciaro and Piskorski, 2005). For this reason, a constant dyadic covariate has been added, which represents mutual dependence of organizations from which the actors come from, scaled to 0-100 range. The basic changes in influence relations have been presented in Table 27, with the densities of influence relations presented in Table 28.

Table 27. Changes in influence networks

Change 1 ==> 2 for variable 0 => 0 0 => 1 1 => 0 1 => 1 Distance Jaccard Missing Model 1 (ties 4-8) 159 144 38 174 182 0.498 84 (14%) Model 2 (ties 7-8) 383 80 10 43 90 0.323 84 (14%)

Table 28. Densities of influence networks

Model 1 (ties 4-8) Model 2 (ties 7-8) Wave wave 1 2 1 2 Density 0.408 0.617 0.095 0.238 Av. degree 9.80 14.82 2.228 5.713

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It can be seen from Table 27 that more ties have been created than dissolved in both models, and that this change is more pronounced for strong ties (Model 2). The level of change between the states of network in time 1 and time 2 is relatively low (0.489) for Model 1, while for Model 2 it is approaching the threshold value of 0.3, where values of Jaccard index below 0.3 for the difference between two consecutive waves violate the assumption of gradual change. The 14% of missing data in both networks is attributed to the actors at wave 2 who did not wish to fill in part of the questionnaire on inter-personal relations saying that not much has changed from wave 1. From Table 28 it can be seen that both densities have increased from wave 1 to wave 2. It is also important to state that, when compared to other applications, the densities in Model 1 are unusually high; however it can be explained by the closed formal setting of the working group, which has practically provided an interaction opportunity between the majority of its members. The parameter estimates of Model 1 and Model 2 are presented in Table 29. Both models have been implemented with 3000 iterations in phase 3 of the Sinena07 estimation process.

Table 29. Models of influence dynamics Model 1 (tie strength 4-8) Model 2 (tie strength 7-8) Estimate Standard Sign. Estimate Standard Sign. error error Influence_1 1. Rate 12.791 1.239 *** 14.902 2.522 *** 2. Outdegree (density) -0.239 1.920 -1.891 0.340 *** 3. Reciprocity 0.608 0.309 ** 0.243 0.264 4.3-cycles 0.252 0.076 ** 0.168 0.106 5.Transitive ties -1.226 1.205 1.136 0.355 ** 6. Same sector -0.229 0.219 0.045 0.177 7. Seniority alter -0.920 0.300 ** -0.662 0.187 *** 8. Seniority ego 1.467 0.403 *** 0.726 0.211 *** 9. Same seniority -0.343 0.174 * -0.301 0.180 + 10. Same organization 1.786 0.554 ** 1.197 0.316 *** 11. Organizational power alter 0.012 0.005 * -0.001 0.004 12.Organizational power ego -0.011 0.005 * 0.000 0.004 13. Mutual organizational dependence 0.014 0.004 ** 0.008 0.003 *

+p < 0.1 * p < 0.05 ** p < 0.01. *** p< 0.001 Both Model 1 and Model 2 have converged as all t-ratios for deviations from targets are smaller than 0.1. The rate functions are significant in both models and have similar parameter estimation, meaning that during the meetings of the working group its members had 12-15 opportunities to change their network status. The outdegree effect is significant and negative in Model 2, indicating pronounced costs for creation of a tie. The reciprocity effect is positive and significant in Model 1, but is not significant at Model 2. This is an expected finding, as it can be stated that

164 on overall, influence relations tend to be reciprocal (Model 1), but not in the case with strong influence relations (Model 2). In Model 1 the three-cycle effect is positive and significant, but it is not significant in Model 2. The opposite situation is with the transitive ties effect, which is positive and significant in Model 2 but is not significant in Model 1. As a negative sign of a three-cycle effect and a positive sign of a transitive ties effect point to local hierarchical structure, there is an indication of non-hierarchical local structure in Model 1 and hierarchical local structure in Model 2. However, as only one of these effects is significant in each model it can be stated that the results with respect to local hierarchy are inconclusive. Affiliation to same sector does not have a significant effect on influence relations, which is complementary to the findings from the analysis of the subgroups (p.136). Both models show importance of seniority, as actors tend to be less influenced by alters who are junior (negative and significant seniority alter effects), and are prone to be influenced more if they are not seniors (positive and significant seniority ego effect). There is also marginally significant indication that actors do not tend to be influenced by alters from the same level of seniority (negative same seniority effect). All of the above indicates that influence relations in both strengths tend to occur from senior towards junior actors. Same organization effect was highly significant and positive, indicating that influence relations tend to occur between members of the same organization. Complementary to the previous propositions on the relations between the organizational and individual level in Model 1 is the positive parameter estimate and significance of organizational power alter effect, and the negative and significant organizational power ego effect. The results also demonstrate that organizational power does not have an effect on influence relations when strong ties (Model 2) are concerned, but that mutual organization does affect influence relations regardless of the strength of ties.

Up to this point, analysis assumed that similarity between actors stems from the influence relations through which they are interconnected. However, due to the simultaneous changes in opinions and influence relations assuming attribution of social influence (i.e. effect of influence network on opinion) to social selection (i.e. effect of opinions on influence network) might lead to wrong conclusions on behavioral dynamics (Steglich et al, 2010). For this reason, a co- evolution model of influence (network) and opinion (behavior) has been constructed. The operationalization of influence in the co-evolution models is the same as in the network dynamics models, where influence relations have been dichotomized on two levels; Model 1 (levels 4-8) and Model 2 (7-8). The operationalization of behavior began by calculating mean actor`s opinion on all nine issues, scaled from 0 to 100, where 0 represents “extreme” position of the forestry sector, 50 represents intermediate position, and 100 represents the “extreme” position of the nature protection sector. From wave one to wave two 11 actors have decreased their values of opinions, 13 actors have increased their values of opinions and one actor`s opinion has remained constant. In absolute terms total decrease of opinions is 128, and total increase is 157, where the mean value increased from 45 to 46, and the standard deviation

165 decreased from 24.3 to 15.8. This indicates that in most cases the more “extreme” opinions came closer to the midpoint of the scale, which was more thoroughly analyzed in the application of the Friedkin and Johnsen`s (1997) model. This is also evident from Figure 34, which shows histograms for opinions at T1 and T1.

Figure 34. Histograms of opinions at time 1 and time 2

It can be clearly seen on Figure 33 that distribution of opinions at T1 was separated in two groups and that at T2 there is a tendency towards central values of opinions. The opinion variable has been rescaled from 0-100 scale to 1-10 scale, where one represents 0-10 range (“extreme” position of the forestry sector) and ten represents 91-100 range (“extreme” position of the nature protection sector). The re-scaling has been performed as a smaller number of categories are more “fitting” to SIENA analysis of selection and influence. The results of the co- evolution model are presented in Table 30.

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Table 30. Co-evolution models of network and behavior Model 1 (tie strength 4-8) Model 2 (tie strength 7-8) Estimate Standard Sign. Estimate Standard Sign. error error Network dynamics 1. Rate 12.733 1.511 *** 15.039 3.600 *** 2. Outdegree (density) -1.027 3.137 -1.819 0.374 *** 3. Reciprocity 0.642 0.315 * 0.235 0.305 4.3-cycles 0.239 0.093 ** 0.146 0.111 5.Transitive ties -1.233 1.265 1.267 0.594 * 6. Same sector -0.403 0.435 0.206 0.557 7. Seniority alter -0.957 0.374 ** -0.612 0.193 ** 8. Seniority ego 1.499 0.621 * 0.717 0.252 ** 9. Same seniority -0.350 0.194 + -0.312 0.175 + 10. Same organization 1.766 0.579 ** 1.251 0.621 ** 11. Organizational power alter 0.013 0.005 * -0.001 0.004 12.Organizational power ego -0.010 0.005 + 0.000 0.009 13. Mutual organizational dependence 0.013 0.004 ** 0.009 0.004 * 14. Opinion similarity 0.743 1.134 -0.600 0.896

Behavior dynamics 1. Rate 2.376 1.026 * 1.848 0.914 * 2. Linear shape 0.097 0.334 0.453 1.024 3. Quadratic shape -0.270 0.315 -1.263 3.155 4. Total similarity 0.301 1.037 -4.591 10.859 5. Effect from sector -0.080 1.190 0.373 3.542 +p < 0.1 * p< 0.05 ** p< 0.01. *** p< 0.001.

The co-evolution models have converged as the two convergence t-ratios are smaller than 0.1. The rate parameter estimates are significant in both models, both for the network and behavior. The effects of network dynamics in the co-evolution models are very similar to the ones from the models of network dynamics; outdegree is negative and significant in Model 2, three-cycles are positive and significant in Model 2 while transitive ties are positive and significant in Model 2. The co-evolution model shows same results with respect to seniority, as influence relations tend to occur from senior towards junior actors. Effects of organizational power are significant in co- evolution Model 1, but mutual organizational dependence affects influence relations regardless of the strength of a tie. The effect of opinion similarity in the influence dynamics is not significant, indicating lack of evidence for the presence of a social selection process.

Although the rate parameter is significant for behavior dynamics, its other effects are not; as such, the co-evolution models used in this research provide little evidence on the behavior

167 dynamics. The parameter estimates for the linear shape are not close to zero (which implies a “drift” toward the midpoint values of the opinion range) and are not significant. Expected negative estimate of the quadratic behavioral shape effect, which indicates a preference for the linear behavioral shape effect, is also not significant. The total similarity effect is also not significant, which points to lack of support for the presence of social influence (i.e. effect of influence network on opinion) process. The effect of sectoral affiliation (a major explanatory variable in the application of Friedkin and Johnsen`s model) on opinion dynamics was also found to be not significant. Other theory-driven effect that would test the impact of network on behavior such as average similarity, total similarity x popularity and its control effect popularity of alters on behavior were not significant. The effect of indegrees on behavior was not used, as both influential and not so influential actors have opinions on both parts of the opinion scale, which would make the interpretation of that effect very difficult. Additional effect of affiliation to state administration was made, but it (also with interaction to sector) did not have a significant effect on behavior dynamics. As inclusion of these effects violates the overall convergence of the co-evolution model, they were not included in the results. Setting the initial parameter values to the estimated ones did not improve the convergence of the model to the observed values.

6. DISCUSSION

Results have shown that the working group was characterized by very dense (0.78 at T2) network of inter-personal relations, most of which were reciprocated. However, with the passage of time and with the increase of the strength of the influence relations the network became more centralized, and more dominated by non-reciprocal hierarchical relations. Hierarchy in influence relations according to seniority was also evident, and was even more pronounced in actual communication patterns which were dominated by few key actors. However this development had positively affected cross-sectoral dialogue as most of these senior actors were more open to influence from other sectors than it was the case in the first wave of data collection. The exceptions to this trend were the seniors from the “more stake-holding” organizations who moved their ego networks further within the forestry sector by the end of the meetings. Some indication on why this has occurred is found in the data that they have reported, as in the first wave they were much less open to influence from the nature protection sector than it was the case with the state administration or the scientific organizations from the forestry sector. Other indication is found in the communication patterns where frequent discussion combined with frequent failed communication influence attempts have led to their lower acceptance from the nature protection sector by the end of the meetings. No pattern of ties can be generalized for

168 actors with scientific/expert background, as they were positioned quite differently. Scientists from nature protection had same pattern of ties as the “more stake-holding” members from the forestry sector: they had broad out-neighborhoods, but were open to influence by just few other actors who had similar opinions as they did. From the side of the forestry sector the situation is quite divergent; some (FOF2) were very close to nature protection and others (CFRI3) emerged later on, while some regardless of frequent inter-sectoral communication and almost no failed communication influence attempts (FOF1) have decreased parts of their in-neighborhood arising from the nature protection sector.

The usage of Friedkin`s (1993) operationalization of inter-personal influence provided results which are in line with its first application (Friedkin, 1993). However, most of the questions were regarded as sensitive, and the usage of one item per power base (French and Raven, 1959) does not provide enough validity to engage in more thorough interpretation of results. As items on the issue related inter-personal influence (visibility and salience of alter`s opinion on ego) were highly correlated (0.72 and 0.86) and were not regarded as sensitive. It is recommended that future research in similar policy setting with high-positioned actors focuses on usage of just these two items, and that the other elements of the Friedkin`s (1993) model are tested separately with more items per power base. The research also showed that the correlation between communication patterns and the influence relations is low (0.33). The ordinal scale through which influence was analyzed had eight points. As most of the key actors in the second wave had ties between themselves on level 7 and 8, a scale with more discriminating power (even a visual analogue scale) would likely enable more thorough analysis of the stronger ties (although this goes against the recommendations of Ferligoj and Hlebec, 1999).

The usage of Friedkin and Johnsen`s (1997) model to predict opinion change was productive, as the correlation between the predicted and the observed values was 0.71. It was also seen that the decisions were not based on consensus; they came closer to one another which was not the case in the beginning. The modeling showed that in most important cases outcome decisions were closer to the positions of the forestry sector, which in general reflects the influence relations in the working group. A second pattern that was noticed is that the outcome decisions are in general closer to the position of the group whose initial opinion is closer to the long-term equilibrium opinions. As these results are based on a single case they hold very little external validity, so further research is needed to support these claims; both in other policy formulation processes and in other cultural contexts.

The application of the model was also marked with several threats to internal validity. The first wave of data gathering was done after one quarter of the process, and not at the onset. Although most of the issues on which opinions were asked were not addressed by the point of the first data collection some information is lost, both in the opinions and in the influence relations. There was not a single decision to be made; rather there were series of different topics. All the topics were

169 not equally relevant, and their inter-relations have not been taken into consideration. This introduces the issue of policy trading, where actors could have traded support on one issue for the support on another issue which is of greater importance to them. As most of the members of the working group were engaged in parallel assignments on other issues out of the working group, there could have been policy trading related to some other issues which were not followed by the research. This kind of strategic behavior and contextual variables have not been taken into consideration. The errors in the calculations of the outcome opinions were not randomly distributed among actors, as they were highest for the influential actors who have to a large extent kept their “more extreme” opinions. The equilibrium opinions also showed more consensus than the actual case. All this indicates to a need for further research on defining the coefficient of social influence (the alpha parameter), as it was set too high and with too little discrimination.

The usage of models on network dynamics showed that for lower levels of influence reciprocity and cross-sectoral relations are important, but that stronger influence show indication of local hierarchy. Closer inspection in the data revealed that most of the change in the network status occurred among junior actors, which implies that senior actors, to a large extent, had already formed relations to other actors in the first wave of the data collection. This is in congruence with high density at wave 1, and with the responses of the actors from the interviews. The co- evolution model of influence relations and opinions showed that actually there is no statistically significant relation of influence network on the change in opinions, but also that there is no significant indication that influence relations are shaped by the similarity of opinions between the influenced and the influencing actor. This puts into question the validity of the application of the Friedkin and Johnsen`s (1997) model.

More validity to the influence dynamics model would be gained by increasing the number of waves, as this study has collected the data only at the onset and at the end of the process. Relaying on observational data is not a good strategy as they are events and not states, which violate the assumptions of the SIENA models. The behavior used in the co-evolution model is the mean opinion per actor for all nine issues. Analyzing each separate issue would cause problems with the internal validity, as the opinions on separate issues did not evolve independently. Using mean values of opinions is an imprecise measure; however it provides more validity than looking at separate opinions per issue and imputing other opinions as changing actor covariates. This would imply that other opinions are independent from the focal one, which is not true – as all actors` opinions represent value judgments that are to a certain extent aligned with the central position of either the forestry sector, or the nature protection sector.

The decision to assume stable organizational environment was correct as the difference in the inter-organizational network from the first to the second wave is small to a level which can be

170 attributed to the responded bias. The results of cross-sectional analysis showed dominance of larger organizations, relative independence of implementing/expert agencies from their administrative counterparts, and a high level of reciprocity in resource flows, all of which is in line with the ‘resource dependence perspective’ (Pfeiffer and Salancik, 1979). Grouping of organizations according to the sectoral division of the network was evident, as was the grouping of organizations of private forestry. Nevertheless, the co-evolution model of network and behavior did not show significant effect of sectoral affiliation on opinion change. In the Friedkin and Johnsen`s model the difference between stated and equilibrium opinions of the key organizations is reflected in their organizational power, where the opinions of the more powerful (CF, MDF) have changed less than it was the case of the less powerful ones (SINP and MCDNP).

Failure to expand the network to +1 snowball sample around the organizations that had representatives in the working group has strongly decreased the discussion on the results of the organizational analysis, as the observed network does not constitute the whole organizational environment of any of the included organizations. For this reason, it is more prudent to maintain the discussion mostly on dyadic relations. The finding that the organizational network is relatively constant can be attributed to the short time horizon of the research. The operationalization of resources, the theoretical framework which guided the research, and the usage of formal network analysis techniques were complementary elements of the research design. A part of the research design that was not adequately performed was the sampling of key informants – there were not enough key informants per each organization. Larger organizations were adequately represented, but little validity can be attributed to organizational relations when the data is pending from just two key informants, as it was the case with several smaller organizations (CUPFOA, FES, CNMH). For this reason, the application of Friedkin and Johnsen`s (1997) model of opinion change was performed on just the most influential and the largest organizations.

To what extent have the inter-organizational relations affected the inter-personal relations in the working group? The sectoral division was evident in the working group. The distribution of degrees among senior actors in the working group followed the distribution of degrees of their organizations. The correlation between the inter-organizational power relations and the inter- personal influence relations among the senior members of the working group was 0.46, which is marginally less (0.475) than when Friedkin (1993) tried to explain inter-personal influence through categorical inter-personal relations and through French and Raven`s (1959) bases of social power. Both organizational power and mutual dependence of organizations are statistically significant effects in explaining the dynamics of inter-personal influence relations (Table 29). All these findings support the claim that the power relations of inter-organizational structure have affected the dynamics of the working group which formulated the expert Natura 2000 forest policy.

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To what extent have the inter-personal relations affected the decision making process? At the first wave of data gathering members of the working group were also asked “to which extent is the discussion guided by scientific arguments?”, and the mean response was 60%. The researchers which performed non-participant observation also counted the number of “political” and “scientific/technical” arguments, and their ratio was 47:53. These crude points give some indication for scientific arguments being an important driver of the policy formulation. This issue was thoroughly addressed in the previous chapter. The application of Friedkin and Johnsen`s (1997) model showed that the perceived implementation points on the specific issues follow the power relations among the sectors, but this is a very simplified relation. The assumption that inter-personal influence relations guide the dynamics of the working group was embedded in the research design. This assumption was not supported by the co-evolution model of influence and opinions, and therefore it cannot be stated that the influence relations are the sole driver of the policy formulation process. Non-significance of many effects in the behavior dynamics in the co- evolution model of influence and opinions also point to the fact that there might be some unobserved variables codetermining network and behavior, which could be solved by a different theoretical framework, or with more rigorous data collection. This issue is further addressed in the final discussion chapter.

This quantitative analysis has provided valuable parts of the explanation on how the stakeholders influenced the formulation of Natura 2000 forest policy, especially on the relation of the inter- organizational and inter-personal level. However, the discussion remains open to alternative interpretations, such as to the role of policy beliefs, strategic usage of communication, science- policy interface, and the usage of non-decision making. As these concepts have been addressed in the previous chapter, their relation to the findings of social network analysis is presented in the final discussion chapter.

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CHAPTER V DISCUSSION AND CONCLUSIONS

Each of the three previous chapters has its own methodology, results and discussion; but only combined do they show a more complete view on how the stakeholders have influenced the formulation of Natura 2000 forest policy in Croatia. Chapter II “Natura 2000 and the context of its transposition” corresponding to its title provides an overview of what of Natura 2000 is, what were the basis of its implementation into the forestry sectors of different EU countries, and provides a critical review of the history of its implementation in Croatia. It demonstrated that the Croatian implementation of Natura 2000 follows the “rationalistic” Differential empowerment path of the Europeanization of environmental governance, and that strong formal pre-accession compliance (including the decisions of the working group on forestry) is turning to weak post- accession compliance. However, Chapter II informs very little on the activities of the working group on forestry, whose contribution to the (future) Ordinance on Natura 2000 represents the most important element of the Network`s implementation in Croatian forestry. The following chapter “Normative, rational and communicative perspective on the working group on Natura 2000” provides detail accounts of the working group’s activities, the opinions of its members, and the various factors which have affected its decision making. It exemplified that overall, its members perceived it as a formal forum where policy learning has occurred; nevertheless, actual policy learning transpired just on secondary topics, and to a greater extend within the sector of nature protection. The most important decisions - site designation and management guidelines – were based on compromise. Strong support is established to the predictions of the ‘Advocacy coalition framework’ from Chapter III, where differences in policy beliefs are traced to the differences between the concepts of sustainable forest management and the concept of ecosystem approach. The chapter demonstrated that “more central” organizations and the “more authoritative” actors played a bigger role in the decision making process in comparison to the other actors, but provided little understanding behind the meaning of the concepts. These concepts were thoroughly addressed in the chapter “Network perspective on the formulation of Natura 2000 forest policy”, which showed that the organizational power has affected the inter- personal relations of the members of the working group, and that the inter-personal influence relations are reflected in the decisions that the group made. It confirmed that the decisions were based on compromise, and it showed trends of strengthening cross-sectoral communication and influence, which are indicators of policy learning.

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As any other research, this one also faces several threats to validity. The research design assumed dominant attribution of agency to the members of the working group, embedded in the structure of long-term inter-organizational relations. These two levels were also the ones on which the analysis was performed, attempting to find out what their contribution to the working group`s dynamics was. Although the majority of decision making has occurred within the formal meetings of the working group – some of the decision making occurred on its side-meetings, and some of these side-meetings hosted high-ranking individuals out of the working group (Croatian interviews). The precise date, topics and participants of these meetings could not be identified by this research. For analytical reasons, inter-organizational relations were regarded as stable; however, from the beginning of data analysis until the end of year 2013, the Ministry of Agriculture has changed its internal structure - the Forest extension service has been dissolved and the majority of its obligations were transferred to Croatian Forests Ltd.,. In addition, the Department for Nature Protection within the Ministry of Culture was transferred to the newly founded Ministry of Environmental and Nature Protection. Diminishing power of private forestry and the growing capacities of nature protection will to a certain extent alter the future steps of the implementation of Natura 2000 from what was presented in this research. Another threat to internal validity is the focus on the expert working group on Natura 2000 in forestry. Testing to which extent stakeholders have been represented in the working group was done by mapping stakeholders through literature review, by interviewing members of the working group and by interviewing key informants from potential stake-holding organizations. The only “relevant” stakeholders who have not been represented at the working group are the environmental, non- governmental organizations. Three of their representatives have been interviewed, and all of them responded that they are interested in the developments of the working group, but do not think that they should take part in it. Reasons for the lack of willingness to participate are lack of tradition for participation in such policy processes, fear of losing legitimacy by working with the land user groups and with the government, and to certain extent lack of the capacity to follow the process. These issues were thoroughly addressed in the chapter “Natura 2000 and the context of its transposition”.

In Chapter III this research has used three distinctive theoretical approaches to test the domain of validity of the normative, rational and scientific discourse on the formulation of the Natura 2000 forest policy. The advantage of this design to other research on the topic (Alphandéry and Fortier, 2001; Julien et al, 2010; Ferranti et al, 2013) is that in this case, the analysis does not a priori attribute any outcome or activity to a certain rationale; rather, it tests its arguments through a series of formal hypotheses. Such analysis may provide valuable information for the following steps of implementation of Natura 2000 in Croatia; as the normative opposition of the forestry sector to Natura 2000 may be more easily diminished through increased information campaigns than through rational-based negotiation of a compromise solution on the management guidelines for forest habitats. This research also represents the first application of social network analysis

174 on the topic of Natura 2000. It showed a stable inter-organizational context with clear distribution of power among the stake-holding organizations. As this contextual setting has affected the policy formulation process, the knowledge on the inter-organizational context may provide valuable background information for designing more equitable, participatory processes. The application of Friedkin and Johnsen`s model has shown that more powerful actors have their initial opinions closer to the outcome opinions than it is the case with the less powerful actors. Applying this kind of analysis in the onset of a policy formulation process may help capture the direction in which the outcome decision is heading, and assist in designing the process so that the outcome represents a more equitable compromise. The co-evolution models however, did not provide support for the effect of sectoral affiliation on opinion change and of the influence relations on opinion change, both of which go against the findings of the Friedkin and Johnsen`s (1997) model of opinion change. Lack of such causation stipulates importance of alternative explanations, which could be found in the importance of the initial normative standpoints as revealed by Chapter III. In such situation a common ground for a decision making in Croatian implementation of Natura 2000 cannot be found until actors lax their initial assumptions on how to proceed. This is reflected by the strong divergence between influential actors SINP5 and CF1 (Figure 15, p.79), and their inability for successful communication (Figure 29, p.148).

In the first paragraph of this chapter it was stated that the differences in the normative standpoints among the members of the working group are rooted in the differences between the concepts of ecosystem approach and sustainable forest management. According to the preamble of the ‘Habitats Directive’, it clearly represents a contribution to sustainable development, which is in line with the anthropocentric paradigm. However, switching the burden of proof of adversely effect in impact assessments from conservation onto development and acceptance of conservation biology as the only allowed type of argumentation in the designation of protection areas clearly implies an alignment with the paradigm of ecocentrism, by which parts of the environment have their own intrinsic value. This discrepancy in the ethical backgrounds of the ‘Habitats Directive’ (Rosa and da Silva, 2005) reflects the cooperation between the Commission and the ENGOs that was present in its formulation (Weber and Christophersen, 2002). The ecocentrism position was also present in the logic of defining the Dutch National Ecological Network, where the current status was benchmarked against the situation in which no human presence existed, which in turn, was used to model the ‘Habitats Directive’.

The State Institute on Nature Protection has created a highly participatory process with the forestry sector and has informally accepted compromise as the decision making rule (SINP5; p.90); however the framing of Natura 2000 as a policy based on scientific argumentation from the field of conservation biology has set many different claims as non-valid. The dissatisfaction with Natura 2000 and with the working group coming from its forest sector members that was previously addressed is expected; as their mostly socio-economic argumentation was non-valid due to the fact that the designation process should be based on scientific criteria. The sustainable

175 forest management concept as the dominant concept of forestry sciences also encompasses a socio-economic component, by which it is also to a certain extent non-valid for the discussion on national implementation of Natura 2000. This is evident from the different perceptions on what Natura 2000 is (see discussion section in Chapter III), as for the forestry sector it is dominantly a protection regime which allows sustainable management of natural resources, and for the nature protection sector it is a protection regime where management should be done according to the principles of conservation biology – i.e. with minimum deterioration of habitats and species.

The ecocentric position is of conservation biology is also evident in the rulings of the European Court of Justice (ECJ) related to Natura 2000, as according to EU case law ‘‘the competent national authorities are to authorize activities only if they have made certain that it will not adversely affect the integrity of that site’’ (ECJ, 2004; C-127/02). A review of studies on the implementation of the Network show that a variety of actors who were involved in the decision making process of the appropriate assessments (i.e. project developers and consultants, public administration officers, national legislators and juridical experts) were unfamiliar with the Directives and their implications to a level that the main reason for passing down projects and plans was insufficient knowledge and information. This led to a practice where the certainty of no adverse effect of the projects on the habitats and species within Natura 2000 has been met very seldom (Opdam et al, 2009). Certainty is not something with which science comes into policy making, as natural systems are inherently stochastic, and the scientific information comes into policy within a context of social discourse (Reckhow, 1994). The scientific information also carries uncertainty by internal, external, construct and content threats to validity (Yin, 2009), as well as by the process of falsifiability (Popper, 1959). The principle path for coping with scientific uncertainty in policy making is the precautionary principle, which is an integral part of the Treaty of the European Union, the Convention on Biological Diversity and the Rio Declaration. The principle relates to accepting and explicitly recognizing it, which then provides options for managing it, rather than preventing it. In the context of forestry, the concept of adaptive management (Schultz, 2008), is a management option which relates to the precautionary principle, having uncertainty as its main variable. Even the term “significant” in the context of influence of plan or project on a specific site is still an object of debate (Kistenkas, 2005).

The discussion above shows a clear trail of the application of the conservation biology concept from the formulation of Directives, through their interpretation by the ECJ and their national transposition, and finally to their national implementation. As argued in the discussion section of Chapter III (p.89-97), a common understanding between the members of the working group was not achieved due to different framing of their expertise, and in such a situation the only possible solution is a compromise decision. Same framing differences will most likely exist in the future steps of the implementation of Natura 2000 in Croatia. After two and a half year period of discussion the attitude of the members of the working group from the forestry sector towards

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Natura 2000 did not improve (Chapter III, p.78), and these individuals will continue to represent their organizations in the implementation of Natura 2000. Once these two elements are taken into consideration, it can be expected that the future steps in the implementation of Natura 2000 will show similarities to its implementation in Bulgaria (p.32), where they were characterized by deep conflict between conservation and land user groups.

Both qualitative (Chapter III) and quantitative approach (Chapter IV) have shown grouping of actors according to their sectoral division in similarity of opinions (Figure 15, p.79), inter- personal relations (Figure 24, p.143; Figure 29, p.148) and in inter-organizational relations (Figure 30, p.154). The sectoral division of actors has also shown (p.78) alignment to either the “multiple use forestry” paradigm or to the “environmentalists” paradigm (Glück, 2000a). Adherence to policy beliefs as the dominant rationale for the actions of the working group`s members was shown in Chapter III, as the data was aligned with most of the predictions arising from the normative approach (Table 10, p.106). The adequacy of Advocacy coalition framework (Sabatier and Jenkins-Smith, 1993) for explaining the activities of the working group was also supported by the application of the different methods of social network analysis, as the administrative organizations had more “moderate” opinions than it was the case with the implementing/expert organizations (Figure 32, p.161). It was stated in Chapter IV that there might be some unobserved variables codetermining the relation between influence and opinions, which could be solved by a different theoretical framework or with more rigorous data collection. An indication of these unobserved variables is found in the application of Friedkin and Johnsen`s model, where majority of the actors held a medium opinion on a specific non- salient issue (Q6; interventions into populations of strictly protected species), and have had very divergent positions on a very salient issue (Q3; Natura 2000 in just nationally protected areas), where their opinions changed very little throughout the process. These differences are in line with the Advocacy Coalition Framework (ACF), by which actors are willing to trade support for a secondary issue in order to focus on their policy core issues, and where actors are grouped into advocacy coalitions based on their generalized belief systems. Another indication of ACF`s applicability is the effect of opinions on influence relations (Table 30, p.167), as accepting very different opinions on a stronger level would imply acknowledging weaknesses in its own policy core. The differences in normative standpoints as reflected in the concepts of sustainable forest management and ecosystem approach on a larger policy scale are a part of a struggle between two policy “camps” - the “environmentalist camp” and the “forestry camp”. Each of these groups from the 1960s onwards, have produced series of legally and non-legally binding documents (Glück, 2000a). The most notable legally binding documents from the “environmentalist camp” are: Ramsar Convention (1972), World Heritage Convention (1972, CITES (1973), Convention on Biological Diversity (1993), EU Birds Directive (1979/2009) and the EU Fauna and Flora Habitats Directive (1992). The most notable non-legally binding documents are: the World Charter for Nature (1982), Statement of Forest Principles (1992), Combating Deforestation

177 within Agenda 21, Chapter 11 (1992) and the Pan-European Biological and Landscape Diversity Strategy (1995). The most notable legally binding documents from the “forestry camp” are: the International Tropical Timber Agreement (1983/1994) and the Protocol on Mountain Forest of the Alpine Convention (1991), while the most notable non-legally binding documents are the ones stemming from the Forest Europe Processes (1993-). Setting the ‘Habitats’ and the ‘Birds Directive’ in a group of policies endorsed by the “environmentalist camp”, provides for the reasoning of the adherence to the ecosystem approach in the formulation of Natura 2000, in its subsequent interpretation by the ECJ, and finally, in the national implementation processes as seen from the perspective of the implementing agencies. As the discussion section of Chapter III has shown, there was a clear misunderstanding within the working group on what kind of knowledge is acceptable as scientific, and even how Natura 2000 is defined in the context of forestry. The same chapter has traced this to the differences between sustainable forest management and ecosystem approach. However, this “misunderstanding” is only a very small section of an on-going policy debate between different perspectives on the protection of forest biodiversity, which can also be put in an even wider context of different perspectives on nature (anthropocentric / ecocentirc), (Glück, 2000a). Such discrepancy in the normative standpoints among the members of the working group has impeded the discursive creation of a common definition of what adequate (scientific) knowledge for the transposition of Natura 2000 in forestry of Croatia is, and has also facilitated the prominence of power relations in the decision making process. Several different approaches have been used in order to detect how stakeholders have influenced the formulation of Croatian Natura 2000 forest policy. Compelling evidence was discovered for the effects of policy beliefs and of power relations. One may argue that the most important finding of the research is the strong significance of these social factors and the role they play in the transposition of Natura 2000. The kind of roles these factors will play in the upcoming phases remains yet to be seen.

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ANNEXES

Annex I: code book

Group of codes Codes Memo TOPICS ALL TOPICS Usage of this code means that the topic of discussion addresses in general all the topics that were discussed by the working group Limiting final cut Relates to any kind of limitation of the final cut from the current practice, e.g. limiting its size, connection of forest compartments, or leaving uncut areas in the centre of the felling area Private forests in Natura Designation of private forests in Natura 2000 2000 protection regime +2 code relates to designating, and -2 relates to not designating private forests in Natura 2000 Protection in special Relates to national categorization of a special reserve in reserve order to further protect some Natura 2000 species or habitat (+2 agree / -2 disagree) Natura 2000 in general When intersected with Opinion on topic codes relates to whether or not will improve sustainable forest management in Croatia; or a general attitude towards Natura 2000. When intersected with information on topic codes relates to general information on Natura 2000. +2 =yes / - 2=no Designation of sites Represents general designation of sites for protection, where agreeing (+2) with this means smaller area of protection, and not agreeing (-2) means approval of designation of larger areas. Also equated with designation of forest habitats within already nationally protected areas Inclusion of Spačva basin Inclusion of Spačva basin to the Natura 2000 network. It is a very economically important sessile oak forest. Inclusion is both for forest habitats and forest related species +2 =yes / - 2=no Presence of deadwood Relates to prescription of management guideline which sets permanent presence of deadwood +2 =yes / - 2=no Management guidelines Relates to prescribing management guidelines for forest habitats within Natura 2000. +2 means approving detailed management guidelines, while -2 relates to preference for approving general management guidelines, or not having them at all. It also relates to prescribing management guidelines which are the same as "business as usual" scenario. This also applies for measures of other species that are related to forest habitats

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OPINION ON +2 Strongly supports TOPIC +1 Moderately supports 0 Neither approve nor disapprove / No opinion -1 Moderately disapproves -2 Strongly disapproves SUBJECT Group A separate code is made for each group (organization, sector, etc.) that is mentioned during the interview Individual A separate code is made for each individual mentioned during the interview PROCESS Facilitating communication Describes a person or a group which had a positive role in facilitating the communication among the members of the working group Impeding communication Having a role in the working group which negatively influences communication Rules known Procedural aspects of decision making are known Rules unknown Procedural aspects of decision making are not known RATIONALE Policy learning Policy learning concept as defined by advocacy coalition framework Science When related to Topic codes means decision based on scientific discourse. When related to Subject codes means usage of scientific argumentation Compromise When related to Topic codes means decision based on compromise. When related to Subject codes means pursuing personal or group interests within the policy formulation process INFORMATION Adequate Relates to presence of adequate information for a ON TOPIC specific topic (as adequate to base a decision on it) Inadequate Relates to presence of inadequate information for a specific topic (as inadequate to base a decision on it) Strategic Strategic use of information to further certain interests or beliefs… e.g. selective usage of information, or deliberately withholding parts of information Contradictory Relates to existence of contradictory information on a specific topic

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Annex II: social power code book

Group of codes Code Memo The powerful I Members of the more powerful groups are seen more through their individual characteristics than through joint group membership attributes their (Deschamps, 1982) Stereotype comment The powerful are more prejudiced against the less powerful (Ryan & Kahn, 1975) Causality of power The powerful attribute more power-related thoughts to others (Schmid-Mast, Hall, and Ickes (2006); attribution of power of an actor as a cause of an event or a decision Causality of competence The powerful are seen as more competent (Fiske, Cuddy, Glick, and Xu, 2002); attribution of competence of an actor as a cause of an event or a decision Out-group homogeneity The powerful perceive out-group as homogenus (Judd & Park, 1988), In-group heterogeneity The powerful group themselves perceive as heterogeneous (Judd & Park, 1988), Dispositional People make more dispositional attributions for the attributions behavior of powerful individuals (‘fundamental attribution error) Overbeck, Tiedens, and Brion (2006) Conversational Powerful display less behavioral inhibition (Keltner interruption et al. (2003) – they interrupt the interviewer Long personal Powerful speak more about themselves Brauer and description Bouhoris, 2006 Open expression of Powerful are more open to express their opinions opinion (Anderson and Galinsky (2006), Brauer and Bouhoris, 2006

The powerless We Members of the less powerful groups are seen more through their joint group membership attributes than through their individual characteristics (Deschamps, 1982) In-group homogeneity The less powerful perceive strong in-group cohesion (Simon and Brown 1987) Out-group heterogeneity The powerful group is perceived more heterogeneous than it actually is (Deschamps, 1982) Situational explanation People make more situational explanations for the behavior of less powerful individuals Overbeck, Tiedens, and Brion (2006 Short personal Powerless speak less about themselves (Guinote, description Judd, & Brauer, 2002). Reluctant / partial Powerless are less open to express their opinions expression of opinion (Anderson and Galinsky (2006), Brauer and Bouhoris, 2006

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Annex III: interview protocol

Group of Description Questions Sub-questions, comments questions Personal Work Please describe your professional development, and Check for the differences since the last interview description your current position Results of the Final results How would you comment the results of the working Check by rationale - policy learning, compromise, scientific process group? discourse.. Go through different topics Importance What kind of results would you prefer? Go through topics of results Say how outcomes differ from their opinions Look for personal/organizational preferences

Have you changed/modified your opinion in any of If they say nothing, go through topics the topics Ask if they have learned something –ask for others Were some topics more relevant than others? Ask for causes Were there some important topics that were not discussed? Are there some topics where decisions were not Ask for causes made? Do you envisage some changes of the working group`s decisions in the future steps? Opinions on Members What is your opinion on the composition of the Ask on organizational level working group working group? Ask on number of people per organization Ask if someone is missing Ask on the choice of representatives by organizations Dynamics What is your opinion on the dynamics of Ask for changes from the first meeting onwards communication in the working group? Ask for types of argumentation used (“science”, “politics”…) Do you have some comments on the content of Ask on is all the people had equal opportunities, to speak, and equal discussions? say in decision making – ask on differences Role How would you describe your role in the working Ask also for others - for dominance relations, mediator, different types group? of expertise, representation of different interest (groups)…..

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Annex IV. Operationalization of hypotheses for Chapter III

Normative approach Core assumptions 1 policy change requires a historical perspective that covers at least a decade 2 Policy change is best observed within a policy subsystem, i.e. in the interaction of stakeholders who follow and try to influence governmental decisions of a policy area 3 Subsystems must include intergovernmental relations 4 Public policies can be conceptualized as belief systems, i.e. a set of values and assumptions on how to realize them 5 beliefs are categorized on a three point scale: deep core beliefs, policy core beliefs, secondary aspects 6 The paths to policy change exist: policy oriented learning, external subsystem events and negotiated agreements 7 Coalitions are stabile over time Auxiliary assumption Hypothesis Comment 1. There is at least one clearly identifiable 1. Actors within an advocacy coalition show Formal hypothesis no.2 of the ACF; Jenkins-Smith and Sabatier, advocacy coalition substantial consensus on issues pertaining the 1994 policy core but less so on secondary aspects The auxiliary assumption is confirmed – two coalitions are identified 1. There is at least one clearly identifiable 2. An actor or coalition will give up secondary Formal hypothesis no.3 of the ACF; Jenkins-Smith and Sabatier, advocacy coalition aspects of a belief system before acknowledging 1994 2. At least one put of three mechanism of policy weaknesses in the policy core The first auxiliary assumption is confirmed – two coalitions are change has occurred during the research identified (policy learning, external perturbation, The second auxiliary assumption is confirmed; the formal setting negotiated agreement) of the working group represents “professional forum” for negotiated agreement; policy learning was identified for the following secondary aspects: limiting final cut and permanent presence of deadwood 1. There is at least two clearly identifiable 3. Policy-oriented learning across belief systems is Formal hypothesis no.6 of the ACF; Jenkins-Smith and Sabatier, advocacy coalition most likely when there is an intermediate level of 1994 2. Policy oriented learning has occurred during informed conflict between the two coalitions. The first auxiliary assumption is confirmed – two coalitions are the research identified 3. Topics with varying level of information The second auxiliary assumption is confirmed; the formal setting have been addressed by the working group of the working group represents “professional forum” for 4. Intermediate level of conflict requires that negotiated agreement; policy learning was identified for the o Each coalition has technical following secondary aspects: limiting final cut and permanent resources to engage in such a debate presence of deadwood o The conflict be between secondary The third auxiliary assumption is confirmed; as actors had aspects of one belief system and different levels of information on different topics. This was most core elements of the other or, pronounced for the topics Site designation process and Natura alternatively, between important 2000 in general secondary aspects of the two belief The fourth auxiliary assumption is the definition of intermediate systems level of conflict from Jenkins-Smith and Sabatier, 1994. The first part of this assumption is not confirmed for the representatives of private forest owners, as they have stated in the interviews that

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they do not have adequate technical resources to completely follow the discussions of the working group. All other actors had adequate technical resources to follow the discussions of the working group. The second part of the fourth auxiliary hypothesis is confirmed, as policy oriented learning has occurred within topics that are identified as secondary policy aspects of both advocacy coalitions 1. There is at least two clearly identifiable 4. Problems for which accepted quantitative data Formal hypothesis no.7 of the ACF; Jenkins-Smith and Sabatier, advocacy coalition and theory exist are more conducive to policy- 1994 2. Topics with varying level of information oriented learning across belief systems than The first auxiliary assumption is confirmed – two coalitions are have been addressed by the working group those in which data and theory are generally identified qualitative, quite subjective, or altogether lacking The second auxiliary assumption is confirmed; as actors had different levels of information on different topics. This was most pronounced for the topics Site designation process and Natura 2000 in general 1. There is at least one clearly identifiable 5. Within a coalition, administrative agencies will Formal hypothesis no.10 of the ACF; Jenkins-Smith and Sabatier, advocacy coalition usually advocate more moderate positions than 1994 2. Majority of advocacy coalitions have as their their interest group allies The first auxiliary assumption is confirmed – two coalitions are members organizations of state identified administration The second auxiliary assumption is confirmed: both coalitions have as their members organizations of state administration; the Ministry of Agriculture and the Ministry of Culture, Directorate for Nature protection 1. There exist two clearly identifiable advocacy 6. Members of the working group will have their The first auxiliary assumption is confirmed – two coalitions are coalition beliefs aligned with the general beliefs of the identified 2. The policy core beliefs of the forestry and forestry and the nature protection sectors The second auxiliary assumption is confirmed – as the the nature protection sector are represented distribution of opinions of different groups of actors (scaled from by the “multiple use forestry” and by the 0 to 1) follows the grouping of actors according to the two “environmentalists” paradigms (Glück, 2000 paradigms; depicted by Figure 16 1. There exist two clearly identifiable advocacy 7. Actors will evaluate their opponents' behavior in Formal hypothesis no.2 of the ACF`s “Devil shift” concept; coalition harsher terms than will most members of their Sabatier et al, 1987 policy community, while evaluating their own The first auxiliary assumption is confirmed – two coalitions are behavior in more favorable terms. identified 1. There exist two clearly identifiable advocacy 8. Actors will perceive their opponents to be more Formal hypothesis no.3 of the ACF`s “Devil shift” concept; coalition influential, and themselves to be less influential, Sabatier et al, 1987 than will most members of their policy The first auxiliary assumption is confirmed – two coalitions are community. identified 1. There exist two clearly identifiable advocacy 9. The amount of distortion (or "devil shift") is Formal hypothesis no.3 of the ACF`s “Devil shift” concept; coalition correlated with the distance between one's beliefs Sabatier et al, 1987 and those of one's opponents. The first auxiliary assumption is confirmed – two coalitions are identified

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Rational approach Core assumptions 1. Behavioral1 explanation is explained by a selection among alternatives 2. Preferences and constraints of actors are the major determinants of their behavior 3. Actors choose alternatives which are optimal in terms of their preferences (with respect to their constraints) 4. Actors are optimally informed rational egoist, they are concerned with tangible consequences of their actions, and take into account only objective constraints Bridge assumption Hypothesis Comment 3. Policy core beliefs represent actors` interests; 1. Policy preferences of the members of The first auxiliary assumption cannot be confirmed for all the working group are distributed actors/organizations, as some of them have their interest set in other according to the organizational topics. These are CUPFO and APFOA in topic Private forests, and interests CNMH in topic Final cut. However, the working group had only one representative from each of these organizations, which disables comparison of inter/intra organizational similarity of opinions for this three organizations; which makes this issue superficial for practical testing of the hypothesis. 1. Policy core beliefs represent actors` interests; 3. Policy preferences of the actors will The first auxiliary assumption cannot be confirmed for all 2. There is no major petrubation of the policy-subsystem stay the same actors/organizations, as some of them have their interest set in other during the observed period topics. These are CUPFO and APFOA in topic Private forests, and CNMH in topic Final cut. Testing of the hypothesis supports its prediction that interest of the actors did not change (ICC = 0.874 and 0.924). With these three actors excluded, the results have stayed the same; so the implications of the auxiliary assumptions do not have practical effect on the testing of the hypothesis R2 The second auxiliary hypothesis is confirmed, as it was found that the observed part of the policy subsystem was stabile during the period covered by the research; see section 5.2 within Chapter IV 1. Policy core beliefs represent actors` interests; 4. Decisions which are aligned with the The first auxiliary assumption cannot be confirmed for all interest of the focal group are actors/organizations, as some of them have their interest set in other characterized as based on scientific topics. These are CUPFO and APFOA in topic Private forests, and criteria, whereas the ones that are not CNMH in topic Final cut. Due to the low activity of these actors as characterized as based on non- there was not enough adequate data to match their policy scientific criteria preferences with different rationales; so they did not have practical effect on the testing of the hypothesis R3 1. Policy core beliefs represent actors` interests; 5. Actors will strive to restrain behavior The first auxiliary assumption cannot be confirmed for all of other actors that goes against the actors/organizations, as some of them have their interest set in other interest of the focal actor topics. These are CUPFO and APFOA in topic Private forests, and CNMH in topic Final cut. These actors did not interrupt anyone and were not interrupted while presenting their arguments; so they had not practical effect on the testing of hypothesis R4 1. Only actors affiliated to faculties and research 6. Scientists in the working group will In the context of the working group the predictions of the first institutes are scientists disapprove scientific findings coming auxiliary hypothesis are confirmed; as there was a clear 2. Scientists are affiliated to the nature protection or to from other sectors, and approve demarcation between “scientific” and “non-scientific” actors. Only the forestry sector finding from her/his own sector the actors affiliated to faculties and research institutes were 230

regarded as scientists, and no actor in the working group that is not scientists had previously pursued academic career. The second auxiliary hypothesis can be confirmed for all scientists; as the grouping of actors according to the “we” criterion clearly shows demarcation between the two sectors (Figure 15) 1. There are several clearly identifiable outcomes of the 7. Actors will describe the outcomes of Regarding auxiliary hypothesis 1, seven specific topics have been working group the working group as a compromise identified. However a complete decision on Topic Management 2. Compromise-based decisions are formed though guidelines has not been made – as they were defined for forest- partial acceptance of different interests regarding the dependent species but not for forest habitats. This incorporates same topic elements of non-decision making, thus limiting the testing of hypothesis R6 on the topic Management guidelines The second auxiliary hypothesis cannot be confirmed; as there exist a possibility of policy-trading, i.e. exchanging support for one topic for alters` support on another topic, even the ones which were not addressed by the working group 1. Expertise in a certain topic is predominantly linked to 8. Actor use strategically information The predictions of the auxiliary hypothesis one can be confirmed one actor or one group of actors from their field of expertise to further for topics Designation process and Natura 2000 in general; as certain interests or beliefs Croatian Forests Ltd. is a holder of the extensive GIS data base on forest habitats, and the State Institue on Nature Protection is the organization responsible for the implementation of Natura 2000. These are also the topics in which majority of intersection of the codes Strategic and Topic occurred. This link of expertise to a certain group of actors could not be identified for the topic Management guidelines, as this topic encompasses management guidelines for forest habitats and many forest dependent species; and expertise in the “composite” topic is distributed though several different organizations 1. Actors engagement in discussions of the working 9. The topics with most divergent policy Auxiliary hypothesis 1 cannot be completely confirmed, as some group is characterized by presentation of information preferences are characterized by actors may have employed alternative strategies to further their which supports their interest contradictory information interest. The strategy of non-decision making may have been employed by SINP for the issue of management guidelines for forest habitats within the Management guidelines topic. For the topic Designation process one or more groups of actors may have chosen not to present the information which goes in their favor within the working group; but rather to pass on that activity to the next step of the formulation of Ordinance on Natura 2000. Investigation of these claims goes beyond the scope of this research 1. Each topic has its own clearly distinguishable 10. Procedural elements for decisions Auxiliary hypothesis cannot be confirmed; as the topics of procedural elements for decision making making will be less known for topics discussion were frequently changed even within a single meeting, for which the interests of those and there was no formal procedure for decision making. This is leading the process is higher reflected in the results of the coding, as majority of Rules known and Rules unknown codes are related to the overall discussions of the working group, and not to any topic in particular

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Communicative approach Core assumptions 1. Communication is based on shared and negotiated understanding of the situation 2. Communication is free from power relations 3. Discourse is conditioned by a consensus on the validity of claims that are made by the actors 4. The primary function of science is to disseminate “proven” knowledge, which is primarily defined by institutionalization of the following social norms: Communalism Universalism Disinterestedness Originality and Organized skepticism Auxiliary assumption Hypothesis Comment 1. Decisions of the working group are based on 1. The decisions of the working group are based on Auxiliary hypothesis cannot be confirmed; as the communication between its members consensus among its members communication was not restricted to the formal meetings of the working group. There were several side-meetings in which several members of the working group were present, alongside several individuals that were not members of the working group. Part of the communication and the decision-making related to the Site designation and Management guidelines topics occurred within these side-meetings. This issue is addressed in Chapter V. 1. Validity check of the presented argumentation is the 2. Changes in opinions of the members of the As the research shows supportive evidence for strategic dominant mechanism of opinion change working group is related to the amount of the use of information (R7) , “devil shift” (N7 and N8) and information available on that topic for tracing opinion change to structure of policy belief system (N2), it cannot be stated that the validity check of presented argumentation is the dominant mechanism of opinion change; i.e. the auxiliary hypothesis can not be confirmed. 1. There is no single information or source of 3. Actors in the working group critically assess the The first auxiliary hypothesis is confirmed – as each information that is adequate to serve as a basis for validity of the claims that support their interests topic that was addressed by the working group is a multi- formation of a decision and beliefs facet topic, there is no single information or source of information that would be adequate to serve as a basis for formation of a decision. . For example, limiting the final cut requires knowledge on silviculture, on bats, birds, other groups of species and on general functioning of the forest ecosystems. As “Discourse is conditioned by a consensus on the validity of claims that are made by the actors”, it is implied that actors should also critically assess the validity of their own claims; and if they do not then the alternative theoretical approaches (normative, rational) provide more fitting explanations. 1. Members of the working group have a shared 4. Members of the working perceive the decisions The first auxiliary hypotheses cannot be confirmed; as understanding of what (acceptable) scientific being made as decisions based on scientific different (groups of) actors had different interpretation argumentation is (for the formation of a decision) argumentation what (correct) scientific argumentation is, and which scientific argumentation is chosen as a basis for formulation of a decision. This issue is addressed in the 232

discussion section within Chapter III 1. All actors have adequate technical resources to accept 5. Members of the working group had equal The auxiliary assumption is not confirmed for the the information needed to engage in communication available information on the topics that were representatives of private forest owners, as they have within the working group discussed stated in the interviews that they do not have adequate technical resources to completely follow the discussions of the working group. All other actors had adequate technical resources to follow the discussions of the working group 1. All actors had adequately participated in the 6. Members of working group perceive that all of Not all the members of the working group have attended communication, which preconditions the formation of them had shared understanding of the issues that all of its meetings; however there were side-meetings shared understanding of the issues that were addressed were discussed at the meetings that addressed same topics, and majority of the members by the working group of the working group worked in other formal settings with other members of the working group, addressing same or related topics. This issue is addressed in the discussion sections of Chapter III and Chapter IV, and again in Chapter V; and the auxiliary assumption is confirmed 1. No actor or group of actors have dominated the 7. No members of the working group had the All actors had same opportunity to engage themselves in communication of the working group dominant influence on the decisions that the the communication, and as revealed by the non- group made participant observation, all groups of actors had actively participated in the communication within the working group; the auxiliary hypothesis is confirmed 1. Members of the working group have a shared 8. No member or members of the working group The first auxiliary hypotheses cannot be confirmed; as understanding of what (acceptable) scientific had the monopoly on the correct interpretation of different (groups of) actors had different interpretation argumentation is (for the formation of a decision) the issues that were addressed by the working what (correct) scientific argumentation is, and which group scientific argumentation is chosen as a basis for formulation of a decision. This issue is addressed in the discussion section within Chapter III 1. Procedural aspects for decision making are either 9. The procedural aspects for the decision making Auxiliary hypothesis cannot be confirmed. known in advance, or there exist a consensus among are known to the members of the working group There was no formal procedure for decision making, and actors when the shared understanding of validity of all there was no consensus among actors when the shared claims is reached understanding of validity of all claims is reached. This issue is thoroughly addressed in the discussion section within Chapter III. 1. All actors had adequately participated in the 10. Distortions in the communication decrease with Not all the members of the working group have attended communication, which preconditions the formation of the passage of time all of its meetings; however there were side-meetings shared understanding of the issues that were addressed that addressed same topics, and majority of the members by the working group of the working group worked in other formal settings with other members of the working group, addressing same or related topics. This issue is addressed in the discussion sections of Chapter III and Chapter IV, and again in Chapter V; and the auxiliary assumption is confirmed

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Annex V. Contradictions among the hypotheses from Chapter III

Normative approach Hypothesis Operationalization Contradiction to 10. Actors within an advocacy coalition show  Differences in policy preferences within a coalition R1 – states different distribution of policy preferences substantial consensus on issues pertaining the are smallest for the most policy core topics (according to organizational affiliation) policy core but less so on secondary aspects C1 – states that policy preferences at time 2 will be similar among actors 11. An actor or coalition will give up secondary  Codes Topic → Opinion on topic →+1, -1 and 0 C2 - states that opinions on policy core topics may change aspects of a belief system before acknowledging from time 1 change in time 2, but the ones that had according to the distribution of Adequate and Inadequate weaknesses in the policy core +2 and -2 do not codes; which includes policy core topics 12. Policy-oriented learning across belief systems is  Changes in Topic → Opinion on topic occurred in C2 - states that opinions on policy core topics may change most likely when there is an intermediate level topics that did not had strong +2/-2 dichotomy according to the distribution of Adequate and Inadequate of informed conflict between the two coalitions. codes; which includes policy core topics 13. Problems for which accepted quantitative data  Changes in Topic → Opinion on topic occurred in and theory exist are more conducive to policy- topics where all groups of Subject → Information on oriented learning across belief systems than topic were marked mostly with +1 code those in which data and theory are generally  Changes in Topic → Opinion on topic occurred in qualitative, quite subjective, or altogether topics for which the dominant code in the lacking Information on topic group of codes was Adequate 14. Within a coalition, administrative agencies will  Actors from administrative agencies have less +2/-2 usually advocate more moderate positions than codes in Topic → Opinion on topic than other actors their interest group allies 15. Members of the working group will have their  Codes of actors within the Topic → Opinion on C1 – states that policy preferences at time 2 will be similar beliefs aligned with the general beliefs of the topic category will be aligned according to the among actors forestry and the nature protection sectors general sectoral policy beliefs (Glück, 2000) R1 – states different distribution of policy preferences (according to organizational affiliation) 16. Actors will evaluate their opponents' behavior in  The dominant code in the Rationale group for actors harsher terms than will most members of their out of the focal coalition is Compromise policy community, while evaluating their own  The dominant codes in the Rationale group of codes behavior in more favorable terms. for actors in the focal coalition are Science and Policy learning  The Strategic code (for usage of information) is related to the actors from the out-group 17. Actors will perceive their opponents to be more  Not influential code is mostly used to describe C7 – states that Influence codes are equally distributed influential, and themselves to be less influential, members of the in-group, and Influential code is among the Subject group of codes than will most members of their policy mostly used to describe members of the out-group community. 18. The amount of distortion (or "devil shift") is  The distribution of influence codes is positively C7 – states that Influence codes are equally distributed correlated with the distance between one's correlated to the difference in the Topic → Opinion among the Subject group of codes beliefs and those of one's opponents. on topic codes between the focal actor and the one(s) that he/she is talking about 234

Rational approach Hypothesis Operationalization Contradiction to 4. Policy preferences of the members of the  Distributions of codes in Topic → Opinion on topic N1 – states that policy preferences are distributed according working group are distributed according to the group of codes are more similar among actors within to advocacy coalitions organizational interests the same organization than among actors from C1 – states that policy preferences at time 2 will be similar different organizations among actors N6 – states that policy preferences are defined by sectoral affiliation 5. Policy preferences of the actors will stay the  Distributions of codes in Topic → Opinion on topic C2 - states that opinions on policy core topics may change same group of codes will not substantially change for according to the distribution of Adequate and Inadequate policy core topics (ICC test) codes; which includes policy core topics 4. Decisions which are aligned with the interest of  Decisions which are skewed toward the opinions of the focal group are characterized as based on the focal group have dominant Scientific rationale scientific criteria, whereas the ones that are not code attributed to them, whereas the out-group will as characterized as based on non-scientific attribute more codes Policy learning and criteria Compromise to the same topics

7. Actors will strive to restrain behavior of other  Interruptions in the dyadic communication in the actors that goes against the interest of the focal meetings of the working group are correlated with actor the difference in opinions (Topic → Opinion on topic) between the person doing the interruption and the interrupted person 6. Scientists in the working group will disapprove  The dominant codes in the Rationale group are scientific findings coming from other sectors, Policy learning and Compromise when related to and approve finding from her/his own sector actors from different sector, and code Science for the actors from the same sector as the focal actor. Relates only to actors affiliated to scientific organizations 10. Actors will describe the outcomes of the  The dominant code in the Topic → Outcome group C4 – states that the dominant code is Science working group as a compromise is the Compromise code 11. Actor use strategically information from their  Code Strategic in the Information on topic group of C6 – states that code Strategic does not have high field of expertise to further certain interests or codes has high frequency for matching actors frequency beliefs (Subject codes) and Topics 12. The topics with most divergent policy  The highest frequency of Contradictory codes is C6 – states that code Contradictory does not have high preferences are characterized by contradictory related to Topics for which have most pronounced frequency for any topic information dichotomy of +2/-2 codes

13. Procedural elements for decisions making will  There will be more Rules unknown codes than Rules C9 – states that there are more Rules known codes be less known for topics for which the interests known codes for topics in which the leaders of the of those leading the process is higher policy formulation (SINP) have higher interest on

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Communicative approach Hypothesis Operationalization Contradiction to 11. The decisions of the working group are based on  At Time 2 distributions of codes in Topic → Opinion N1 – states that distribution of codes Opinion on topic at time consensus among its members on topic group of codes are similar all among actors for 2 will not substantially change for policy core, and that they majority of the topics are distributed according to coalition

R1 – states that distribution of codes Opinion on topic at time 2 will not much change for policy core, and that they are distributed according to organizational affiliation

N6 – states that distribution of codes Opinion on topic at time 2 will not substantially change for policy core, and that they are distributed according to sectoral affiliation

12. Changes in opinions of the members of the  Change in codes in Topic → Opinion on topic group of N2 – states that change will occur on secondary aspects in working group is related to the amount of the codes from time 1 to time 2 is greater for topics which order to maintain the policy core, and that is not conditioned information available on that topic have higher frequency of Adequate than Inadequate by the availability of data codes from the Information group of codes R2 – states that policy core will remain the same, regardless of the availability of data

N3 – States that policy core opinion change is unlikely, regardless of the level of information

13. Actors in the working group critically assess the  When stating their policy preferences (Opinion on validity of the claims that support their interests topic codes crossed with Topics codes) crossed with and beliefs Science rationale actors will frequently use Inadequate code from the Information on topic group of codes - more frequently than Adequate

14. Members of the working perceive the decisions  The dominant code in the Topic → Outcome group is being made as decisions based on scientific the code Science argumentation 15. Members of the working group had equal available  The Adequate and Inadequate codes in Topic → information on the topics that were discussed Information on topic group are equally distributed across all actors for all topics 16. Members of working group perceive that all of  Codes Strategic and Contradictory from the R7 – states that code Strategic has high frequency for them had shared understanding of the issues that Information on topic group of codes are not dominant matching topics and actors were discussed at the meetings for any of the topics. All codes in the Information on topic group are equally distributed among the actors R8 – States that salient topics have high frequency of

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Contradictory code

17. No members of the working group had the  The influence codes are equally distributed among N7 – states that influence codes are distributed according to dominant influence on the decisions that the group Subject group of codes for all of the topics the in-group / out-group criterion made 18. No member or members of the working group had  No actor had dominated in the frequency of the Science the monopoly on the correct interpretation of the code for any of the topics issues that were addressed by the WG 19. The procedural aspects for the decision making are  In the Process group of codes there is more Rules R9 – states that the distribution of codes Rules known and known to the members of the working group known codes than Rules unknown codes for all of the Rules known depends on the interest of SINP topics

20. Distortions in the communication decrease with the  Frequency of Impeding communication decreases, and passage of time of Facilitating communication code increases

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Annex VI. Network visualizations with fixed layout

All the visualizations are presented in a circle layout, and the position of nodes is fixed

Figure 1. Interpersonal influence relations at time 1 - only strong (6,7 and 8) influence relations are shown

Figure 2. Interpersonal influence relations at time 2 - only strong (6,7 and 8) influence relations are shown 238

Figure 3. Cumulative reciprocal dyadic communication - only frequencies larger than 7 are shown (0-63 range)

Figure 4. Cumulative non-reciprocal (failed) dyadic communication - only frequencies larger than 4 are shown (0-22 range)

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Figure 5. Cumulative inter-organizational resource flows - only frequencies larger than 4 are shown (0-10.5 range)

Figure 6. Inter-organizational power relations - only values larger than 0.6 are shown (0-1 range)

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