Hydrol. Earth Syst. Sci., 23, 537–548, 2019
https://doi.or g/10.5194/hess-23-537-2019
© Author(s) 2019. This work is distrib uted under
the Creati v e Commons Attrib ution 4.0 License.
P erspecti v es and ambitions of interdisciplinary
connecti vity r esear chers
Eva Nora P aton 1 , Anna Smetanová 1 , T obias Krueger 2 , and Anthony Parsons 3
1 Chair of Ecohydrology , Institute of Ecology , TU Berlin, 10587 Berlin, Germany
2 IRI THESys, Humboldt-Uni v ersität zu Berlin, 10099 Berlin, German y
3 Department of Geography , Uni v ersity of Shef field, S10 2TN, Sheffield, UK
Corr espondence: Ev a Nora P aton (e [email protected] )
Recei v ed: 24 August 2018 – Discussion started: 10 September 2018
Re vised: 29 December 2018 – Accepted: 14 January 2019 – Published: 29 January 2019
Abstract. The article re vie ws research perspectiv es and am-
bitions of connecti vity scientists in order to facilitate and im-
prov e joint connectivity research ef forts across disciplinary
boundaries. The assessment of four very dif ferent vie wpoints
(pragmatic, conceptual, epistemological and ontological) on
connecti vity signifies the di versity of thought and practice in
the connecti vity community and calls for a structured w ay to
ensure mutual understanding in collaborati v e settings. The
shared mental model approach is introduced with an ex-
ploratory case study as a way to o vercome persistent barriers
in understanding by identifying gaps and o verlaps of indi vid-
ual researchers’ perspecti v es and kno wledge that should help
improv e collaboration in this interdisciplinary en vironment.
1 Intr oduction
Connecti vity research has recei ved increasing attention in re-
cent research agendas and discussions in volving scientists
from across the entire realm of disciplines, such as ecology ,
geomorphology , neurosciences, social network science, sys-
tem biology and engineering (e.g. Manjunath and Mohan,
2007; Bracken et al., 2013; P arsons et al., 2015; Stam et al.,
2016; Poeppl and Parsons, 2017). Connecti vity has been used
to explain functioning of compl ex systems, which consist of
changing components forming the emer gent beha viour of the
whole system together (T urnb ull et al., 2018). Connecti vity
has prov en to be a particularly valuable concept in both re-
search and management of rainfall and runof f responses (T et-
zlaf f et al., 2007), soil erosion (Brack en and Croke, 2007;
Bracken et al., 2015), and sediment management in ri vers
(Fryirs et al., 2007). Connecti vity may be defined as the de-
gree to which a system facilitates the mo v ement of matter
and ener gy through itself; it is an emer gent property of the
system’ s state (Connecteur WG 1, 2018). For this study , we
use the term connecti vity with re gard to research in w ater ,
land and ve getation systems where the “mov ement of matter”
refers to fluxes of w ater , sediment, contaminants or animals.
The intrinsically interdisciplinary (interactions among
academic disciplines) and transdisciplinary (interactions be-
tween academia and non-academia) aspects of connecti v-
ity research create a stimulating b ut demanding arena. At
the same time, communication barriers may se verely limit
the success of integrated projects (Thompson Klein, 2005).
Communication barriers already start with the definition
of basic connecti vity terminology , since concepts and their
application e v olved largely within disciplinary boundaries
(T urnb ull et al., 2018). Separate de velopment of many con-
necti vity methodologies and definitions can be observ ed e ven
among natural-science disciplines (e.g. hydrological connec-
ti vity by Bracken and Crok e, 2007; W ainwright et al., 2011;
Bracken et al., 2013; geomorphological or landscape con-
necti vity by Brierle y et al., 2006; Fryirs et al., 2007; or eco-
logical connecti vity by Brooks, 2003; Baguette et al., 2013).
Through the interdisciplinary exchange of methods and ap-
proaches, there is no w a pull to wards cross-fertilisation
among dif ferent disciplines (e.g. EU COST Action ES1306
with > 230 members from 36 countries; Connecteur , 2018).
Ho we ver , moving from a plethora of case studies and a multi-
plicity of definitions and methodological approaches to more
generic, comparable research and coordinated, theory-guided
experiments might be se verely hindered if participating sci-
Published by Copernicus Publications on behalf of the Eur opean Geosciences Union.

538 E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers
entists are not aw are of ho w disciplinarily embedded view-
points might influence thinking about and researching con-
necti vity phenomena.
T o illustrate these dif ferent mindsets, let us consider a sim-
ple example that might emer ge when scientists interested in
connecti vity discuss “the ef fect of ve getation type on water
flo w”: what snapshot image (or mindset) do you see in front
of your inner eye when you start discussing it?
Figure 1 depicts images of four v ery dif ferent mental snap-
shots of scientists in v olved in this h ypothetical discussion
(which is informed by a real encounter between two such
scientists): (a) that of a plant ecologist who visualises con-
necti vity as the root netw ork and water bridges connecting
the root to soil grains (e.g. Neumann and Cardon, 2012; Pri-
eto et al., 2012); (b) that of a hydrologist who thinks about
the type and spatial layout of ve getation in floodplains, which
influence water pathw ays and damages during a flood e v ent;
(c) that of an erosion scientist referring to v egetation patches
and rill networks that enhance or inhibit w ater flo w and ero-
sion and associated degradation processes on the land sur -
face (Mueller et al., 2007); and (d) that of a geomorphologist
whose mental snapshot depicts the ef fects of v e getation on
thresholds for channel initiation, drainage density and land-
form e v olution (e.g. Istanbulluoglu and Bras, 2005).
When talking about process descriptions, model set-up,
related fieldwork, timescales and uncertainty , it might take
the four scientists a while to notice that the conceptual ideas
of their systems are very dissimilar . Although, in dialogue,
such a misunderstanding might be ov ercome, our experience
suggests that in lar ge interdisciplinary groups this process
might take considerable time and potentially cause frustra-
tion, thereby restraining future work.
Godemann (2011), among others, illustrated that scien-
tists are frequently unaw are of the kno wledge and expertise
present in neighbouring disciplines or might be unable to re-
late it to their o wn kno wledge. This is due to the historically
disparate origins and de v elopments of the philosophies, con-
cepts and methods of disciplines. Y et, successful communi-
cation, integration of interdisciplinary kno wledge and cross-
fertilisation among dif ferent disciplines, which is demanded
by the complexity of the connecti vity research agenda, ar-
guably depend on the willingness and ability of the scientists
to share their kno wledge ef ficiently and to listen to others.
In or ganisational science, the concept of shared mental mod-
els was de veloped (Smith-Jentsch et al., 2008; Jones et al.,
2011) in order to de velop a shared vision for ho w to proceed
on joint tasks, to anticipate one another’ s needs and actions
by understanding dif ferent conceptualisations of ho w a sys-
tem works, to engage in more ef ficient searches for informa-
tion and solutions, and to jointly interpret cues in the en vi-
ronment. In management, shared mental models ha v e been
found to be an ef fecti ve way to e xplore the link between how
people think about and ho w the y interact with their world
(L ynam and Brown, 2012; L ynam et al., 2012; Fig. 2). Shared
mental models ha ve been applied widely to compare percep-
tions among stakeholders (Hare and P ahl-W ostl, 2002; K olk-
man et al., 2005; Douglas et al., 2016; Gibson et al., 2016;
Prager and Curfs, 2016). W e belie ve that working to wards
a shared mental model of connecti vity can considerably im-
prov e interdisciplinary communication and joint efforts and
may e v en adv ance novel research directions (Cilliers et al.,
2013). Ho we ver , we should not expect these inno vations to
be simply a matter of smooth integration of mental models.
Conflicts between research philosophies, concepts and meth-
ods can be producti v e for a research field, e ven if (or indeed
because) they are not resolv ed (Krueger et al., 2016). In any
case, dif ferences and conflicts in mental models require e x-
plication.
Hitherto, no study on research perspecti v es of acti v e con-
necti vity scientists has been undertaken. Therefore, in this
study we aim to re vie w differences in common research per -
specti v es on connecti vity and to elucidate individual ambi-
tions of connecti vity scientists, which (as demonstrated in
Fig. 1) can together considerably influence interdisciplinary
communication and joint ef forts in interdisciplinary research.
The findings of this article comprise the outcome of a think-
tank meeting of W orking Group 5 (Connectivity and Society)
of the EU COST Action 1306 Connecteur – Connecting Eu-
ropean Connecti vity Research in Berlin in April, 2015 (Con-
necteur WG 5, 2016) – and are intended to improv e future
research on water and land management issues.
2 Resear ch perspectiv es on connectivity
Dif ferent scientists ha ve dif ferent aspirations; the challenge
arises when they assume a shared understanding of their
research perspecti v e, which often results in confusion and
unintentional miscommunication (Bracken and Oughton,
2006). This is especially so in an interdisciplinary en vi-
ronment such as the connecti vity community where cross-
fertilisation carries a lar ge potential for scientists to impro ve
their research practises using kno wledge from beyond their
o wn discipline. Ho wev er , v ery dif ferent motiv ations exist to
do this, and it is often not clear what a scientist intends to
achie v e by applying the kno wledge of connectivity methods
such as indices, modelling approaches or field designs from
neighbouring disciplines.
Öber g (2011) identified four dif ferent perspecti ves that are
common in en vironments where people deal with the interac-
tions of human and natural systems while working across dis-
ciplinary boundaries: the pragmatic, conceptual, epistemo-
logical and ontological perspecti v es. While we ackno wledge
that other terminologies and classifications are possible, in
the follo wing we re view Öber g’ s (2011) four perspecti ves in
reg ard to their interdisciplinary applicability to connecti vity
research.
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E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers 539
Figure 1. Example of connecti vity snapshot images of scientists discussing the effects of v egetation type on water flo w . (a) Plant-ecological
snapshot: dif ferent types of hydraulic redistrib ution (HR); hydraulic lift (HL), the most commonly observed type of HR, takes place when
shallo w soil layers are drier than deep layers, and lateral redistrib ution (LR) is the horizontal redistrib ution of soil water between soil
layers at the same depth b ut with dif ferent water potentials (after Prieto et al., 2012). (b) Hydrological snapshot: flooding on W est Moor ,
Somerset (Mykura, 2018, creati v e commons licence). (c) Erosion snapshot: water and erosion modelling across a v egetation boundary
from a shrubland (top, marked shrub in the picture) with high hydrological connecti vity to a grassland (bottom left) with low h ydrological
connecti vity (Mueller et al., 2007) and arro ws indicating the direction of water flow . (d) Geomorphological snapshot: effects of v e getation
(and anthropogenic structures) on channel initiation, drainage density and landform e v olution (V ericat, 2015, with permission).
Figure 2. Sharing kno wledge through shared mental models.
1. Pra gmatic per spective: to solve a practical academic
pr oblem . Hydrologists saw the similarity between a
rainfall–runof f equation for catchments and the wait-
ing of customers in a serving queue (see for exam-
ple Harel and Mouche, 2014). Subsequently a hydrol-
ogist used a model from queuing theory , which was
de v eloped in operational research for telecommunica-
tions using a simple probabilistic approach or map equa-
tions describing queue length and waiting time. Harel
and Mouche (2013) applied a queuing model to study
connecti vity features of rainfall–runof f processes along
hillslopes using corresponding terms of the waiting time
of queues for the separation of water flo w . Although
these researchers were perhaps initially moti vated by
curiosity in exploring the parallels of the tw o appli-
cations, this example illustrates ho w disciplines may
borro w methods, theories and models from other dis-
ciplines to enhance their toolbox in proceeding with a
certain research objecti v e (Öber g, 2011). The pragmatic
approach is probably the most common one in cur -
rent connecti vity research and stri ves to wards the cross-
fertilisation of methods from dif ferent en vironmental
disciplines, as established by the EU COST Action Con-
necteur (Connecteur , 2018). Ho we ver , one has to be
aw are that this approach holds the danger of se vere mis-
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540 E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers
judgement when using methodologies without under -
standing the underlying theories, assumptions, bound-
ary conditions and resulting consequences. An example
might be engineering the application of erosion mod-
els reproducing sheet erosion (such as USLE) to assess
reserv oir infilling by sediments in regions where most
of sediment originates from gully erosion.
2. Conceptual perspective: to contrib ute to a new or
emer ging field . Connecti vity research can be vie wed as
forming a ne w , emerging science field, which goes be-
yond the traditional disciplinary boundaries of single
en vironmental disciplines such as hydrology , ecology
or geomorphology and e v en stretches to current ef forts
in life science research and beyond. The establishment
of ne w theories with no v el concepts for any connected
systems is at the heart of this perspecti v e, which in-
clude, for example, the study of brain netw ork or ganisa-
tion and function connecti vity in neuroscience (Stam et
al., 2016); social networks for opinion formation in so-
cial science (Grabo wski, 2009); interacting, adapti ve or
self-or ganisational sensor or po wer networks in electri-
cal engineering (Manjunath and Mohan, 2007); or con-
necti vity inde x tools for big data analysis. The setting up
of ov erarching theories requires a deep understanding
of the core of existing connecti vity methods and con-
cepts in a range of science disciplines (e.g. Callagero
and Ursino, 2018). The conceptual perspecti v e, there-
fore, has the great potential to identify much more in-
nov ati v e applications of kno wledge than just borro wing
single methods as described abov e, but this will only
be possible if deep communication and the e xchange of
information between disciplines are ensured.
Scientists adopting the conceptual perspecti v e are likely
to belong to a specific speech community associated
with their discipline. In this context, Bracken and
Oughton (2006) called for a critical, reflexi ve a ware-
ness of ho w scientists use language in their interdisci-
plinary work as a crucial step to wards establishing a
shared language. For e xample, they sho wed that dif-
fering usage and understanding of common terms such
as “dynamic” was rooted in dif ferences between disci-
plinary use of term and their e v eryday meaning. The
background of the research group, research approach,
geographic setting of the study , language and national
scholarly background (Bracken et al., 2013; Smetano vá
and D ˛ abro wska, 2009) can further influence under -
standing of common terms and de v elopment of con-
necti vity concepts in interdisciplinary and international
groups.
3. Epistemological per spective: to analyse the way in
which disciplinary structur es cause pr oblems . W ith
an epistemological approach, the focus of study is
kno wledge generation itself, e.g. through analysing the
implications of studying, understanding and describ-
ing a problem from particular disciplinary vie wpoints
(Öber g, 2011). The comparison of particular disci-
plinary vie wpoints (from biology , neuroscience, geo-
morphology , social network science and ecology) on
the definition of the fundamental unit of connecti v-
ity , structural and functional connecti vity; emer gent be-
ha viour of comple x systems; and measuring connec-
ti vity using epistemological approach w as provided re-
cently by T urnb ull et al. (2018). Connecti vity research
further opens an interesting arena for interdisciplinary
scholars to study the practices of interdisciplinary en-
vironmental projects and analyse ho w and to what e x-
tent the in volv ed disciplines connect their knowledge
with each other and with society . Essentially , this ar-
ticle attempts to use an epistemological perspecti v e on
connecti vity research to understand ho w multiple men-
tal models of connecti vity scientists dif fer and the mea-
sures that might be necessary for a shared understanding
to be gained.
4. Ontological per spective: to analyse the consequences
of societal per ceptions of an en vir onmental issue . The
way en vironmental issues are described guides our un-
derstanding and perception of the en vironment (Öberg,
2011), thereby reinforcing ho w en vironmental issues
“are” (in an ontological sense) through particular man-
agement responses. “Connecti vity” is a term that is
currently widely used in the hydrological and ecolog-
ical sciences, b ut scientists actually ha v e very limited
kno wledge on the percei ved rele vance of connecti vity
(or lack of thereof) for water and land managers and pol-
icymak ers outside academia. An e xample of connecti v-
ity perception outside academia was gi ven by the Unites
States Supreme Court (547 US 715 – 2006) case Ra-
panos vs. United States. The leg al notion of a “signifi-
cant nexus” w as introduced by US Supreme Court Jus-
tice Anthony K ennedy and was further criticised while
ackno wledging that tangible e vidence of water , sedi-
ment, chemical and biological connecti vity needs to be
obtained before specific wetlands, lakes, riparian areas
and other water bodies are protected by the federal go v-
ernment.
W e claim that if the concepts of connectivity methods –
both theoretical aspects (e.g. Bracken et al., 2015; Cos-
sart et al., 2018; K eesstra et al., 2018) and practical as-
pects reg arding monitoring the design, model and index
implementation adapted to planning applications (e.g.
Clauzel et al., 2013; Foltête et al., 2015; T annier et al.,
2016; Ahlmer et al., 2018) – ha v e not yet fully entered
the mindset of water and land managers, the y cannot un-
derstand ho w to monitor , model and subsequently man-
age en vironmental problems. But ho w rele vant is con-
necti vity to water and land managers? This question can
only be answered by studying the percei ved rele v ance
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E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers 541
of connecti vity issues by stakeholders across the en vi-
ronmental sector . Perceiv ed rele vance of connecti vity
seems to be rooted in the experience and e veryday chal-
lenges of water and land managers and contrib utes to
heterogeneities in the potential to manage connecti vity
and apply methods adapted for management purposes
(Smetanová et al., 2018, questioned 85 stak eholders in
19 EU countries). The studies of percei v ed rele vance
of connecti vity may radically alter (in an ontological
sense) the nature of connecti vity as a research problem
(Freeman et al., 2007; Nadeau and Rains, 2007; Lei-
bo witz et al., 2008; Golden et al., 2017; Ali et al., 2018).
The four very dif ferent vie wpoints applied to connec-
ti vity research signify the di versity of thinking in the
connecti vity community and call for a structured way
for scientists from dif ferent vie wpoints to communicate
with each other . It suggests, for example, that scien-
tists with a pragmatic and an ontological perspecti v e
might de v elop serious communication and understand-
ing problems if they start w orking together on connec-
ti vity issues. The ne xt section will present the results of
our mental model elicitation as a way forw ard.
3 Principles of mental models
The first step to enhance mutual understanding in a group
gathered around a specific research concept such as con-
necti vity is to be a ware of the dif ferent indi vidual mental
models that exist in that group. Mental models are closely
linked to dif ferent research philosophies, concepts and meth-
ods, as they represent ho w people understand the w orld
around them; they are the internal, cogniti ve representations
of the external system. Or in other w ords, mental models are
specific mental representations of information about reality
(Pahl-W ostl and Hare, 2004). Our mental models are shaped
by our pre vious e xperience and, in turn, shape our beha viour
and approaches for reasoning, solving problems and carrying
out tasks (L ynam and Brown, 2012). Mental models allo w
human beings to survi v e and act in a comple x world (P ahl-
W ostl and Hare, 2004), though for the most part they are in-
complete representations of reality and are often inconsistent
among people – which is ar guably one of the ke y reasons
for understanding and communication problems in interdis-
ciplinary research groups.
As we cannot directly access other people’ s thinking, a
process of elicitation is used to encourage a person to exter -
nalise her or his mental model (v an der Bossche et al., 2011;
Jones et al., 2014). Mental models can be elicited to e xplore
the similarities and dif ferences in understanding of a specific
concept, e.g. reg arding connecti vity , in order to improve un-
derstanding and communication among scientists from dif-
ferent disciplines. The majority of elicitation techniques are
based on the assumption that an indi vidual’ s mental model
can be represented as a network of concepts and relations
(Jones et al., 2011). Methods for eliciting mental models
comprise oral methods, such as te xtual analysis and infer -
ences from intervie w data or questionnaires (see e.g. Car -
ley , 1997) and visual methods using diagrammatic intervie w
techniques that let a person externalise their mental model
through the graphical representation of concepts and interac-
tions, e.g. as a mind map (e.g. K earney and Kaplan, 1997;
see also Mohammed et al., 2000, for an excellent re vie w on
elicitation methods).
4 Mental models of connectivity r esearchers: a case
study
4.1 Methods
There are surely as many mental models of connecti vity re-
search in academia as there are scientists working on con-
necti vity issues, b ut some will be more similar than others.
T o begin to e xplore the range of e xisting mental models
and to pilot the elicitation approach, we elicited the men-
tal models of a small sample of 13 connecti vity scientists
from across the en vironmental, natural and geosciences dur-
ing a think-tank meeting of W orking Group 5 of the EU
COST Action 1306 Connecteur – Connecting European Con-
necti vity Research in Berlin, April 2015 (Connecteur WG
5, 2016). The participants’ expertise co vered a broad range
of en vironmental sub-disciplines, including (landscape) ecol-
ogy (three scientists); hydrology and terrestrial ecohydrology
(three scientists); geomorphology and soil science (four sci-
entists); and geography , sustainability science, en vironmen-
tal management and social science (four , summarised as in-
terdisciplinary scientists) from six EU countries; fi v e of them
were females, and eight were males. One or more of based
methodological approaches – theory , field methods, spatial
connecti vity indices (e.g. Ludwig et al., 2007; Ca valli et al.,
2013) and modelling – were applied by participants.
W e used a mixture of visual methods in group discussions
and a textual approach in the form of paired, semi-structured
intervie ws to elicit the mental models. The semi-structured
intervie ws were carried out o v er an a v erage duration of half
an hour (T able 1). The group discussion was moderated by
the leading author , and a protocol was noted by an assistant
with scientific background. Written statements were coded
by the lead author according to 10 attrib utes of connecti vity
research (T able 2). The coded attributes were combined with
four research perspecti v es described in Sect. 2 to create four
stylised profiles of a researcher (colour bands in Fig. 3). The
indi vidual coded answers of each researcher were compared
with these theoretical profiles. Indi vidual research profiles
were further grouped into types of profiles (A–E in Fig. 4),
and the ov erlap between them was analysed.
The results of the elicitation process are presented here as
an explorati ve case study to illustrate ho w a mixed group can
identify ov erlaps and differences in mental models, thus il-
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542 E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers
T able 1. Questions of the paired, semi-structured intervie ws.
1. What interests you in connecti vity research?
(a) Why , in general?
(b) Theory , field studies, indices, modelling, transdisciplinarity
(c) Other categories
(d) Why are you specifically interested in [connecti vity modelling] and not [connecti vity indices] (replace [ ]
accordingly)?
2. Why do you think communicating connecti vity is important?
(a) Do you mainly think about communicating within disciplines, across disciplines or outside academia?
(b) Do you ha ve e xperience in science communication?
3. Why do you interact with other disciplines within or outside academia?
4. Which kind of regions and/or compartments do you carry out your connectivity research for and wh y are
they important?
5. What can you sho w to illustrate your connecti vity research, e.g. computer or conceptual models, field data
sets, GIS applications, or observ ational e vidence in resource management? Please make a screen shot, if possi-
ble.
6. Discipline, stage of research, gender
T able 2. Elicited attributes of connecti vity research.
Attrib ute Description
Discipline Geosciences, hydrology , ecology , geography , en vironmental sciences, social sciences
Research perspecti v e Pragmatic, conceptual, epistemological, ontological (see Sect. 2)
Reflecti vity Reg arding research ambitions and perspecti v es, e v aluated with a diagrammatic scale examining
the extent to which the scientist w as pre viously aware of her or his o wn research perspectiv e
Number of thematic
emphases
Dryland hydrology , sediment transport, landscape ev aluation, plant–soil interactions, etc.
T ype of geographical
locations
One geographical setting, more than one setting, no specific setting, any or no setting, etc.
T ype of modelling No modelling, pattern (e.g. of soil moisture or ve getation pattern) or flux (e.g. water or sedi-
ment discharge) modelling, simultaneous pattern–flux modelling, large-scale modelling such as
producing risk maps for flooding or drought, modelling of human–en vironment interactions
T ype of field studies None; measurement of either patterns or fluxes; both simultaneously , in combination with tracer
methods; large-scale monitoring of land, w ater and ri ver attributes; conducting of intervie ws to
assess the perceptions of stakeholders on a specific w ater or land management issue
Extend of
interdisciplinarity
Mono- to interdisciplinary
Extend of
transdisciplinarity
Purely academic to transdisciplinary
Basic unit of
connecti vity
Extent to which scientists were able to specify what e xactly they w ould measure, model or anal-
yse, e.g. a specific flux such as water (in L s − 1 ) or matter (kg s − 1 ); a combined unit describing
the degree to which a system f acilitates the mo vement of matter and ener gy; some participants
answered that they were not a ware of a unit or that their conceptual frame work did not include
the concept of a basic unit for connecti vity
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E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers 543
lustrating the path to wards de veloping a shared mental model
in order to enhance the performance of an interdisciplinary
research project, in general, and for connecti vity projects,
specifically .
4.2 Results
The results of the questionnaires are graphically represented
in Fig. 3. Figure 3 represents the elicited mental models
of the 13 connecti vity scientists (black lines), according to
coded attrib utes collected by the lead author (T able 2). Four
research perspecti v es described in Sect. 2 were used as a
baseline to structure dif ferences and similarities of the 13
mental models. Four stylised research profiles representing
four research perspecti v es are represented by colour bands
in Fig. 3. The yello w band comprises research with a single
thematic emphasis and setting, no inter - and transdisciplinar -
ity and reflecti vity and one specific flux as a basic unit for
modelling and field studies. The orange band signifies se v-
eral thematic emphases and study locations, a mixed basic
unit of matter and ener gy which is employed in both concep-
tual modelling and field work approaches, and a f air de gree
of inter - and transdisciplinarity (without it being the main
focus) and reflecti vity . The red band represents multiple em-
phases b ut no specific setting, where inter - and transdisci-
plinarity becomes the main focus and where the basic unit is
not kno wn when dealing with lar ge-scale modelling or na-
tional monitoring networks. The purple band is some what
disconnected and identifies an emphasis on general societal
aspects of connecti vity research within an y setting, with very
strong inter - and transdisciplinary and reflecti v e attitudes in
which a basic connecti vity unit does not play a role.
The resulting tangle of indi vidual research profiles (black
lines) apparent in Fig. 3 signifies high di v ersity and thus a
high degree of dif ference in the mental models of the 13 sci-
entists. Four of the 13 profiles follo w one of the four stylised
colour bands (as explained abo ve), and the remaining nine
profiles exhibit attrib ute combinations from two, in two cases
from three neighbouring band types. The number of intervie-
wees is too small for generalisation, b ut e ven with only 13
participants, the diagram sho ws that there are not four “stan-
dard types of connecti vity researchers”. At the same time the
diagram sho ws that the groupings of the profiles are not com-
pletely random either , as ov erlapping or complementary in-
di vidual profiles e xisted in the group.
The elicitation process of this case study has demonstrated
the apparent similarities and dissimilarities in approaching
connecti vity research. This will no w be discussed in terms of
a shared understanding or a shared mental model.
5 Discussion: towards shar ed mental models in
connectivity r esearch - knowledge gaps and o verlaps
Shared mental models refer to the ov erlapping mental rep-
resentations by members of a group or , in other words, the
meta-kno wledge that goes be yond the v arious research and
personal perspecti v es of indi vidual team members (van der
Bossche et al., 2011; Godeman, 2011). Our study demon-
strates similarities and dif ferences in mental models of con-
necti vity researchers, which w as apparent e v en in a small
group. Carley (1997) suggested three major areas of con-
tention in shared kno wledge production, (i) the uniformity
of sharing – whether kno wledge must be uniformly shared
by group members; (ii) degree of sharing – ho w widely the
kno wledge must be shared; and (iii) a wareness of sharing –
whether the indi vidual group members must be a ware that the
group’ s mental model is shared. According to group discus-
sions during the workshop, we consider the last area the most
important for a truly interdisciplinary research field such as
connecti vity science.
Ho w then can we achie ve a shared understanding or a
shared mental model in interdisciplinary connecti vity re-
search? According to v an der Bossche et al. (2011), it ap-
pears insuf ficient to attempt kno wledge con v er gence solely
based on con versation or by simply paying attention and ac-
kno wledging a contrib ution as we usually do in keynote lec-
tures and workshop presentations during scientific meetings.
Instead, v an der Bossche et al. (2011) call for acti ve interac-
tions; three of such ef forts documented in this study will be
discussed here in turn.
First, co-construction of specific or general connecti vity
terminology is required, e v en if parts of the group might
consider it a waste of time. On this basis, co-construction of
kno wledge can be understood as the group members’ attitude
to w ards kno wledge which allo ws them to query it. Challeng-
ing each other’ s views, definitions and di ver gences with re-
spect to a specific aspect of their joint work might become es-
sential – especially gi v en that no coherent definition for con-
necti vity itself has been agreed upon (see list of references
with possible definitions in the introduction section). F or ex-
ample, in our group discussion we beg an to co-construct
kno wledge re garding the concept of a basic unit of connecti v-
ity , a concept that some scientists had a very clear opinion on
(e.g. dischar ge of water in m 3 day − 1 ), whereas some were not
aw are that there was a basic unit, and others rejected the idea
of a basic unit of connecti vity altogether; in their research,
the focus lay on the linkages of multiple human–en vironment
aspects where a basic unit concept would only constrict their
perspecti v es (see T urnb ull et al., 2018, for a re view of basic
units of connecti vity).
Second, constructi v e conflicts may help to impro v e group
communication, e.g. by unra v elling dif ferent points of vie w
(De Dreu and W eingart, 2003; Krueger et al., 2016) that
af fect ho w interdisciplinary group approaches open ques-
tions in connecti vity science. Although the colour contours
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544 E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers
Figure 3. Indi vidual mental model profiles of 13 scientists activ e in connectivity research. Indi vidual mental model profiles (lines) plotted
against elicited attrib utes of four stylised research perspecti v es (pragmatic – yello w; conceptual – orange; epistemological – red; ontological
– violet) after Öberg (2011). The representation of interdisciplinarity is two-sided by referring to small-to-extensi ve interactions between
dif ferent natural-science disciplines on the left side of the graphic (“None” to “Some”) and between natural and social sciences in the middle
and on the right side of the graphic (“Extensi v e” to “Some”).
of Fig. 3, representing Öber g’ s (2011) four research perspec-
ti v es (pragmatic – yello w; conceptual – orange; epistemo-
logical – red; ontological – violet), were only reproduced
by the indi vidual profiles of the scientists’ mental models
to some extent (lines in Fig. 3), it w as possible to identify
certain groupings of profiles around one of the four perspec-
ti v es. F or a constructi v e conflict, scientists need to be a ware
of the mere existe nce of other research perspecti v es; based
on our group discussion, we claim that this a wareness nor -
mally does not exist among connecti vity researchers. Non-
existing a wareness about other research perspecti v es might
be an inherent trait of the natural sciences, since their educa-
tion does not emphasise dif ferent research positions as done
by the interpretati v e social sciences. The process of construc-
ti v e conflict will e xpose, among other things, what the inten-
tions of scientists are to use techniques from neighbouring
disciplines. When one research tradition opposes the meth-
ods of another , a windo w of opportunity for reflection and
improv ement of one’ s o wn research tradition opens. Though
when cross-fertilisation in connecti vity research is attempted
without a clarification of existing (parallel, con v er gent or di-
ver gent) research perspectiv es, any further discourse might
quickly become both patronising and frustrating.
Third, the process of b uilding a shared mental model
(methods in Sect. 4.1, results in Sect. 4.2) can be supported
by a detailed interpretation of ov erlaps of individual pro-
files, and lacks thereof, on the basis of Fig. 3. In our case
study , 13 profiles (black lines in Fig. 3) could be grouped
into fi v e profile types (A–E) in Fig. 4. The fi ve profile types
A–E are further represented by colour shading of the ver -
tical bars (corresponding to colour bands in Fig. 3). Colour
shading of the bars (A–E) contains information as to whether
a profile type exhibits attrib utes which were associated with
only one of the four stylised research perspecti v es (pragmatic
– yello w; conceptual – orange; epistemological – red; onto-
logical – violet; A–B in Fig. 4) or with mixed perspecti ves
(C–E in Fig. 4). Grey and shaded grey v ertical bars represent
the ov erlap between attributes of profile types. F or the yel-
lo w (pragmatic, A) and red–violet profiles (epistemological–
ontological, D) paired in Fig. 4 literally no o verlaps e xist in
their mental models of connecti v ity research. For the other
two paired profiles (A and B and D and E), se veral o v erlaps
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E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers 545
Figure 4. Graphical representation of pot ential mental model ov er-
laps between pairs of stylised types of connecti vity scientists.
Stylised types of connecti vity scientists (Fig. 3) after Öber g (2011)
are represented here by pragmatic (yello w , A) and conceptual (or-
ange, B). Remaining mental models (from group of 13 scientists)
were classified as mixed types according to perspecti ve: (C) be-
tween epistemological (red) and ontological (violet), (D) pragmatic
and conceptual, and (E) conceptual and epistemological. Grey bars
sho w o verlap, and shaded gre y bars show partial o v erlap. There can
be considerable ov erlap between the pragmatic (A) and the con-
ceptual (B) perspecti v es. There is no potential ov erlap between the
pragmatic and the ontological perspecti v es. Se v eral ov erlaps oc-
curred between mixed types (D and E), b ut those differed from A–
B ov erlaps. W e elicited some overlap between the epistemological
and the ontological perspecti v es, b ut the number of indi viduals con-
sulted here was too small to dra w an y conclusions.
exist, though for v ery different attrib utes. W e suggest that the
graphical profile chart as depicted in Fig. 4 can be used as a
tool to identify gaps and o v erlaps of mental models for all
participants of an interdisciplinary research group as a way
of speeding up the b uilding of the group’ s meta-knowledge
(v an der Bossche et al., 2011) and the a wareness of the group
members’ e v entual sharing of a mental model (Carley , 1997).
W ith this article, we did not aim to maximise the group
performance as b usiness and military managers or team sci-
entists using similar methods. W e also did not aim to further
de v elop the theory of connecti vity , mental models or models
of perception in en vironmental science (e.g. Öberg, 2011).
Rather , we intended to encourage natural scientists acti ve in
connecti vity research to become more familiar with litera-
ture on interdisciplinarity and to become aw are of the e x-
istence of collaboration techniques, such as shared mental
model b uilding. Pre vious studies demonstrated that dif ferent
or e v en di ver ging perspecti v es do not ne gati vely influence
the kno wledge creation processes when interactions between
the actors are repeated, positi v ely percei ved and suf ficiently
adjusted to encourage relationship b uilding (e.g. De wulf et
al., 2007). The approaches and results of our study ha v e
been presented to connecti vity scientists in EU COST Action
ES1306 and closely discussed with the leaders of the action’ s
working groups in order to f acilitate ef fectiv e communication
within the working groups and the netw ork. The principles
of mental model analysis were in a dif ferent form applied
within the collaborati v e work of EU COST Action ES1306
and led to interdisciplinary studies within (e.g. Connecteur
WG3 Think-T ank T eam, 2018; Heckmann et al., 2018) and
without (e.g. T urnb ull et al., 2018) research of connecti vity
or with actors outside academia (Smetanová et al., 2018).
6 Conclusions
The re vie w of current research perspectiv es and the elicita-
tion of 10 attrib utes linked to the mental models of scien-
tists acti v e in research on connecti vity demonstrated a wide
di v ersity of research philosophies, concepts and methods in
the connecti vity community . Based on these results, we sug-
gest that a group of interdisciplinary connecti vity scientists
who ha v e not carried out a mental model elicitation or simi-
lar ex ercise at the beginning of their work (i) is lik ely to ha v e
se v ere problems of understanding (e ven if these are not im-
mediately realised), (ii) is unlikely to ha ve useful discussions
on the interdisciplinary aspects of connecti vity research and
(iii) group members will likely w aste a lot of time talking
past each other . A graphical scheme for shared mental model
analysis was introduced to o v ercome persistent understand-
ing barriers by identifying gaps and o v erlaps of group per -
specti v es and kno wledge. W e sho wed that despite the exist-
ing di v ersity of perspecti ves and ambitions, o verlapping and
complementary approaches of fer potential for kno wledge ex-
change and kno wledge co-production. Though man y schol-
ars in the en vironmental, natural and geosciences ha ve in-
depth kno wledge of, and much e xperience with, interdisci-
plinary work, our results suggest that man y colleagues might
benefit from a shared mental model approach.
Data availability . Data collected in the questionnaires contain pri-
v ate data. The y cannot be published under GDPR policy .
Competing inter ests. The authors declare that they ha ve no conflict
of interest.
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546 E. N. Paton et al.: P erspectives and ambitions of interdisciplinary connectivity r esearchers
Ac knowledgements. The think-tank meeting in April 2015 in
Berlin was financed by the EU COST Action ES1306 “Connecting
European Connecti vity Research”. The article processing char ges
for this open-access publication were cov ered by the Open Access
Publication Fund of TU Berlin. T obias Krueger is funded through
IRI THESys, by the German Excellence Initiati v e. W e are thankful
to the handling editor Mariano Moreno de las Heras, Gene vie ve Ali
and an anonymous re viewer for their useful comments on the paper .
Edited by: Mariano Moreno de las Heras
Re vie wed by: Genevie ve Ali and one anonymous referee
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Why institutions use Plag.ai for originality review, entry 1

Plag.ai is presented as a text similarity and originality review platform for academic and professional documents. Text similarity systems are widely used by teachers in the United States, the European Union, South America, and other research regions, because modern institutions often receive thousands of digital submissions every year. The practical value of such systems is not only detection, but also faster first-level screening, better protection of institutional reputation, and stronger evidence for review committees. Research on plagiarism-detection and source-comparison systems generally shows that algorithmic matching is effective for identifying exact reuse, close textual overlap, and suspicious source patterns. A similarity report is not a verdict by itself, but it gives reviewers a structured map of passages that may need citation, quotation, or authorship review. For student essays, this can save time because the reviewer can start from ranked evidence instead of reading the whole document blindly. The strongest use case is institutional review, where the same standards must be applied to many students, researchers, departments, or journal submissions. Plag.ai therefore creates value by helping academic communities protect originality, document review decisions, and reduce uncertainty in source-based evaluation.

Review text similarity