Investigating Fuzzy Cognitive Mapping

as a participatory tool for conceptual landscape modelling

MSc Thesis in Landscape Management by

Stud.scient. Kirsten Grovermann Qvist Isak

September 2008

Investigating Fuzzy Cognitive Mapping as a participatory tool for conceptual landscape

modelling

MSc Thesis in Landscape Management

Stud. scient. Kirsten Grovermann Qvist Isak, LKF 05001

Faculty of Life Sciences, University of Copenhagen

September 2008

Supervisor: Senior research scientist, Ph.D. Tove Enggrob Boon, Forest & Landscape, Faculty of

Life Sciences, University of Copenhagen

External supervisor: Senior research scientist, Director of Research Department, Ph.D. Flemming

Skov, Department of Wildlife Ecology and Biodiversity, National Environmental Research

Institute, Aarhus University

Table of contents

Preface..................................................................................................................................................2

Acknowledgements..............................................................................................................................2

Resumé.................................................................................................................................................3

Investigating Fuzzy Cognitive Mapping as a participatory tool for conceptual landscape modelling 4

Abstract ............................................................................................................................................4

Introduction......................................................................................................................................5

Public participation in Danish landscape management................................................................5

Introduction of a soft systems methodology, fuzzy cognitive mapping ......................................6

Presentation of the case study ......................................................................................................6

Presentation of fuzzy cognitive mapping.........................................................................................8

What is fuzzy cognitive mapping?...............................................................................................8

The analysis of fuzzy cognitive maps..........................................................................................8

The case study................................................................................................................................11

Presentation of informants and six locations within the case study area...................................11

Analysis of the fuzzy cognitive maps ........................................................................................15

Case study results.......................................................................................................................17

Discussion ......................................................................................................................................25

The suitability of fuzzy cognitive mapping for producing a holistic landscape description in a

participatory manner ..................................................................................................................25

Discussion of the case study results...........................................................................................25

Fuzzy cognitive mapping as a tool for participatory landscape management ...........................29

References......................................................................................................................................32

1

Preface

This paper presents my MSc Thesis in Landscape Management conducted at the Faculty of Life

Sciences, University of Copenhagen. The purpose of the thesis is to address the inadequate public

participation conducted in Denmark today, recently expressed through the debate concerning

National Parks in Denmark. The thesis presents a model which investigates individuals’ perceptions

of a given area and outlines how the model can be used in a participatory landscape management.

During the project, I was connected to Department of Wildlife Ecology and Biodiversity, The

National Environmental Research Institute, Aarhus University.

Kalø, September 26th 2008__________________________________________________________

Kirsten Grovermann Qvist Isak, LFK 05001

Acknowledgements

First of all I would like to thank the informants and the many local people in Mols Bjerge who have

helped me, without whom this project could not have been made.

Secondly, I would like to thank professor Christian Frølund Damgaard, Department of Terrestrial

Ecology, National Environmental Research Institute, University of Aarhus for priceless help with

the mathematical analyses. The National Environmental and Research Institute (NERI), Kalø

played an essential role in this work and I would like to thank the staff for an inspiring working

environment and the master students in particular for listening to and answering endless flow of

questions.

Lastly I am now in debt to:

Research student James Speed, University of Aberdeen as he provided irreplaceable feedback and

language corrections.

Stud.scient.Katrine Meisner, NERI as she corrected the same grammatical errors over and over

again and provided an amazing support in the last few weeks.

Professor Tony Fox, NERI as he found time for a much appreciated last minute language check,

during fieldwork in Tøndermarsken.

2

Resumé

Soft systems metoden ”fuzzy cognitive mapping” blev benyttet til begrebsmæssigt at beskrive et

landskab og metodens potentiale som et borgerinddragelsesværktøj blev undersøgt. Det blev

undersøgt hvorledes ”fuzzy cognitive mapping” kan benyttes til at beskrive informanters opfattelse

af et specifikt landskab og om hvorvidt et bredt udsnit af aspekter i landskabet kan inkluderes i en

landskabsbeskrivelse. Et ”case study” blev gennemført, dækkende kerneområdet i en nylig udpeget

Nationalpark i Danmark og ”fuzzy cognitive maps” blev produceret på baggrund af semi-

strukturerede interviews med tolv informanter. Informanternes beskrivelser af landskabet viste ikke

en entydig tilknytning til deres respektive interessegruppe, men forskelle var til stede mellem

borgerne og eksperterne. ”Fuzzy cognitive mapping” viste sig velegnet til at involvere borgere og

eksperter i at beskrive landskabet og til at inkludere et bredt udsnit af aspekter i landskabet. Der

blev indhentet en forståelse af årsagssammenhænge og feedback mekanismer i landskabet, men det

var ikke muligt at opnå en indsigt i de underliggende mekanismer i landskabet. ”Fuzzy cognitive

mapping” kan bruges i borgerinddragelse som et kollaborativt læringsværktøj, og derigennem opnå

en forbedret kommunikation mellem forskellige interessegrupper. Derudover kan ”fuzzy cognitve

mapping” benyttes i forbindelse med en debat iblandt interessegrupper, om ønskede og mulige

ændringer i landskabet. ”Fuzzy cognitive mapping” kan produceres i grupper for at udnyttet

metodens potentiale for læring og ”fuzzy cognitive maps” kan med fordel produceres på baggrund

af foruddefinerede koncepter, der indhentes gennem semi-strukturerede interviews med informanter

forud for arbejdet i grupper.

3

Investigating Fuzzy Cognitive Mapping as a participatory tool for

conceptual landscape modelling

Abstract

A soft systems methodology for conceptual landscape modelling, fuzzy cognitive mapping, was

investigated for its potential as a tool in public participation. The use of fuzzy cognitive mapping to

conceptually describe a landscape through the perceptions of informants was investigated, as was

whether a wide range of aspects in the landscape can be included in the description. A case study

was undertaken in the core area of a newly designated National Park in Denmark and fuzzy

cognitive maps were created during semi-structured interviews with twelve informants. The

informants’ perception of the landscape did not show evident connection to their respective

stakeholder group but some differences were present between lay people and experts. Fuzzy

cognitive mapping showed its suitability to involve both lay people and experts in including a broad

range of aspects in a conceptual landscape description. An understanding of the cause and effect

relations, and the feed back mechanisms was obtained, but it was not possible to gain an

understanding of the emergent properties in the landscape. Fuzzy cognitive mapping can be used in

participatory landscape management as a collaborative learning tool to improve communication

between stakeholders and when debating desirable and feasible changes in the landscape. Fuzzy

cognitive maps should, in order to take advantage of their potential for social learning, be created in

group sessions. Fuzzy cognitive maps can advantageously be created based on predefined concepts

which have been identified during individual semi-structured interviews with informants prior to

group sessions.

Keywords: Fuzzy cognitive mapping, soft systems methodology, public participation, collaborative

learning, national park.

4

Introduction

This paper presents a soft systems methodology for conceptual landscape modelling. The method

was applied in a case study in order to investigate the method’s suitability for 1) involving

participants in creating a conceptual landscape description, 2) including a broad range of aspects in

a conceptual landscape description and 3) describing the dynamics in a landscape. Lastly, this paper

outlines the method’s potential as a participatory tool in landscape management.

Public participation in Danish landscape management

Denmark is characterised by a highly specialised and intensive agricultural sector, with 62 % of the

land being cultivated and by a relative high population density with 127 inhabitants pr. sq. km

(www.statistikbanken.dk). Together with an increasing political focus on public health and outdoor

recreation (www.folkesundhed.dk; www.friluftsraadet.dk), the aim of stopping the loss of

biodiversity by the year 2010 (www.blst.dk/2010; www.countdown2010.net) is under pressure

(Teknologi-Rådet 2008). Five National Parks have recently been designated with emphasis on their

biodiversity, and the main aim is to create coherent natural areas in a manner which involves the

public. The public’s view of Danish national parks often reflects opposing interests in the landscape

because whereas some stakeholders, e.g. landowners, see a national park as a threat to their

traditional use of land, other stakeholders view parks as a mechanism for expanding tourism and

other business opportunities (Månsson (ed.) 2005).

In the pilot project studies leading up to designation of the National Parks, the “blank paper model”

was proposed and introduced (Kvistgaard Consult 2005). This model challenged the public to

delineate the park, define the aims for the park and design the planning and management of the

park. However evaluation of the model showed that the model’s success was limited (Kvistgaard

Consult 2005). Hansen (2007) studied the pilot projects from a democratic point of view and argued

for a need to rethink public participation in Denmark. The criticism made during the pilot projects

and by Hansen (2007), could be met by working with a model for public participation, which

focuses on: 1) creating an understanding of the values in the landscape, and how the landscape

functions and thus changes people’s perception of the landscape, 2) considering a wide range of the

population’s views and perceptions, and 3) communicating these views and perceptions broadly in

order to reach common ground for management.

5

Introduction of a soft systems methodology, fuzzy cognitive mapping

Fuzzy cognitive mapping (FCM) is a soft systems methodology that consists of a number of

variable concepts and connections which illustrate the cause and effect relations between the

concepts. FCM creates a conceptual description of a system as illustrated in Figure 1. A thorough

explanation of fuzzy cognitive mapping will be given under Presentation of fuzzy cognitive

mapping.

Fuzzy cognitive mapping (FCM) will be investigated, in order to answer the following questions:

1) How can FCM be used to conceptually

describe a landscape through the

perceptions of informants?

2) Can a wide range of aspects in the

landscape be included in the

description?

3) How suitable is FCM for i) involving

participants in creating a conceptual

landscape description, independent of

stakeholder groupings, ii) including a

broad range of aspects in a conceptual

landscape description and iii)

describing the dynamics in a landscape?

4) How can FC

Your well being

Food intake

Exercise Overw eight

positive

strongpositivenegativepositive

strongnegative

Figure 1: A simple example of a fuzzy cognitive map with four concepts: Your well being, Food intake, Exercise and Overweight. The effect one concepts has on another is represented by an arrow with a strenght described with words: strong positive, positive, strong negative, or negative (Skogoey & Skov 2007).

M work as a participatory tool in landscape management?

by which aspects a

Presentation of the case study

igure 2, totals 2915 hectares, and forms the core area of “National

In order to answer these questions, a case study was conducted, investigating

broad selection of informants perceive the case study area, and how they perceive the cause-effect

relations, the feed back mechanisms and the emergent properties in the area.

The case study area, shown in F

Park Mols Bjerge” (Månsson 2005). The hilly landscape was created during the glacial period

Weischel. The area is primarily covered by dry grassland, forest plantations and privately owned

6

agricultural land. The cultural heritage in the area is prominent, with sites and elements ranging

from the Bronze Age to historic time (Skov- og Naturstyrelsen 2008).

The whole area is designated as NATURA 2000 area (EF-habitat area) and contains several

protected nature types (dry grassland, heath, lake, bog and fresh meadow) (kort.arealinfo.dk) and

963 hectares is part of the EU LIFE+ program

(www.skovognatur.dk/Natur/Naturprojekter/LI

FE/Overdrev/Projektomraader/Mols_Bjerge;

www.ec.europa.eu/environment/life). Mols

Bjerge was chosen as study area because it is

well known and frequently used by the public,

and easy to define. Furthermore, it is subject to

numerous interests, such as nature protection,

recreational use, everyday life, agriculture and

forestry, which makes it suitable for applying

fuzzy cognitive mapping as a participatory

tool.

Figure 2: The case study area, Mols Bjerge delineated by the red line. The seven most notable types of land cover are presented together with the six locations for conducting interviews (© Kort- og Matrikelstyrelsen; Danmarks Arealinformation).

7

Presentation of fuzzy cognitive mapping

What is fuzzy cognitive mapping?

Fuzzy cognitive mapping (FCM) is a method for analysing and depicting human perception of a

given system. The method produces a conceptual model which is not limited by exact values and

measurements, and thus is well suited to represent relatively unstructured knowledge and causalities

expressed in imprecise forms. FCM is a dynamic tool because cause-effects relations and feed back

mechanisms are involved (Kosko 1986). Furthermore, the emergent properties in the system can be

investigated by asking “what-if” questions regarding the system (Khan & Quaddus 2004). A fuzzy

cognitive map can be produced by one individual or by several individuals together, and more maps

can be merged into a larger fuzzy cognitive map covering more aspects of the system (Tan &

Özesmi 2006). FCM focuses on the components and features in the system and is fairly simple and

easy to understand for the participants, which opens up the possibility for involving lay people as

well as experts.

FCM originates from the cognitive maps developed by Euler in 1736 which were based on directed

graphs (Özesmi & Özesmi 2004). Axelrod (1976) presented binary cognitive maps by defining and

describing variables in a cognitive map, and Kosko (1986) applied fuzzy causal functions with

number (-1, +1) to the connections. Furthermore, he computed the outcomes of a fuzzy cognitive

map and modelled the effects of different policy options. When Axelrod in 1976 first introduced

FCM, he used lay people in his research and when applied by Kosko in 1986, experts were used in

the research. In more recent research, FCM has been applied in working with different stakeholder

groups (Özesmi & Özesmi 2003), for presenting expert knowledge (Skov & Svenning 2003; Tan &

Özesmi 2006) and for comparing the perceptions of lay people and experts (Giles et al. 2006).

The analysis of fuzzy cognitive maps

The structure of fuzzy cognitive maps can be analysed and used when comparing maps created by a

number of informants. It can be investigated how many times a given concept is mentioned, and if

many informants mention the same concept, it can be interpreted as important for the system

(Özesmi & Özesmi 2004). Three indices can also be used when comparing maps: the density index,

the hierarchy index and the complexity index. The density index looks at the number of concepts

8

(variables) and connections in the maps, and expresses how connected the variables in the maps are.

A high density index indicates that the map represents a perception where many causal relationships

are present. Thus the higher the density index, the more options for changing the system exists. The

hierarchy index looks at how the variables in a map affect other variables and are affected by the

other variables. This is related to the total number of variables in the map. The hierarchy index

ranges between 0 and 1 and expresses how adaptable the system is to changes. A low index value

(democratic map) is more adaptable to changes due to the level of integration and dependencies,

than an index value near 1 (hierarchy map). The complexity index is the ratio between the receiver

variables (R) and the transmitter variables (T) in the map. A receiver variable (R) is affected by

variables without affecting the other variables (is said to contain only indegree values) and a

transmitter variable (T) affects other variables without being affected by any (is said to contain only

outdegree values). Variables can also be ordinary which is defined as containing both indegree and

outdegree values. A large complexity index illustrates many usable outcomes and less controlling

forcing functions. Lastly, the variables in a fuzzy cognitive map may also be represented by the

centrality index. The centrality index is the sum of the indegree and the outdegree, thus, the

centrality expresses how large a role a given variable plays in the system. A high centrality shows a

large importance and a low centrality reflects a lesser importance (Özesmi & Özesmi 2004).

A principal component analysis (PCA) can be conducted on the informants’ fuzzy cognitive maps

where the X axis represents the greatest difference among the informants and the Y axis represents

the second largest difference (Shaw 2003). The participants may subsequently be arranged in a plot

along these axes and participants with similar maps will be placed closely together in the plot. This

may be used to visualise differences and to classify groups of fuzzy cognitive maps.

Fuzzy cognitive maps can also be analysed in a dynamic manner by creating scenarios for the

system. This can be done by setting some variables in the map (e.g. the driving forces which are

variables with transmitter properties) to certain values, and let the system settle to either

equilibrium, or to a repetitive pattern. The affect on selected variables (e.g. the variables identified

as being the most important variables) can then be investigated (Khan & Quaddus, 2004). The

analysis will not be able to make predictions but can be used for gaining an understanding of the

system (Mendoza & Prabhu 2006). A dynamic analysis can be conducted in “Wolfram

Mathematica” software (www.wolfram.com/products/mathematica) by simulating a certain

9

management of the system by setting predefined variables to certain values prior to each iteration

process. This can be done for one single fuzzy cognitive map or for a number of maps, where the

output will be drawn at random among the maps. When using “Wolfram Mathematica” on a number

of maps, the outcome will be a mean value and deviation for the variables. The mean value of a

variable gives information about how the variable is perceived and the deviation gives information

about how different the variable is viewed in the different maps.

10

The case study

Presentation of informants and six locations within the case study area

Three categories of stakeholders were identified based on reports and abstracts from the pilot

project “National Park Mols Bjerge”, internet search, and interviews. They were classed as:

ʻrecreational usersʼ, ʻlandownersʼ and ʻplanners and managersʼ.

Stakeholders from the ʻrecreational usersʼ

(RU) category were defined by their interest in

outdoor activities in the area, either through

their profession or individual interests. They

were identified by investigating: 1) What

impact their activities were assumed to have

on the flora and fauna and on the recreational

quality of the area, and 2) how strongly the

stakeholders were assumed to be influenced by

the management of the area. This analysis is

presented in Figure 3 where the X-axis

illustrates the impact of the stakeholder’s

activity, and the Y-axis illustrates the

importance of the management to the

stakeholder. The stakeholders were placed in the chart based on investigations regarding people’s

degree of disturbance of nature (Tind & Agger 2003; www.friluftseffekter.dk). The informants in

the top right quadrant were identified for participation in the study, and three informants, presented

in Table 1 were selected through interviews and their willingness to participate in the study.

Danish Gymnastics and Sports Associations,

Karpenhøj

Rønde folk school

UnorganisedGeo-chaching

La

rge

imp

ort

ance

Sm

all

imp

ort

an

ce

Unorganised Mountain bike riders

Jökull– Society for Icelandic Horses

The Nature day care centre Mols Bjerge

High impactLow impact

Active in nature:A private company

Figure 3: Analysis of the stakeholder category ʻrecreational usersʼ. The x-axis shows how strong the impact from the activity is, on the flora, fauna and recreational quality, with one visit. The y-axis shows how important the management is assumed to be for the stakeholder. The three stakeholders in bold were selected for participation in this study.

The ʻlandownersʼ (LO) were defined as individuals, who either own or manage land and are

affected by the planning of the area. The informants were identified based on, 1) the location of the

individual’s land, 2) the individual’s previous participation in the pilot project study for the

“National Park Mols Bjerge”, and 3) interviews with people in the local community. The aim was to

cover the major ownership types and the four informants are presented in Table 1.

11

ʻPlanners and managersʼ (PM) were defined as

stakeholders who have authority in the planning

and/or management of the area. The choice of

stakeholders was made through investigating

their authority in relation to management

decisions by using a stakeholder grid (Eden &

Ackermann 2004). Figure 4 shows the

stakeholders within politics, public

administration and non government

organisations (NGO) and the three most

influential PLAYERS were identified. Five

informants, presented in Table 1 were selected,

based on their willingness to participate in the

study.

SUBJECTS PLAYERS

Affiliation Activity link

Works with communication of nature values RU-I Is an employee in an organisation, which has a commercial interest in the area.

- conducts guided tours in the area. www.dgi.dk/karpenhoej

Chairman of Jökull (local club for Icelandic horses).

RU-II Uses and enjoys the area

Lives in the area and rides in the area two or more times each day.

www.jokull.dk

Was born within the area. RU-III Has a personal commercial interest in the area. Manages a firm which arranges trips in the

area.

www.aktiv-djursland.dk

Was born in the core of the area and still lives in the area.

LO-I Is a farm manager with a thorough knowledge of the history and the changes in the area during the last 60-70 years.

Works for a landowner in the area, where he manages livestock.

Is chairman of Vistoft Plantation board which administrates Vistoft Plantation.

LO-II Is a forestry owner.

Comes to the area when participating in hunting events.

Table 1: Presentation of the informants. RU-I to RU-III represents the three informants from the stakeholder category ʻrecreational usersʼ, LO-I to LO-IV represents the four informants from the stakeholder category ʻlandownersʼ and PM-I to PM-V represents the five informants from the stakeholder category ʻplanners and managersʼ. The column affiliation describes the ground for the participation and the column activity describes the informant’s activities in the area. The column links contains internet links for further information.

Figure 4: A Stakeholder grid presenting the stake- holders from the category ʻplanners and managersʼ as SUBJECT, PLAYERS, CROWD, or STRATEGY CONTEXT SETTERS (Eden & Ackermann 2004). The PLAYERS considered in the case study are marked in bold.

CROWD

STRATEGY CONTEXT SETTERS

Bystanders Actors

Sta

keh

old

ers

Un

affe

cte

d

Power in relation to management

Interest

in the

mana-

gement

strate-gies

Danish Society for Nature Protection

Danish Forest and Nature Agency

Danish HuntingAssociation

Djursland’sFarmer Association

Danish Society for Ornithologist The Danish

ForestAssociation

Syddjurs Municipality

The Danish Outdoor Council

12

LO-III Is a landowner who focuses on nature protection and appropriate traffic in the area.

Is a retired teacher from the local municipal primary and secondary school, where he taught biology and geography.

www.dn.dk

LO-IV Is a fulltime conventional farmer.

Is born in the area, and is now managing a conventional pig farm.

PM-I Is a local politician. Is the chairman for the committee for Nature, Technology and Environment in the municipality of Syddjurs.

www.syddjurs.dk

Is a retired high school teacher in biology, and has a summer cottage in the area.

www.dn.dk PM-II Is active in NGOs.

Is member of the local division of the Danish Society for Nature Protections and the Agenda 21 network in Syddjurs municipality.

www.syddjurs.dk

PM-III Is a public servant within cultural heritage.

Is the leader of Ebeltoft Museum which is the public authority with the responsibility for the cultural heritage in the area.

www.ebeltoftmuseum.dk

PM-IV Is a public servant within nature management and public participation.

Is regional state forest manager with the responsibility for the contact to the public in the area.

www.sns.dk

PM-V Is a local politician. Is the chairman for the committee for Planning, Development and Culture in the municipality of Syddjurs.

www.syddjurs.dk

The interviews were conducted on site to present the informants for the genius loci (“spirit of

place”) (Nordberg-Schultz 1980) in order to obtain a broad description of the area. Nordberg-

Schultz (1980) defines a place as “a space which has a distinct character” (p. 5) and presents the

genius loci as a combination of five basic modes of mythical understanding: 1) Things, which are

concrete natural elements, 2) Cosmic order, which is abstracting a systematic order from the flux of

occurrences, 3) Character, which are the natural places related to human traits, 4) Light, which is

the sun and its rays, and 5) Temporal rhythms, which are the seasons and time. The interviews were

conducted at six different locations for all twelve participants. These six locations where chosen to

represent different expressions in the landscape and to, all together, describe Mols Bjerge broadly.

The six expressions were inspired by Arler (2000a, b) and the six locations were chosen based on

the author’s local knowledge, field studies and discussions with people with thorough knowledge of

the area. The locations where the interviews were conducted can be seen in Figure 2 and were

Trehøje¸ Skovbjerg, Tinghulen, Vistoft Plantage, Agri Bavnehøj and Århus Plantage. The six

locations are described in Table 2 and express the aspects: The Vast, The Intimate, The Social, The

Wild, The Treasured and The Controlled. Photographs of the six locations can be found in appendix

I.

13

Table 2: The six locations where the interviews were conducted. The column Expression presents the different expression held by the locations and the column Description shortly describes the locations. The column Location provides the name of the location.

Expression Description Location The Vast Is a gathering of 22 burial mounds which mostly are located on dry

grassland and thus very visible. Trehøje is one of the most visited locations in Mols Bjerge.

Trehøje

The Intimate Is an old oak thicket located on hilly terrain. The area is designated as unmanaged natural forest.The location is specifically mentioned in the tour material for the area.

Skovbjerg

The Social Is a depression in the landscape created from melting ice during the last glacial period. Tinghulen is also the former Thing stead for three parish. Locally, the location is widely used for family picnics, school trips and other gatherings.

Tinghulen

The Wild Is a privately owned plantation, planted in the mid 1800s, and consists today of both coniferous and deciduous trees. It is located in a hilly terrain and is forestry managed, though only extensively. The plantation is not highly utilised by the public.

Vistoft Plantage

The Treasured Is the highest point in Mols Bjerge. The increase in trees and shrubs around and on Agri Bavnehøj started the conservation plan for Mols Bjerge, as the managers and politicians could see that the valuable view disappeared. This removal of plantations and shrubs continues today. The location is one of the most visited location in Mols Bjerge.

Agri Bavnehøj

The Controlled Is a former privately owned coniferous plantation, which was recently bought by the State. The area is presently in the process of being restored as dry grassland, as part of a EU LIFE+ project. The area is not frequently visited, besides traffic passing through.

Århus Plantage

The fuzzy cognitive maps were created through semi-structured interviews (Kvale & Brinkmann

2008) on the basis of on the interview guide in appendix II. All interviews were conducted by the

author. The interviews were conducted at the six locations, in the same order. Each participant was

interviewed in two separate sessions separated by one or more weeks. On the first session,

interviews were conducted at the first three locations, and on the second session, interviews were

conducted at the last three locations. A coffee-meeting was held few months after the interview

sessions, where ten of twelve informants participated. Landowner II and ʻplanners and managersʼ I

were unable to attend. The concepts and their meaning were discussed and thus the qualitative

aggregation of the concepts (explained in: Analysis of the fuzzy cognitive maps) was verified.

14

Analysis of the fuzzy cognitive maps

The meaning of the concepts was analysed by use of the Cultural Value Model developed by

Stephenson (2008). The model focuses on the cultural heritage and the nature in the landscape, and

describes three fundamental components of the landscape: forms, relationships and practices. The

components affect each other repeatedly. This dynamic pattern of the landscape contains a

temporality as the values in a landscape can be surfaced values connected to the landscape in

present time, and embedded values, connected to the past Stephenson (2008). The aggregated

concepts (explained below) were placed in the model, under forms, relationships or practices and

under embedded, surfaced and/or future values in the landscape. The future values were added to

the model as a concept can have a future value, expressed through the informant’s thought, beliefs

and/or perceptions.

The interviews were conducted in Danish and the fuzzy cognitive maps were subsequently

translated into English. The six fuzzy cognitive maps from each informant were transformed into

six separate matrices by listing the concepts vertically and horizontally, and the effect one concept

had on another as a number representing the strength of the effect. The concepts mentioned by the

informants in their six fuzzy cognitive maps (i.e. the variables in the matrices) were grouped by a

qualitative aggregation (Özesmi & Özesmi 2004) into twenty two concepts. The six matrices for

each informant were, based on the qualitative aggregation of the variables, aggregated into one

matrix for each informant. The aggregation of the strength of the connections was done by adding

the strength of the connections and dividing by six, as described by Banini & Beardman (1998). The

diagonal, where two identical variables meet, were set to either 1 or 0. The diagonal was given the

value 1 in cases where the variable’s presence “this year” affects its presence “next year” (e.g. the

area with forest today, affects the area with forest next year), On the contrary, the diagonal was

given the value 0 where the variable’s presence “this year” did not have any influence on its

presence “next year” (e.g. the sense of peace today does not affect the sense of peace next year).

A structural analysis investigated how many times the concepts were mentioned by the three

stakeholder groups. The indegree and outdegree for the variables and the density index, centrality

index and hierarchy index were calculated in ”Wolfram Mathematica”, based on the formulas in

Özesmi & Özesmi (2004). The Complexity index was calculated manual with variables having

15

receiver or transmitter properties as no variables were “clean” transmitter or receiver. A principal

component analysis was also calculated in ”Wolfram Mathematica”.

A dynamic analysis was conducted, to gain understanding of what might happen, as the area

becomes the core area in “National Park Mols Bjerge”. The park has just recently been designated

and the balancing between nature protection, agriculture, recreation and other interests, has not been

decided upon yet. Thus four scenarios were investigated where the National Park planning and

management will either: 1) not have any influence on the area 2) have a strong focus on protection

of nature and development towards a large coherent nature area will continue, 3) have a strong

anthropological focus by meeting the demands from recreational users and the trends in the

development in the society or 4) focus both on protection of nature and anthropological issues. The

scenarios were set by giving the variables with the largest transmitter properties predefined values,

and investigating what happened to the variables predefined as the most important.

16

Case study results

The qualitative aggregation of the concepts resulted in twenty-two concepts, shown in Table 3,

which cover both the landscape’s attributes (components in the vertical landscape) and the ecotopes

(the horizontal combination of the attributes).

Table 3: Explanation of the twenty-two variables. The column Concepts presents the name by which these concepts will be referred to and the column Meanings describes the interpretation of the concepts.

Concepts Meanings landscape The [perceived importance of the] landscape’s characteristics - the contours, the sandy

soil, the amount of nutrients and the climatic conditions grassland The areas with dry grassland (which often are fenced and grazed) forest The area with forest, which provides shelter from the wind, and the area with unmanaged

nature clearance The area where forest has been cleared since 1980-90's shrub The area with tree and shrub vegetation in light demanding nature types agriculture The area with agricultural fields land use The variation between different land use in the area coherence The coherence in the landscape - distances between area with same nature type wild animal The population size of game and other wild animals species The number of species - the variation in species history The intensity of the cultural heritage and the number of visible historic objects and

remnants people The number of people in the area (including human activities, degradation as a

consequence of activities and human constructions) recreation The focus on recreational initiatives conflict The intensity of problems/conflicts in the area view An undisturbed view - lack of objects covering and obstructing the view peace Peace, calmness and quietness - the lack of sounds economy The resources for economic income management The nature management intensity communication The communication of nature and cultural/ancient values national park The process of establishing ”National Park Mols Bjerge” - the strength and the power of the

process development The development in the society (public health, policies etc.) – the intensity and the power personal The joy of being in the area – the personal gain

The concepts in Table 3 were analysed in the Cultural Value Model (Stephenson 2008), and

describe all three components in the landscape, as illustrated in Figure 5, in the solid lined boxes.

17

relationships

practicesfo

rms

history*view* (m,c)

personal gain (m,c)

history*view* (m,c)

personal gain (m,c)

landscape (m,c)grassland (c)forest (m,c)

clearance (m)shrub

agriculturehistory*

view* (m,c)

peopleconflicts

managementcommunicationNational Parkdevelopment

18

Thirteen of the twenty-two concepts are representing the components forms and reflects the

temporality in the landscape nicely as they both represent surfaced, embedded and future values.

The component practices is also represented thoroughly by eight concepts, both presenting

embedded and surfaced values, but no concepts represent future values. The component

relationship is not so well represented, as only three concepts represent this component, which all

reflect embedded values.

Figure 5: Holistic analysis of concepts describing Mols Bjerge. The boxes with the solid lines show which concepts represent the three respective components in the landscape: forms, relationships and practices. Two concepts, history and view, both belong to forms and relationships. The marking m represents that the concept is mentioned by all informants and the marking c represents that the concept is among the six most central concepts. The coloured box represents the concepts with surfaced values, the hatched boxes represent the concepts with embedded values and the dotted lined boxes represent the future values.

landscape (m,c)grassland (c)forest (m,c)

clearance (m)shrub

agriculturevariation (m)

landscape (m,c)grassland (c)forest (m,c)

clearance (m)shrub

agriculturevariation (m)land use (m)coherence

wild animalsspecies (m)

history*view* (m,c)

people (m,c)recreationconflictseconomy

management (m,c)communicationnational parkdevelopment wild animals

species (m)people (m,c)recreationconflictseconomy

management (m)National Park

Ten concepts were mentioned by all informants, as illustrated in Figure 6 where the number of

times a concept is mentioned by a stakeholder group is presented as a percentage of the total

number of informants in the specific stakeholder group. The ʻrecreational usersʼ (RU) all mentioned

RU

LO

0 10 20 30 40 50 60 70 80 90 100

personal

development

national park

communication

management

economy

peace

view

conflict

recreation

people

history

species

wild animal

coherence

land use

agriculture

shrub

clearance

forest

grassland

landscapePM

Figure 6: How many times each concept is mentioned by the informants, separated into stakeholder groups. The x-axis represents the percentage of informants in the respective group which have mentioned the specific concept.

fourteen and all together mentioned eighteen of the twenty-two concepts. The agriculture,

coherence, economy, national park concepts were not mentioned by any of the ʻrecreational usersʼ.

The ʻlandownersʼ (LO) all mentioned sixteen concepts and all together mentioned twenty of the

twenty-two concepts and did not mention the coherence or communication concepts. The ʻplanners

and managersʼ (PM) all mentioned ten concepts and all together mentioned all twenty-two concepts.

19

The centrality index, presented in Figure 7, was calculated as the mean for the twenty-two concepts

for each stakeholder group and for all informants. It shows that the mean centrality index for the

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

lan

dsc

ape

gra

ssla

nd

fore

st

clea

ran

ce

shru

b

agri

cult

ure

lan

d u

se

coh

eren

ce

wil

d a

nim

al

spec

ies

his

tory

peo

ple

recr

eati

on

con

flic

t

view

pea

ce

eco

no

my

man

agem

ent

com

mu

nic

atio

n

nat

ion

al p

ark

dev

elo

pm

ent

per

son

al

RU

LO

PM

mean

Figure 7: The centrality index for the twenty-two concepts. Diamonds are the mean centrality index for the three informants from the recreational users (RU) group, square is the mean centrality index for the four informants from the landowner (LO) group and the triangle is the mean centrality index for the five informants from the planner and manager (PM) group. The line is the mean centrality index for all twelve informants.

concept personal has the largest difference. The concepts peace, economy, management,

communication and national park have the lowest mean centrality index and the concepts with the

six highest mean centrality index are grassland, forest, clearance, people, view and personal.

The variables’ outdegree minus indegree, shown in Figure 8, illustrates the variables’ transmitter

and receiver properties and showed that the concepts with the largest transmitter properties were

landscape, forest, clearance, shrub, management, recreation and development. The concepts with

the largest receiver properties were personal, view, people, conflicts, species, wild animals and

20

peace. Four variables were viewed by some stakeholder groups as having transmitter properties and

by other as having receiver properties: grassland, land use, history and recreation.

Figure 8: Identifying the concepts as having transmitter or receiver properties by looking at the mean values by which a concept affects other concepts (outdegree) minus the mean value by which the concepts is being affected by other concept (indegree). This is divided into the three stakeholder groups: ʻrecreational usersʼ (RU), ʻlandownersʼ (LO) and ʻplanners and managersʼ (PM) and the mean values for all twelve informants. The variables with receiver properties have a negative value (to the left) and the variables with transmitter properties have a positive value (to the right).

mean PM LO RU

personal

development

national park

communication

management

economy

peace

view

conflict

recreation

people

history

species

wild animal

coherence

land use

agriculture

shrub

clearance

forest

grassland

landscape

-3,5 -3 -2,5 -2 -1,5 -1 -0,5 0 0,5 1 1,5

21

The complexity index for the twelve informants in Figure 9 illustrates that one informant’s

complexity index is somewhat higher that the other (PM-I) and that five informant’s complexity is

above the mean complexity index and six

informants’ complexity index is below the

mean complexity. ʻPlanners and managersʼ

(PM) appears to have a higher complexity in

general than both ʻrecreational usersʼ (RU) and

ʻlandownersʼ (LO).

0

0,5

1

1,5

2

2,5

3

RU

-I

RU

-II

RU

-III

LO

-I

LO

-II

LO

-III

LO

-IV

PM

-I

PM

-II

PM

-III

PM

-IV

PM

-V

all-

me

an

The density index for the twelve informants’

cognitive maps was between 0.1053 and

0.1549 and thus very similar. The hierarchy

index was just above 0, ranging from 0.0092 to

0.0267. Figure 9: The complexity index for the twelve informants and the mean complexity index for all twelve informant’s complexity indices.

The simple principal component analysis (PCA) of the informants’ fuzzy cognitive maps is shown

in Figure 10. The X and Y axis each represent respectively the concepts with the largest and second

largest difference in the informants’ perception of the concepts value – its eigenvalue. Correlation

between the variables or between variables and demographic data was not calculated. It was not

determined which variables are represented by the two axes.

22

The PCA shows that the informants from the ʻrecreational usersʼ (RU) are present in the bottom left

and bottom right quadrant. There are no informants present from the landowner (LO) in the bottom

left quadrant and no informants from the ʻplanners and managersʼ (PM) stakeholder group are

present in the top left quadrant. LO-I and LO-II are, as the only informants, positioned closely.

RU-III

LO-III

PM-II

PM-III

PM-IV

RU-I

RU-II

LO-I

LO-II

LO-IV

PM-I

PM-V

-2,5

-1,5

-0,5

0,5

1,5

2,5

-2,5 -1,5 -0,5 0,5 1,5 2,5

RU-I

RU-II

RU-III

LO-I

LO-II

LO-III

LO-IV

PM-I

PM-II

PM-III

PM-IV

PM-V

Figure 10: Principal component analysis (PCA) of the twelve informant’s fuzzy cognitive maps. The X and the Y axis represent the large eigenvalues of two unidentified concepts. RU I-III represents the informants from ʻrecreational usersʼ, the LO I-IV represents the informants from ʻlandownersʼ and PM I-V represent the informants for ʻplanners and managersʼ.

Two other groups of informants may be recognised. One group is PM-V, RU-I and LO-IV and the

other is PM-IV, LO-III and PM-III. The last four informants, PM-I, RU-II, RU-III and PM-II are

scattered among the others, with the latter two appearing to be furthest away from other informants.

23

The results from the dynamic analyses, investigated four scenarios by using scenario I (no changes)

as a reference and interpreting the other three scenarios against this. The scenarios II-IV were also

interpreted against each other. No remarkable differences in the variables’ mean value or in the

mean values deviation from the scenarios were present in either case.

24

Discussion

The suitability of fuzzy cognitive mapping for producing a holistic landscape description in a

participatory manner

Fuzzy cognitive mapping (FCM) gathered, in this study, a broad range of aspects in the conceptual

landscape description. The landscape was considered as a whole, but FCM can also focus on few

aspects in the landscape and thus describe sub-systems. The research questions leading up to FCM

are therefore important for its suitability for creating a holistic description of a landscape. This

study created fuzzy cognitive maps through semi-structured interviews with individuals. The

strength of this approach was that it opened up for perceptions without the pressure from other

participants and thus was suitable in conducting a participatory process. Working with FCM in

group sessions, on the other hand, has the strength that it may involve discussion, which can lead to

“undiscovered” concepts and perceptions.

Twelve different fuzzy cognitive maps were produced, describing Mols Bjerge, and showed that

FCM is a suitable tool for illustrating the cause-effect relations in a system. To illustrate the

feedback mechanisms, the effects need to be clarified, which this study experienced difficulties in

doing. The feedback mechanisms and the emergent properties in a landscape can be investigated by

setting “what-if” questions and letting the mechanisms develop in the fuzzy cognitive map. This

study investigated four different scenarios but the interpretation of the results showed no indications

of differences between the scenarios. This supports the suitability for fuzzy cognitive mapping as a

tool for describing the cause-effect relations and the feedback mechanisms in a landscape but also

emphasises the need for further development of the analysis in order to investigate the emergent

properties in the landscape.

Discussion of the case study results

The Cultural Value Model by Stephenson (2008) was chosen as a framework for analysis as both

nature and cultural heritage play important parts in the case study area. The concepts from this

study covered all three types of components in the landscape: forms, relationships and practices but

only three concepts represented the component relationships whereas two of these also represented

forms. This could be caused by either fuzzy cognitive mapping not including relationships very well

25

in the landscape description or by the qualitative aggregation of the concepts which created the

broad concepts personal. Embedded values in the landscape were thoroughly described as they

were representing all three components. Surfaced values were only representing forms. This may be

explained by the manner by which the temporality has been perceived by the author. Some concepts

in practices and in relationships could be perceived as representing surfaced values. Future values

were added to the Cultural Value Model as the informants’ expectations, thoughts and beliefs for

the future, played a role during the interviews. Future values were represented in both forms and

practices and contributed in describing the landscape’s temporality.

Structural analysis

The qualitative aggregation, following Özesmi & Özesmi (2004) is to some extent subjective and a

more systematic approach could be important for the further analysis of the fuzzy cognitive maps.

The aggregated concepts were presented for the informants in an attempt to verify the aggregation

and thus meet the weaknesses.

During the interviews, it proved difficult to give the connections a value representing the

informants’ perception. A test of whether the strength is in accordance with the informant’s

perception during the interview session could improve future analyses. This could be done by

investigating the fuzzy cognitive maps in “Microsoft Visio” (http://office.microsoft.com/visio)

where the effects of one concept affecting another can be illustrated. The aggregated connections

were calculated according to Banini & Beardman (1998) which challenged the interpretation of the

structural analysis and strongly influenced the dynamic analysis. This could indicate that the

connections have been simplified to a point where important details have been lost.

The structural analysis showed that the ʻrecreational usersʼ did not mention the concepts

agriculture, coherence, economy, and national park. This may be explained by the first three

concepts not, directly, influencing the informant’s activity in the area. The lack of use of the term

national park, however, is puzzling, as outdoor activities is a sub-objective for the national park

(Retsinfo 2007). The ʻlandownersʼ did not mention coherence and communication. The former can

be explained by the ʻlandownersʼ focusing on a somewhat local scale (one farm), and the latter can

be explained by the ʻlandownersʼ not being involved in communication of nature values. This can

both be interpreted negatively – the ʻlandownersʼ were not interested in communication of nature

26

values, or positively – the communication of nature values present in the area, does not affect the

ʻlandownersʼ in a negative manner. ʻPlanners and managersʼ mentioned all concepts. This indicates

that the ʻplanners and managersʼ view the landscape slightly differently than the two other groups.

The ʻplanners and managersʼ only “agree” on less than half of the concepts mentioned, which could

indicate that the landscape is viewed more broadly within the ʻplanners and managersʼ group than

within the other two groups. However the differences can also be influenced by the unequal number

of informants in the three groups.

The difference in the centrality index between the three groups, were largest for personal as

ʻrecreational usersʼ scored higher than the two other groups. This supports the definition of the

stakeholders from the ʻrecreational usersʼ category as having an interest in outdoor activities in the

area and to be in the area precisely to achieve a personal experience. Economy, national park and

communication were not mentioned by all three groups which can influence the low centrality, but

peace was mentioned by eleven informants from all three groups and management was mentioned

by all informants. Economy, national park, communication and management are concepts which

played an important role in the discussions during the pilot project (Månsson (ed) 2005) thus it is

noteworthy that they are perceived as being of small importance in the landscape. The role of peace

and management were perceived by many informants as playing a peripheral role. The concepts

with the six highest centrality index were mentioned by eleven or twelve informants, which shows

the informants having a similar perception of what is central in the landscape.

Five variables, grassland, land use, history, recreation and communication, were viewed by some

stakeholder groups as having transmitter properties and by others as having receiver properties but

none of the stakeholder groups can be said to have opposing perceptions of the system. Özesmi &

Özesmi (2004) present variables as being “clean” transmitters and receivers, but no variables in this

study were either one or the other. This may be explained by the relative small fuzzy cognitive

maps produced during the interviews (9-17 concepts) which might not have included all transmitter

variables. Or it could indicate that the aggregation of the concepts and of the matrices have resulted

in connections between variables which were not mentioned by the informants. This emphasises a

need for further development of the use and the analysis of the fuzzy cognitive maps and for

verification of the data collected after any aggregation.

27

The higher complexity among the ʻplanners and managersʼ indicates that these informants might

view the landscape slightly more complexly than the informants from both the ʻrecreational usersʼ

and the ʻlandownersʼ. The informants’ profession and/or their education may have an influence, but

data was not analysed for correlations between profession and/or education and the complexity.

The principal component analysis did not show clear grouping of the informants into the three

stakeholder groups. The analysis was conducted on an aggregation of the twelve matrices instead of

on a single matrix which might have played an important role for the results. Some trends appeared,

as no stakeholder group was present in all quadrants. This may be explained by the different

numbers of informants in the three groups or by the relative small number of informants. The

informants were positioned in groups across the stakeholder groups, but when investigating the

informants’ affiliation to the area and their activity, these grouping did not seem apparent. No

correlation analyses between the PCA and the informants’ demographic data were conducted.

Investigating the dynamics in the landscape

An expected result from investigating scenarios was an indication of how the system would respond

to changes, illustrated by a change in the mean values of variables and difference in their variance.

The mean values could change between the different scenarios, indicating how the variable would

react to the given scenario, given a large mean value would reflect a positive reaction, and a small

mean value would reflect a negative reaction. A difference between the deviations from the mean

values, could give information regarding how differently the informants view the specific variable.

Differences were investigated both by comparing scenarios II-IV to scenario I and by comparing

scenarios I-IV against each other, where all variables were investigated for responses to a scenario.

The effects of the scenarios did not show any clear trends, neither when investigating the mean

values for variables or when investigating the deviations. The reason for failing to detect any trends

from the scenarios could be the aggregation of the concepts, or more likely the calculations of the

connections and the values in the diagonals in the matrices.

The informants’ affiliation to the respective stakeholder group

The underlying basis for this study was three stakeholder categories: ʻrecreational usersʼ

ʻlandownersʼ and ʻplanners and managersʼ. The former two can be perceived as lay people and the

latter as experts. The centrality index and the investigation of the transmitter and receiver properties

28

of the variables did not show any differences between the three stakeholder groups, nor did it show

differences between lay people and experts. An analysis of the centrality index on an individual

level could be conducted to investigate for other grouping of the informants. Viewing by whom and

how often the variables were mentioned, a distinction between the lay people and the experts can

be seen. This trend also showed when viewing the complexity index. The principal component

analysis neither showed a division of the informants into the three stakeholder groups nor a division

into lay people and experts, but indicated another grouping across the ʻrecreational usersʼ the

ʻlandownersʼ and the ʻplanners and managersʼ.

Fuzzy cognitive mapping as a tool for participatory landscape management

During this study, it was found that FCM focused on the aspects and issues in the landscape, thus

moved focus away from the individuals involved towards the landscape itself. This is an important

aspect in negotiations as it plays a large role for communication between stakeholders with different

interests (Fischer et al. 1999) and emphasises FCM as a tool for improving communication between

stakeholders. A consequence of communication between stakeholders may be an insight into the

perceptions of other stakeholders. This insight may lead to reflection of one’s own values and acts

and thus an achievement of knowledge and understandings, which may affects one’s further actions

(Daniels & Walker 2001).

Learning plays an important role in this context. In connection to public participation, social

learning can be important and Daniels & Walker (2001) presented a system approach for

collaborative learning, shown in Figure 11. A process moves clockwise through the four phases:

Diverging, Assimilating, Converging and Accommodating and through the four learning styles:

Concrete Experience, Reflective Observation, Abstract Conceptualisation and Active Experience.

The first phase is Diverging, which has its starting point in Concrete Experience. During this study,

fuzzy cognitive mapping was not applied during the Diverging phase, but has a potential for being

applied both in judging and in perceiving the situation. A process then moves through Reflective

Observation into the Assimilating phase. In this study, FCM showed its strength as a method for

describing the situation in an engaging manner and FCM proved to be a useful tool for eliciting the

informant’s perception, as pointed out by Maurel (ed) (2003). The informants were presented with

29

the fuzzy cognitive map during the interview and in this manner the informants were included in

developing the model.

ActiveExperimantation

ConcreteExperience

ReflectiveObservation

AbstractConceptualization

Ia. Judge the situation to beimproved or monitored

II. Describe the situation

III. Define transformations

IV. Develop models

V. Compare models with reality

VI. Debate desirable and feasible changes

VII. Implementation

Ib. Perceive the situation

Accommodating Diverging

Assimilating

Converging

Figure 11: A system approach to collaborative learning when dealing with situations, presented through four phases: Diverging, Assimilating, Converging and Accommodating. Four learning styles are present: Concrete Experience, Reflective Observation, Abstract Conceptualisation and Active Experimentation and seven stages in working with a situation are presented in I-VII (Wilson & Morren presented by Daniels & Walker 2001).

From Assimilating, a process moves through Abstract Conceptualisation into the third phase,

Converging. During Converging, FCM can, as pointed out by Maurel (ed) (2003), be used as a tool

for improving communication between stakeholders. This can be done by using FCM in debating

desirable and feasible changes in the landscape by illustrating the different perceptions and values

in a group session with the informants. In this study, FCM and the twenty-two concepts were

introduced at the group meeting. The informants’ responded that they regarded FCM as a very

30

technical method, which was difficult to fully comprehend in the short time available. Firstly, this

showed that the structure and the analyses of FCM can be very mathematical and complex which

affected the participatory process negatively. Secondly it showed that fuzzy cognitive maps quickly

can become difficult to cope with as more concepts are included. If the aim of FCM is to obtain an

understanding of the landscape, many concepts may be necessary, but when FCM is used as a

participatory tool, focus should be on FCM as a communicative tool. In this manner, FCM can

provide an understanding among the participants of each other’s perceptions through a social

learning process. Fuzzy cognitive mapping should, in order to take full advantage of its potential for

social learning, be applied in group sessions. It could be an advantage to create fuzzy cognitive

maps based on predefined concepts which have been identified during individual semi-structured

interviews with the informants prior to the group sessions. In this manner, the participants

perception could be collected free of influence from other stakeholders.

Lastly, a process moves through Active Experience into Accommodating. This study did not

consider implementation and FCM’s role during accommodating will be of smaller importance, but

a dynamic analysis might provide an understanding of the landscape which can be useful in the

implementation phase. The last stage in accommodating is Concrete Experience which will lead

through the circle anew.

FCM can be applied as an Information and Communication Tool in a Social learning context

(Maurel (ed) 2003). The aim of applying FCM as a tool in communication may be to clarify the

participants’ values and positions, either to clarify differences or to reach a common understanding

of the value in the area. A common understanding may be important in relation to conflict

occurrence and escalation of existing conflicts, and can be used to identify the values that are

commonly agreed upon in the area: “the common third”. Identification and agreement on the “the

common third” can lead to a feeling of ownership for the area (Nielsen & Nielsen 2006) and be

used when creating a brand of the area (Jensen 2007) which may be the next step in “National Park

Mols Bjerge”.

31

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Appendix I: Photographs from the interview locations

Trehøje – The Vast .......................................................................................................................ii

Skovbjerg – The Intimate............................................................................................................iv

Tinghulen – The Social ...............................................................................................................vi

Vistoft Plantage – The Wild ......................................................................................................viii

Agri Bavnehøj – The Treasured ..................................................................................................x

Århus Plantage – The Controlled...............................................................................................xii

Trehøje – The Vast

ii

Trehøje – The Vast

iii

Skovbjerg – The Intimate

iv

Skovbjerg – The Intimate

v

Tinghulen – The Social

vi

Tinghulen – The Social

vii

Vistoft Plantage – The Wild

viii

Vistoft Plantage – The Wild

ix

Agri Bavnehøj – The Treasured

x

Agri Bavnehøj – The Treasured

xi

Århus Plantage – The Controlled

xii

Århus Plantage – The Controlled

xiii

Appendix II: Interview guide and guidelines for conducting the interviews

Interview guide ............................................................................................................................ii

Guide to conduct the interviews..................................................................................................iii

Interview guide

Research questions Interview questions What does the informant perceive as important concepts in this landscape, and how is this being influenced by other concepts?

When you experience this place: What is important for you? What do you appreciate? What do you not like?

What: Affects X Causes X to have the value you describe?

Which factors (natural changes, human activities etc) can change this system?

What Do you believe can change this picture? Have changed since you started coming

here? (natural changes / changes caused by humans

What if: More people are coming? More noisy people are coming? There are decided limitations to the

management? There are decided limitations to the

traffic? How affects these concepts each other (positively, negatively, feed back mechanisms)?

What happens with X when Y becomes larger/smaller? What happens then with Z?

How strong are these effects (small, medium, large)?

How: Large effect positive/negative effect does concept X have on concept Y (small/medium/large)? Important is it for concept X that concept Y changes (small/medium/large)?

ii

Guide to conduct the interviews

Introduction (before we leave for the first location)

Who am I and what do I study?

I study landscape management on Copenhagen University, the former “Landbohøjskole”. I write

my master thesis at DMU at Kalø.

What is the purpose of the project?

The purpose of the project is to talk with people who have different interests and connections to

Mols Bjerge (the protected area) and draw a picture of their perception of different locations in

Mols Bjerge. I do this in order to consider many different perceptions in a future plan and

management of the area.

What will happen now?

We drive out to three locations, where we talk 30-45 minutes each place. We start at Trehøje, then

drive to Skovbjerg and lastly Tinghulen. I you after to day would like to continue to participate in

my study, I would like us to visit Vistoft Plantage, Agri Bavnehøj and Århus Plantage an other day.

Background information (small talk while we drive)

The informants:

Affiliation to the area

Use of the area

Interests in the area

Interests in the National Park

Experiences regarding changes in the area

Notes for the second interview session

Thank you for participating in this study, it is very useful for me.

Small talk while we drive:

Have anything new happen since we last meet?

What do you think of the interviews at our last meeting (positive/negative)?

iii

iv

Interview – creating the FCM

See the interview guide

Practical issues

Write on A3 paper

Use a pencil – it works in rainy weather

Aim at a map containing 8-12 (max 15) concepts (do this by focusing on how detailed the

map is getting. Draw some generalisation is necessary (finding a concept which covers two

or more concepts).

Verify that I have understood the answers correctly by asking:

o “is it correctly understood that….”

o “does that mean that……”

o “have I understood you correctly, that you…..”

o Etc.

Remember to listen – give the informant time to think

Do not lead the informant to specific concepts, but help them instead by:

o Rephrasing the question

o Give different options

Use their words in describing the concepts. If I add some concepts, remember to get the

informant to validate the wording of the new concept.

Closure

What will happen now?

I will type up the maps and put all your maps together in one covering the whole Mols Bjerge.

I would like us to meet again in a few weeks to visit the other three location, if you are interested.

I plan for a meeting where all the informants participate where I present my finding, and where you

can discuss the findings together.