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.